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Spotnitz M, Ekanayake CD, Ostropolets A, McKhann GM, Choi H, Ottman R, Neugut AI, Hripcsak G, Natarajan K, Youngerman BE. Use of Recommended Neurodiagnostic Evaluation Among Patients With Drug-Resistant Epilepsy. JAMA Neurol 2024:2816508. [PMID: 38557864 PMCID: PMC10985618 DOI: 10.1001/jamaneurol.2024.0551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 01/07/2024] [Indexed: 04/04/2024]
Abstract
Importance Interdisciplinary practice parameters recommend that patients with drug-resistant epilepsy (DRE) undergo comprehensive neurodiagnostic evaluation, including presurgical assessment. Reporting from specialized centers suggests long delays to referral and underuse of surgery; however, longitudinal data are limited to characterize neurodiagnostic evaluation among patients with DRE in more diverse US settings and populations. Objective To examine the rate and factors associated with neurodiagnostic studies and comprehensive evaluation among patients with DRE within 3 US cohorts. Design, Setting, and Participants A retrospective cross-sectional study was conducted using the Observational Medical Outcomes Partnership Common Data Model including US multistate Medicaid data, commercial claims data, and Columbia University Medical Center (CUMC) electronic health record data. Patients meeting a validated computable phenotype algorithm for DRE between January 1, 2015, and April 1, 2020, were included. No eligible participants were excluded. Exposure Demographic and clinical variables were queried. Main Outcomes and Measures The proportion of patients receiving a composite proxy for comprehensive neurodiagnostic evaluation, including (1) magnetic resonance or other advanced brain imaging, (2) video electroencephalography, and (3) neuropsychological evaluation within 2 years of meeting the inclusion criteria. Results A total of 33 542 patients with DRE were included in the Medicaid cohort, 22 496 in the commercial insurance cohort, and 2741 in the CUMC database. A total of 31 516 patients (53.6%) were women. The proportion of patients meeting the comprehensive evaluation main outcome in the Medicaid cohort was 4.5% (n = 1520); in the commercial insurance cohort, 8.0% (n = 1796); and in the CUMC cohort, 14.3% (n = 393). Video electroencephalography (24.9% Medicaid, 28.4% commercial, 63.2% CUMC) and magnetic resonance imaging of the brain (35.6% Medicaid, 43.4% commercial, 52.6% CUMC) were performed more regularly than neuropsychological evaluation (13.0% Medicaid, 16.6% commercial, 19.2% CUMC) or advanced imaging (3.2% Medicaid, 5.4% commercial, 13.1% CUMC). Factors independently associated with greater odds of evaluation across all 3 data sets included the number of inpatient and outpatient nonemergency epilepsy visits and focal rather than generalized epilepsy. Conclusions and Relevance The findings of this study suggest there is a gap in the use of diagnostic studies to evaluate patients with DRE. Care setting, insurance type, frequency of nonemergency visits, and epilepsy type are all associated with evaluation. A common data model can be used to measure adherence with best practices across a variety of observational data sources.
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Affiliation(s)
- Matthew Spotnitz
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Cameron D. Ekanayake
- Department of Neurological Surgery, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Anna Ostropolets
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Guy M. McKhann
- Department of Neurological Surgery, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Hyunmi Choi
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Ruth Ottman
- Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- The Gertrude H. Sergievsky Center, Columbia University Irving Medical Center, New York, New York
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
- Division of Translational Epidemiology and Mental Health Equity, New York State Psychiatric Institute, New York
| | - Alfred I. Neugut
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
- Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Herbert Irving Comprehensive Cancer Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - George Hripcsak
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Karthik Natarajan
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Brett E. Youngerman
- Department of Neurological Surgery, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
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2
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Link-Gelles R, Rowley EA, DeSilva MB, Dascomb K, Irving SA, Klein NP, Grannis SJ, Ong TC, Weber ZA, Fleming-Dutra KE, McEvoy CE, Akinsete O, Bride D, Sheffield T, Naleway AL, Zerbo O, Fireman B, Hansen J, Goddard K, Dixon BE, Rogerson C, Fadel WF, Duszynski T, Rao S, Barron MA, Reese SE, Ball SW, Dunne MM, Natarajan K, Okwuazi E, Shah AB, Wiegand R, Tenforde MW, Payne AB. Interim Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccines Against COVID-19-Associated Hospitalization Among Adults Aged ≥18 Years with Immunocompromising Conditions - VISION Network, September 2023-February 2024. MMWR Morb Mortal Wkly Rep 2024; 73:271-276. [PMID: 38547037 PMCID: PMC10986819 DOI: 10.15585/mmwr.mm7312a5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
In September 2023, CDC's Advisory Committee on Immunization Practices recommended updated 2023-2024 (monovalent XBB.1.5) COVID-19 vaccination for all persons aged ≥6 months to prevent COVID-19, including severe disease. As with past COVID-19 vaccines, additional doses may be considered for persons with immunocompromising conditions, who are at higher risk for severe COVID-19 and might have decreased response to vaccination. In this analysis, vaccine effectiveness (VE) of an updated COVID-19 vaccine dose against COVID-19-associated hospitalization was evaluated during September 2023-February 2024 using data from the VISION VE network. Among adults aged ≥18 years with immunocompromising conditions, VE against COVID-19-associated hospitalization was 38% in the 7-59 days after receipt of an updated vaccine dose and 34% in the 60-119 days after receipt of an updated dose. Few persons (18%) in this high-risk study population had received updated COVID-19 vaccine. All persons aged ≥6 months should receive updated 2023-2024 COVID-19 vaccination; persons with immunocompromising conditions may get additional updated COVID-19 vaccine doses ≥2 months after the last recommended COVID-19 vaccine.
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3
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Adams K, Weber ZA, Yang DH, Klein NP, DeSilva MB, Dascomb K, Irving SA, Naleway AL, Rao S, Gaglani M, Flannery B, Garg S, Kharbanda AB, Grannis SJ, Ong TC, Embi PJ, Natarajan K, Fireman B, Zerbo O, Goddard K, Timbol J, Hansen JR, Grisel N, Arndorfer J, Ball SW, Dunne MM, Kirshner L, Chung JR, Tenforde MW. Vaccine Effectiveness Against Pediatric Influenza-A-Associated Urgent Care, Emergency Department, and Hospital Encounters During the 2022-2023 Season: VISION Network. Clin Infect Dis 2024; 78:746-755. [PMID: 37972288 PMCID: PMC10954409 DOI: 10.1093/cid/ciad704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/27/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND During the 2022-2023 influenza season, the United States experienced the highest influenza-associated pediatric hospitalization rate since 2010-2011. Influenza A/H3N2 infections were predominant. METHODS We analyzed acute respiratory illness (ARI)-associated emergency department or urgent care (ED/UC) encounters or hospitalizations at 3 health systems among children and adolescents aged 6 months-17 years who had influenza molecular testing during October 2022-March 2023. We estimated influenza A vaccine effectiveness (VE) using a test-negative approach. The odds of vaccination among influenza-A-positive cases and influenza-negative controls were compared after adjusting for confounders and applying inverse-propensity-to-be-vaccinated weights. We developed overall and age-stratified VE models. RESULTS Overall, 13 547 of 44 787 (30.2%) eligible ED/UC encounters and 263 of 1862 (14.1%) hospitalizations were influenza-A-positive cases. Among ED/UC patients, 15.2% of influenza-positive versus 27.1% of influenza-negative patients were vaccinated; VE was 48% (95% confidence interval [CI], 44-52%) overall, 53% (95% CI, 47-58%) among children aged 6 months-4 years, and 38% (95% CI, 30-45%) among those aged 9-17 years. Among hospitalizations, 17.5% of influenza-positive versus 33.4% of influenza-negative patients were vaccinated; VE was 40% (95% CI, 6-61%) overall, 56% (95% CI, 23-75%) among children ages 6 months-4 years, and 46% (95% CI, 2-70%) among those 5-17 years. CONCLUSIONS During the 2022-2023 influenza season, vaccination reduced the risk of influenza-associated ED/UC encounters and hospitalizations by almost half (overall VE, 40-48%). Influenza vaccination is a critical tool to prevent moderate-to-severe influenza illness in children and adolescents.
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Affiliation(s)
- Katherine Adams
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Zachary A Weber
- Department of Clinical Research, Westat, Rockville, Maryland, USA
| | - Duck-Hye Yang
- Department of Clinical Research, Westat, Rockville, Maryland, USA
| | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Malini B DeSilva
- Department of Research, HealthPartners Institute, Minneapolis, Minnesota, USA
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Stephanie A Irving
- Department of Science Programs, Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Allison L Naleway
- Department of Science Programs, Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Suchitra Rao
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Manjusha Gaglani
- Department of Pediatrics, Section of Pediatric Infectious Diseases, Baylor Scott & White Health and Baylor College of Medicine, Temple, Texas, USA
- Department of Medical Education, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Shikha Garg
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Anupam B Kharbanda
- Department of Emergency Medicine, Children's Minnesota, Minneapolis, Minnesota, USA
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
- School of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Toan C Ong
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Peter J Embi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
- Medical Informatics Services, New York-Presbyterian Hospital, New York, New York, USA
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Julius Timbol
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - John R Hansen
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Sarah W Ball
- Department of Clinical Research, Westat, Rockville, Maryland, USA
| | - Margaret M Dunne
- Department of Clinical Research, Westat, Rockville, Maryland, USA
| | - Lindsey Kirshner
- Department of Clinical Research, Westat, Rockville, Maryland, USA
| | - Jessie R Chung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Mark W Tenforde
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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4
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Levy ME, Yang D, Dunne MM, Miley K, Irving SA, Grannis SJ, Weber ZA, Griggs EP, Spark TL, Bassett E, Embi PJ, Gaglani M, Natarajan K, Valvi NR, Ong TC, Naleway AL, Stenehjem E, Klein NP, Link‐Gelles R, DeSilva MB, Kharbanda AB, Raiyani C, Beaton MA, Dixon BE, Rao S, Dascomb K, Patel P, Mamawala M, Han J, Fadel WF, Barron MA, Grisel N, Dickerson M, Liao I, Arndorfer J, Najdowski M, Murthy K, Ray C, Tenforde MW, Ball SW. Risk of COVID-19 Hospitalization and Protection Associated With mRNA Vaccination Among US Adults With Psychiatric Disorders. Influenza Other Respir Viruses 2024; 18:e13269. [PMID: 38494192 PMCID: PMC10944689 DOI: 10.1111/irv.13269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 02/06/2024] [Accepted: 02/07/2024] [Indexed: 03/19/2024] Open
Abstract
BACKGROUND Although psychiatric disorders have been associated with reduced immune responses to other vaccines, it remains unknown whether they influence COVID-19 vaccine effectiveness (VE). This study evaluated risk of COVID-19 hospitalization and estimated mRNA VE stratified by psychiatric disorder status. METHODS In a retrospective cohort analysis of the VISION Network in four US states, the rate of laboratory-confirmed COVID-19-associated hospitalization between December 2021 and August 2022 was compared across psychiatric diagnoses and by monovalent mRNA COVID-19 vaccination status using Cox proportional hazards regression. RESULTS Among 2,436,999 adults, 22.1% had ≥1 psychiatric disorder. The incidence of COVID-19-associated hospitalization was higher among patients with any versus no psychiatric disorder (394 vs. 156 per 100,000 person-years, p < 0.001). Any psychiatric disorder (adjusted hazard ratio [aHR], 1.27; 95% CI, 1.18-1.37) and mood (aHR, 1.25; 95% CI, 1.15-1.36), anxiety (aHR, 1.33, 95% CI, 1.22-1.45), and psychotic (aHR, 1.41; 95% CI, 1.14-1.74) disorders were each significant independent predictors of hospitalization. Among patients with any psychiatric disorder, aHRs for the association between vaccination and hospitalization were 0.35 (95% CI, 0.25-0.49) after a recent second dose, 0.08 (95% CI, 0.06-0.11) after a recent third dose, and 0.33 (95% CI, 0.17-0.66) after a recent fourth dose, compared to unvaccinated patients. Corresponding VE estimates were 65%, 92%, and 67%, respectively, and were similar among patients with no psychiatric disorder (68%, 92%, and 79%). CONCLUSION Psychiatric disorders were associated with increased risk of COVID-19-associated hospitalization. However, mRNA vaccination provided similar protection regardless of psychiatric disorder status, highlighting its benefit for individuals with psychiatric disorders.
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Affiliation(s)
| | | | | | | | | | - Shaun J. Grannis
- Center for Biomedical InformaticsRegenstrief InstituteIndianapolisIndianaUSA
- School of MedicineIndiana UniversityIndianapolisIndianaUSA
| | | | - Eric P. Griggs
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGeorgiaUSA
| | | | | | - Peter J. Embi
- Center for Biomedical InformaticsRegenstrief InstituteIndianapolisIndianaUSA
- Vanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Manjusha Gaglani
- Baylor Scott & White HealthTempleTexasUSA
- Texas A&M University College of MedicineTempleTexasUSA
| | - Karthik Natarajan
- Department of Biomedical InformaticsColumbia University Irving Medical CenterNew YorkNew YorkUSA
- New York Presbyterian HospitalNew YorkNew YorkUSA
| | - Nimish R. Valvi
- Center for Biomedical InformaticsRegenstrief InstituteIndianapolisIndianaUSA
| | - Toan C. Ong
- School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | | | - Edward Stenehjem
- Division of Infectious Diseases and Clinical EpidemiologyIntermountain HealthcareSalt Lake CityUtahUSA
| | - Nicola P. Klein
- Kaiser Permanente Vaccine Study CenterKaiser Permanente Northern California Division of ResearchOaklandCaliforniaUSA
| | - Ruth Link‐Gelles
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGeorgiaUSA
| | | | | | | | - Maura A. Beaton
- Department of Biomedical InformaticsColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Brian E. Dixon
- Center for Biomedical InformaticsRegenstrief InstituteIndianapolisIndianaUSA
- Fairbanks School of Public HealthIndiana UniversityIndianapolisIndianaUSA
| | - Suchitra Rao
- School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical EpidemiologyIntermountain HealthcareSalt Lake CityUtahUSA
| | - Palak Patel
- Influenza Division, National Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGeorgiaUSA
| | | | - Jungmi Han
- Department of Biomedical InformaticsColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - William F. Fadel
- Center for Biomedical InformaticsRegenstrief InstituteIndianapolisIndianaUSA
- Fairbanks School of Public HealthIndiana UniversityIndianapolisIndianaUSA
| | - Michelle A. Barron
- School of MedicineUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical EpidemiologyIntermountain HealthcareSalt Lake CityUtahUSA
| | - Monica Dickerson
- Influenza Division, National Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGeorgiaUSA
| | | | - Julie Arndorfer
- Division of Infectious Diseases and Clinical EpidemiologyIntermountain HealthcareSalt Lake CityUtahUSA
| | - Morgan Najdowski
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGeorgiaUSA
| | | | - Caitlin Ray
- Influenza Division, National Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGeorgiaUSA
| | - Mark W. Tenforde
- Influenza Division, National Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGeorgiaUSA
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5
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DeCuir J, Payne AB, Self WH, Rowley EA, Dascomb K, DeSilva MB, Irving SA, Grannis SJ, Ong TC, Klein NP, Weber ZA, Reese SE, Ball SW, Barron MA, Naleway AL, Dixon BE, Essien I, Bride D, Natarajan K, Fireman B, Shah AB, Okwuazi E, Wiegand R, Zhu Y, Lauring AS, Martin ET, Gaglani M, Peltan ID, Brown SM, Ginde AA, Mohr NM, Gibbs KW, Hager DN, Prekker M, Mohamed A, Srinivasan V, Steingrub JS, Khan A, Busse LW, Duggal A, Wilson JG, Chang SY, Mallow C, Kwon JH, Exline MC, Columbus C, Vaughn IA, Safdar B, Mosier JM, Harris ES, Casey JD, Chappell JD, Grijalva CG, Swan SA, Johnson C, Lewis NM, Ellington S, Adams K, Tenforde MW, Paden CR, Dawood FS, Fleming-Dutra KE, Surie D, Link-Gelles R. Interim Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccines Against COVID-19-Associated Emergency Department and Urgent Care Encounters and Hospitalization Among Immunocompetent Adults Aged ≥18 Years - VISION and IVY Networks, September 2023-January 2024. MMWR Morb Mortal Wkly Rep 2024; 73:180-188. [PMID: 38421945 PMCID: PMC10907041 DOI: 10.15585/mmwr.mm7308a5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
In September 2023, CDC's Advisory Committee on Immunization Practices recommended updated 2023-2024 (monovalent XBB.1.5) COVID-19 vaccination for all persons aged ≥6 months to prevent COVID-19, including severe disease. However, few estimates of updated vaccine effectiveness (VE) against medically attended illness are available. This analysis evaluated VE of an updated COVID-19 vaccine dose against COVID-19-associated emergency department (ED) or urgent care (UC) encounters and hospitalization among immunocompetent adults aged ≥18 years during September 2023-January 2024 using a test-negative, case-control design with data from two CDC VE networks. VE against COVID-19-associated ED/UC encounters was 51% (95% CI = 47%-54%) during the first 7-59 days after an updated dose and 39% (95% CI = 33%-45%) during the 60-119 days after an updated dose. VE estimates against COVID-19-associated hospitalization from two CDC VE networks were 52% (95% CI = 47%-57%) and 43% (95% CI = 27%-56%), with a median interval from updated dose of 42 and 47 days, respectively. Updated COVID-19 vaccine provided increased protection against COVID-19-associated ED/UC encounters and hospitalization among immunocompetent adults. These results support CDC recommendations for updated 2023-2024 COVID-19 vaccination. All persons aged ≥6 months should receive updated 2023-2024 COVID-19 vaccine.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - CDC COVID-19 Vaccine Effectiveness Collaborators
- Coronavirus and Other
Respiratory Viruses Division, National Center for Immunization and Respiratory
Diseases, CDC; Vanderbilt University Medical Center, Nashville,
Tennessee; Westat,
Rockville, Maryland; Division of Infectious Diseases and Clinical Epidemiology,
Intermountain Healthcare, Salt Lake City, Utah; HealthPartners Institute,
Minneapolis, Minnesota; Kaiser Permanente Center for Health Research,
Portland, Oregon; Indiana University School of Medicine, Indianapolis,
Indiana; Regenstrief
Institute Center for Biomedical Informatics, Indianapolis, Indiana; University of Colorado
School of Medicine, Aurora, Colorado; Kaiser Permanente Vaccine Study Center, Kaiser
Permanente Northern California Division of Research, Oakland, California;
Department of
Biomedical Informatics, Columbia University Irving Medical Center, New York, New
York; New
York-Presbyterian Hospital, New York, New York; General Dynamics Information
Technology, Falls Church, Virginia; University of Michigan, Ann Arbor, Michigan;
Baylor Scott
& White Health, Texas; Baylor College of Medicine, Temple, Texas; Intermountain Medical
Center, Murray, Utah; University of Utah, Salt Lake City, Utah; University of Iowa, Iowa
City, Iowa; Wake
Forest School of Medicine, Winston-Salem, North Carolina; Johns Hopkins University School of
Medicine, Baltimore, Maryland; Hennepin County Medical Center, Minneapolis,
Minnesota; Montefiore
Medical Center, Albert Einstein College of Medicine, New York, New York; University of Washington,
Seattle, Washington; Baystate Medical Center, Springfield, Massachusetts;
Oregon Health
& Science University, Portland, Oregon; Emory University, Atlanta, Georgia; Cleveland Clinic,
Cleveland, Ohio; Stanford University School of Medicine, Stanford,
California; Ronald
Reagan UCLA Medical Center, Los Angeles, California; University of Miami, Miami, Florida;
Washington
University in St. Louis, St. Louis, Missouri; The Ohio State University, Columbus,
Ohio; Texas A&M
University College of Medicine, Dallas, Texas; Henry Ford Health, Detroit,
Michigan; Yale
University School of Medicine, New Haven, Connecticut; University of Arizona, Tucson,
Arizona; Influenza
Division, National Center for Immunization and Respiratory Diseases, CDC
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6
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Griggs EP, Mitchell PK, Lazariu V, Gaglani M, McEvoy C, Klein NP, Valvi NR, Irving SA, Kojima N, Stenehjem E, Crane B, Rao S, Grannis SJ, Embi PJ, Kharbanda AB, Ong TC, Natarajan K, Dascomb K, Naleway AL, Bassett E, DeSilva MB, Dickerson M, Konatham D, Fireman B, Allen KS, Barron MA, Beaton M, Arndorfer J, Vazquez-Benitez G, Garg S, Murthy K, Goddard K, Dixon BE, Han J, Grisel N, Raiyani C, Lewis N, Fadel WF, Stockwell MS, Mamawala M, Hansen J, Zerbo O, Patel P, Link-Gelles R, Adams K, Tenforde MW. Clinical Epidemiology and Risk Factors for Critical Outcomes Among Vaccinated and Unvaccinated Adults Hospitalized With COVID-19-VISION Network, 10 States, June 2021-March 2023. Clin Infect Dis 2024; 78:338-348. [PMID: 37633258 DOI: 10.1093/cid/ciad505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/22/2023] [Indexed: 08/28/2023] Open
Abstract
BACKGROUND The epidemiology of coronavirus disease 2019 (COVID-19) continues to develop with emerging variants, expanding population-level immunity, and advances in clinical care. We describe changes in the clinical epidemiology of COVID-19 hospitalizations and risk factors for critical outcomes over time. METHODS We included adults aged ≥18 years from 10 states hospitalized with COVID-19 June 2021-March 2023. We evaluated changes in demographics, clinical characteristics, and critical outcomes (intensive care unit admission and/or death) and evaluated critical outcomes risk factors (risk ratios [RRs]), stratified by COVID-19 vaccination status. RESULTS A total of 60 488 COVID-19-associated hospitalizations were included in the analysis. Among those hospitalized, median age increased from 60 to 75 years, proportion vaccinated increased from 18.2% to 70.1%, and critical outcomes declined from 24.8% to 19.4% (all P < .001) between the Delta (June-December, 2021) and post-BA.4/BA.5 (September 2022-March 2023) periods. Hospitalization events with critical outcomes had a higher proportion of ≥4 categories of medical condition categories assessed (32.8%) compared to all hospitalizations (23.0%). Critical outcome risk factors were similar for unvaccinated and vaccinated populations; presence of ≥4 medical condition categories was most strongly associated with risk of critical outcomes regardless of vaccine status (unvaccinated: adjusted RR, 2.27 [95% confidence interval {CI}, 2.14-2.41]; vaccinated: adjusted RR, 1.73 [95% CI, 1.56-1.92]) across periods. CONCLUSIONS The proportion of adults hospitalized with COVID-19 who experienced critical outcomes decreased with time, and median patient age increased with time. Multimorbidity was most strongly associated with critical outcomes.
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Affiliation(s)
- Eric P Griggs
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Victoria Lazariu
- Department of Clinical Research, Westat, Inc, Rockville, Maryland, USA
| | - Manjusha Gaglani
- Section of Pediatric Infectious Diseases, Department of Pediatrics, Baylor Scott & White Health, Temple, Texas, USA
- Department of Medical Education, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Charlene McEvoy
- Department of Research, HealthPartners Institute, Minneapolis, Minnesota, USA
| | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Nimish R Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
| | - Stephanie A Irving
- Department of Science Programs, Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Noah Kojima
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Bradley Crane
- Department of Science Programs, Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Suchitra Rao
- Department of Biomedical Informatics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
- Department of Family Medicine, School of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Peter J Embi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Anupam B Kharbanda
- Department of Emergency Medicine, Children's Minnesota, Minneapolis, Minnesota, USA
| | - Toan C Ong
- Department of Biomedical Informatics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
- Medical Informatics Services, New York-Presbyterian Hospital, New York, New York, USA
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Allison L Naleway
- Department of Science Programs, Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Elizabeth Bassett
- Department of Clinical Research, Westat, Inc, Rockville, Maryland, USA
| | - Malini B DeSilva
- Department of Research, HealthPartners Institute, Minneapolis, Minnesota, USA
| | - Monica Dickerson
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Deepika Konatham
- Department of Research Analytics and Development, Baylor Scott & White Research Institute, Baylor Scott & White Health, Temple, Texas, USA
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Katie S Allen
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
- Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA
| | - Michelle A Barron
- Department of Biomedical Informatics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Maura Beaton
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | | | - Shikha Garg
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Kempapura Murthy
- Department of Research Analytics and Development, Baylor Scott & White Research Institute, Baylor Scott & White Health, Temple, Texas, USA
| | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Brian E Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
- Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA
| | - Jungmi Han
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Chandni Raiyani
- Department of Research Analytics and Development, Baylor Scott & White Research Institute, Baylor Scott & White Health, Temple, Texas, USA
| | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - William F Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
- Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA
| | - Melissa S Stockwell
- Division of Child & Adolescent Health, Department of Pediatrics, New York-Presbyterian Hospital, New York, New York, USA
- Division of Child and Adolescent Health, Department of Pediatrics, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
- Department of Population and Family Health, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Mufaddal Mamawala
- Department of Research Analytics and Development, Baylor Scott & White Research Institute, Baylor Scott & White Health, Temple, Texas, USA
| | - John Hansen
- Kaiser Permanente Vaccine Study Center, Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Division of Research, Kaiser Permanente Northern California, Oakland, USA
| | - Palak Patel
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Ruth Link-Gelles
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Katherine Adams
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Mark W Tenforde
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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7
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Kanabar K, Vyas P, Natarajan K, Shah N, Dake R. Use of export thrombus aspiration catheter as a dual lumen catheter for antegrade LAD CTO wiring with side branch. J Invasive Cardiol 2024; 36. [PMID: 38335512 DOI: 10.25270/jic/23.00134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2024]
Abstract
A 50-year-old female patient presented with class III angina for 6 months, positive stress test, and a prior CT angiogram suggestive of 3-vessel disease.
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Affiliation(s)
- Kewel Kanabar
- Department of Cardiology, U.N. Mehta Institute of Cardiology and Research Centre, Ahmedabad, India.
| | - Pooja Vyas
- Department of Cardiology, U.N. Mehta Institute of Cardiology and Research Centre, Ahmedabad, India
| | - Karthik Natarajan
- Department of Cardiology, U.N. Mehta Institute of Cardiology and Research Centre, Ahmedabad, India
| | - Nirmal Shah
- Department of Cardiology, U.N. Mehta Institute of Cardiology and Research Centre, Ahmedabad, India
| | - Radhakishan Dake
- Department of Cardiology, U.N. Mehta Institute of Cardiology and Research Centre, Ahmedabad, India
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8
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Zuo X, Zhou Y, Duke J, Hripcsak G, Shah N, Banda JM, Reeves R, Miller T, Waitman LR, Natarajan K, Xu H. Standardizing Multi-site Clinical Note Titles to LOINC Document Ontology: A Transformer-based Approach. AMIA Annu Symp Proc 2024; 2023:834-843. [PMID: 38222429 PMCID: PMC10785935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
The types of clinical notes in electronic health records (EHRs) are diverse and it would be great to standardize them to ensure unified data retrieval, exchange, and integration. The LOINC Document Ontology (DO) is a subset of LOINC that is created specifically for naming and describing clinical documents. Despite the efforts of promoting and improving this ontology, how to efficiently deploy it in real-world clinical settings has yet to be explored. In this study we evaluated the utility of LOINC DO by mapping clinical note titles collected from five institutions to the LOINC DO and classifying the mapping into three classes based on semantic similarity between note titles and LOINC DO codes. Additionally, we developed a standardization pipeline that automatically maps clinical note titles from multiple sites to suitable LOINC DO codes, without accessing the content of clinical notes. The pipeline can be initialized with different large language models, and we compared the performances between them. The results showed that our automated pipeline achieved an accuracy of 0.90. By comparing the manual and automated mapping results, we analyzed the coverage of LOINC DO in describing multi-site clinical note titles and summarized the potential scope for extension.
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Affiliation(s)
- Xu Zuo
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yujia Zhou
- University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jon Duke
- Georgia Institute of Technology, Atlanta, GA, USA
- OHDSI Consortium, Natural Language Processing Working Group
| | - George Hripcsak
- Columbia University, New York City, NY, USA
- OHDSI Consortium, Natural Language Processing Working Group
| | - Nigam Shah
- Stanford University, Stanford, CA, USA
- OHDSI Consortium, Natural Language Processing Working Group
| | - Juan M Banda
- Georgia State University, Atlanta, GA, USA
- OHDSI Consortium, Natural Language Processing Working Group
| | - Ruth Reeves
- Vanderbilt University Medical Center, Nashville, TN, USA
- OHDSI Consortium, Natural Language Processing Working Group
| | - Timothy Miller
- Boston Children's Hospital, Boston, MA, USA
- OHDSI Consortium, Natural Language Processing Working Group
| | | | - Karthik Natarajan
- Columbia University, New York City, NY, USA
- OHDSI Consortium, Natural Language Processing Working Group
| | - Hua Xu
- Yale University, New Haven, CT, USA
- OHDSI Consortium, Natural Language Processing Working Group
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9
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Bear Don't Walk Iv OJ, Pichon A, Nieva HR, Sun T, Altosaar J, Natarajan K, Perotte A, Tarczy-Hornoch P, Demner-Fushman D, Elhadad N. Auditing Learned Associations in Deep Learning Approaches to Extract Race and Ethnicity from Clinical Text. AMIA Annu Symp Proc 2024; 2023:289-298. [PMID: 38222422 PMCID: PMC10785932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
Complete and accurate race and ethnicity (RE) patient information is important for many areas of biomedical informatics research, such as defining and characterizing cohorts, performing quality assessments, and identifying health inequities. Patient-level RE data is often inaccurate or missing in structured sources, but can be supplemented through clinical notes and natural language processing (NLP). While NLP has made many improvements in recent years with large language models, bias remains an often-unaddressed concern, with research showing that harmful and negative language is more often used for certain racial/ethnic groups than others. We present an approach to audit the learned associations of models trained to identify RE information in clinical text by measuring the concordance between model-derived salient features and manually identified RE-related spans of text. We show that while models perform well on the surface, there exist concerning learned associations and potential for future harms from RE-identification models if left unaddressed.
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Affiliation(s)
| | | | - Harry Reyes Nieva
- 2 Columbia University, New York, New York
- Harvard Medical School, Boston, Massachusetts
| | - Tony Sun
- 2 Columbia University, New York, New York
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10
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Tenforde MW, Weber ZA, Yang DH, DeSilva MB, Dascomb K, Irving SA, Naleway AL, Gaglani M, Fireman B, Lewis N, Zerbo O, Goddard K, Timbol J, Hansen JR, Grisel N, Arndorfer J, McEvoy CE, Essien IJ, Rao S, Grannis SJ, Kharbanda AB, Natarajan K, Ong TC, Embi PJ, Ball SW, Dunne MM, Kirshner L, Wiegand RE, Dickerson M, Patel P, Ray C, Flannery B, Garg S, Adams K, Klein NP. Influenza vaccine effectiveness against influenza-A-associated emergency department, urgent care, and hospitalization encounters among U.S. adults, 2022-2023. J Infect Dis 2023:jiad542. [PMID: 38041853 DOI: 10.1093/infdis/jiad542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 11/08/2023] [Accepted: 11/27/2023] [Indexed: 12/04/2023] Open
Abstract
BACKGROUND The 2022-2023 United States influenza season had unusually early influenza activity with high hospitalization rates. Vaccine-matched A(H3N2) viruses predominated, with lower levels of A(H1N1)pdm09 activity also observed. METHODS Using the test-negative design, we evaluated influenza vaccine effectiveness (VE) during the 2022-2023 season against influenza-A-associated emergency department/urgent care (ED/UC) visits and hospitalizations from October 2022-March 2023 among adults (age ≥18 years) with acute respiratory illness (ARI). VE was estimated by comparing odds of seasonal influenza vaccination among case-patients (influenza A test-positive by molecular assay) and controls (influenza test-negative), applying inverse-propensity-to-be-vaccinated weights. RESULTS The analysis included 85,389 ED/UC ARI encounters (17.0% influenza-A-positive; 37.8% vaccinated overall) and 19,751 hospitalizations (9.5% influenza-A-positive; 52.8% vaccinated overall). VE against influenza-A-associated ED/UC encounters was 44% (95% confidence interval [95%CI]: 40-47%) overall and 45% and 41% among adults aged 18-64 and ≥65 years, respectively. VE against influenza-A-associated hospitalizations was 35% (95%CI: 27-43%) overall and 23% and 41% among adults aged 18-64 and ≥65 years, respectively. CONCLUSIONS VE was moderate during the 2022-2023 influenza season, a season characterized with increased burden of influenza and co-circulation with other respiratory viruses. Vaccination is likely to substantially reduce morbidity, mortality, and strain on healthcare resources.
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Affiliation(s)
- Mark W Tenforde
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
| | | | | | | | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, United States
| | - Stephanie A Irving
- Kaiser Permanente Center for Health Research, Portland, Oregon, United States
| | - Allison L Naleway
- Kaiser Permanente Center for Health Research, Portland, Oregon, United States
| | - Manjusha Gaglani
- Department of Pediatrics, Section of Pediatric Infectious Diseases, Baylor Scott & White Health and Baylor College of Medicine, Temple, Texas, United States
- Department of Medical Education, Texas A&M University College of Medicine, Temple, Texas, United States
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, United States
| | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, United States
| | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, United States
| | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, United States
| | - Julius Timbol
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, United States
| | - John R Hansen
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, United States
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, United States
| | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, United States
| | | | - Inih J Essien
- HealthPartners Institute, Minneapolis, Minnesota, United States
| | - Suchitra Rao
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, United States
- School of Medicine, Indiana University, Indianapolis, Indiana, United States
| | | | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, United States
- New York Presbyterian Hospital, New York, New York, United States
| | - Toan C Ong
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Peter J Embi
- Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | | | | | | | - Ryan E Wiegand
- Coronavirus and other Respiratory Viruses Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
| | - Monica Dickerson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
| | - Palak Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
| | - Caitlin Ray
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
| | - Shikha Garg
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
| | - Katherine Adams
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States
| | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, United States
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11
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Master H, Annis J, Huang S, Beckman JA, Ratsimbazafy F, Marginean K, Carroll R, Natarajan K, Harrell FE, Roden DM, Harris P, Brittain EL. Author Correction: Association of step counts over time with the risk of chronic disease in the All of Us Research Program. Nat Med 2023; 29:3270. [PMID: 37046000 PMCID: PMC10719085 DOI: 10.1038/s41591-023-02313-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/14/2023]
Affiliation(s)
- Hiral Master
- Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeffrey Annis
- Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shi Huang
- Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Joshua A Beckman
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Francis Ratsimbazafy
- Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kayla Marginean
- Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Robert Carroll
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Karthik Natarajan
- Department Biomedical Informatics, Columbia University, New York, NY, USA
| | - Frank E Harrell
- Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Dan M Roden
- Department of Medicine and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paul Harris
- Department of Biomedical Informatics, Biomedical Engineering and Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Evan L Brittain
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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12
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Patel P, Schrader KE, Rice CE, Rowley E, Cree RA, DeSilva MB, Embi PJ, Gaglani M, Grannis SJ, Ong TC, Stenehjem E, Naleway AL, Ball S, Natarajan K, Klein NP, Adams K, Kharbanda A, Ray C, Link-Gelles R, Tenforde MW. Effectiveness of the Original Monovalent Coronavirus Disease 2019 Vaccines in Preventing Emergency Department or Urgent Care Encounters and Hospitalizations Among Adults With Disabilities: VISION Network, June 2021-September 2022. Open Forum Infect Dis 2023; 10:ofad474. [PMID: 37965644 PMCID: PMC10642729 DOI: 10.1093/ofid/ofad474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 09/18/2023] [Indexed: 11/16/2023] Open
Abstract
Adults with disabilities are at increased risk for severe coronavirus disease 2019 (COVID-19). Using data across 9 states during Delta- and Omicron-predominant periods (June 2021-September 2022), we evaluated the effectiveness of the original monovalent COVID-19 messenger RNA vaccines among 521 206 emergency department/urgent care encounters (11 471 [2%] in patients with a documented disability) and 139 548 hospitalizations (16 569 [12%] in patients with a disability) for laboratory-confirmed COVID-19 illness in adults (aged ≥18 years). Across variant periods and for the primary series or booster doses, vaccine effectiveness was similar in those with and those without a disability. These findings highlight the importance of adults with disabilities staying up to date with COVID-19 vaccinations.
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Affiliation(s)
- Palak Patel
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Catherine E Rice
- Division of Human Development and Disability, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Elizabeth Rowley
- Department of Clinical Research, Westat, Rockville, Maryland, USA
| | - Robyn A Cree
- Division of Human Development and Disability, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Malini B DeSilva
- Department of Research, Health Partners Institute, Minneapolis, Minnesota, USA
| | - Peter J Embi
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Manjusha Gaglani
- Section of Pediatric Infectious Diseases, Department of Pediatrics, Baylor Scott & White Health, Temple, Texas, USA
- Department of Medical Education, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
- School of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Toan C Ong
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Allison L Naleway
- Department of Science Programs, Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Sarah Ball
- Department of Clinical Research, Westat, Rockville, Maryland, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, NewYork, New York, USA
- Medical Informatics Services, NewYork-Presbyterian Hospital, NewYork, New York, USA
| | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Katherine Adams
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Anupam Kharbanda
- Department of Emergency Medicine, Children’s Minnesota, Minneapolis, Minnesota, USA
| | - Caitlin Ray
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Ruth Link-Gelles
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Mark W Tenforde
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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13
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Sun TY, Hardin J, Nieva HR, Natarajan K, Cheng RF, Ryan P, Elhadad N. Large-scale characterization of gender differences in diagnosis prevalence and time to diagnosis. medRxiv 2023:2023.10.12.23296976. [PMID: 37873224 PMCID: PMC10592987 DOI: 10.1101/2023.10.12.23296976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
We carry out an analysis of gender differences in patterns of disease diagnosis across four large observational health datasets and find that women are routinely older when first assigned most diagnoses. Among 112 acute and chronic diseases, women experience longer lengths of time between symptom onset and disease diagnosis than men for most diseases regardless of metric used, even when only symptoms common to both genders are considered. These findings are consistent for patients with private as well as government insurance. Our analysis highlights systematic gender differences in patterns of disease diagnosis and suggests that symptoms of disease are measured or weighed differently for women and men. Data and code leverage the open-source common data model and analytic code and results are publicly available.
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Affiliation(s)
- Tony Yue Sun
- Department of Biomedical Informatics, Columbia University; New York City, USA
| | - Jill Hardin
- Janssen Research and Development; Titusville, USA
| | - Harry Reyes Nieva
- Department of Biomedical Informatics, Columbia University; New York City, USA
- Department of Medicine, Harvard Medical School; Boston, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University; New York City, USA
| | - Ru-fong Cheng
- Gender Equality Division, Bill and Melinda Gates Foundation; Seattle, USA
| | - Patrick Ryan
- Janssen Research and Development; Titusville, USA
| | - Noémie Elhadad
- Department of Biomedical Informatics, Columbia University; New York City, USA
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14
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Sharma M, Natarajan K, Kumar AM, Paramasivan P. Celiac artery thrombosis presenting as acute abdomen. J Postgrad Med 2023; 69:234-236. [PMID: 37530377 PMCID: PMC10846811 DOI: 10.4103/jpgm.jpgm_331_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/05/2023] [Accepted: 06/14/2023] [Indexed: 08/03/2023] Open
Abstract
Mesenteric vascular thrombosis, typically of the superior mesenteric artery, is a frequent occurrence in patients with hypercoagulable conditions. Isolated involvement of the celiac artery is rare. Patients with celiac artery thrombosis can present with an acute abdomen or occasionally with acid peptic symptoms. A delay in diagnosis is associated with high rates of morbidity and mortality. We present a rare case of splenic infarction with celiac trunk thrombosis in a 54-year-old patient with underlying antiphospholipid (APLA) syndrome who presented with epigastric pain that was mistaken for symptoms of acid reflux.
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Affiliation(s)
- M Sharma
- Department of Gastroenterology, Apollo Hospitals, Greams Road, Chennai, Tamil Nadu, India
| | - K Natarajan
- Department of Gastroenterology, Apollo Hospitals, Greams Road, Chennai, Tamil Nadu, India
| | - A Mahesh Kumar
- Department of Medical Services, Apollo Hospitals, Greams Road, Chennai, Tamil Nadu, India
| | - P Paramasivan
- Department of Gastroenterology, Apollo Hospitals, Greams Road, Chennai, Tamil Nadu, India
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15
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Embi PJ, Levy ME, Patel P, DeSilva MB, Gaglani M, Dascomb K, Dunne MM, Klein NP, Ong TC, Grannis SJ, Natarajan K, Yang DH, Stenehjem E, Zerbo O, McEvoy C, Rao S, Thompson MG, Konatham D, Irving SA, Dixon BE, Han J, Schrader KE, Grisel N, Lewis N, Kharbanda AB, Barron MA, Reynolds S, Liao IC, Fadel WF, Rowley EA, Arndorfer J, Goddard K, Murthy K, Valvi NR, Weber ZA, Fireman B, Reese SE, Ball SW, Naleway AL. Effectiveness of COVID-19 vaccines at preventing emergency department or urgent care encounters and hospitalizations among immunocompromised adults: An observational study of real-world data across 10 US states from August-December 2021. Vaccine 2023; 41:5424-5434. [PMID: 37479609 PMCID: PMC10201325 DOI: 10.1016/j.vaccine.2023.05.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/06/2023] [Accepted: 05/16/2023] [Indexed: 07/23/2023]
Abstract
BACKGROUND Immunocompromised (IC) persons are at increased risk for severe COVID-19 outcomes and are less protected by 1-2 COVID-19 vaccine doses than are immunocompetent (non-IC) persons. We compared vaccine effectiveness (VE) against medically attended COVID-19 of 2-3 mRNA and 1-2 viral-vector vaccine doses between IC and non-IC adults. METHODS Using a test-negative design among eight VISION Network sites, VE against laboratory-confirmed COVID-19-associated emergency department (ED) or urgent care (UC) events and hospitalizations from 26 August-25 December 2021 was estimated separately among IC and non-IC adults and among specific IC condition subgroups. Vaccination status was defined using number and timing of doses. VE for each status (versus unvaccinated) was adjusted for age, geography, time, prior positive test result, and local SARS-CoV-2 circulation. RESULTS We analyzed 8,848 ED/UC events and 18,843 hospitalizations among IC patients and 200,071 ED/UC events and 70,882 hospitalizations among non-IC patients. Among IC patients, 3-dose mRNA VE against ED/UC (73% [95% CI: 64-80]) and hospitalization (81% [95% CI: 76-86]) was lower than that among non-IC patients (ED/UC: 94% [95% CI: 93-94]; hospitalization: 96% [95% CI: 95-97]). Similar patterns were observed for viral-vector vaccines. Transplant recipients had lower VE than other IC subgroups. CONCLUSIONS During B.1.617.2 (Delta) variant predominance, IC adults received moderate protection against COVID-19-associated medical events from three mRNA doses, or one viral-vector dose plus a second dose of any product. However, protection was lower in IC versus non-IC patients, especially among transplant recipients, underscoring the need for additional protection among IC adults.
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Affiliation(s)
- Peter J Embi
- Vanderbilt University Medical Center, Nashville, TN, USA; Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA.
| | | | - Palak Patel
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | | | - Manjusha Gaglani
- Baylor Scott & White Health, Texas A&M College of Medicine, Temple, TX, USA; Texas A&M University College of Medicine, Temple, Texas, USA
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | | | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Toan C Ong
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA; Indiana University School of Medicine, Indianapolis, IN, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA; New York Presbyterian Hospital, New York, NY, USA
| | | | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | | | - Suchitra Rao
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Mark G Thompson
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | - Deepika Konatham
- Baylor Scott & White Health, Texas A&M College of Medicine, Temple, TX, USA
| | - Stephanie A Irving
- Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA
| | - Brian E Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA; Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | - Jungmi Han
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | | | - Michelle A Barron
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Sue Reynolds
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | - I-Chia Liao
- Baylor Scott & White Health, Texas A&M College of Medicine, Temple, TX, USA
| | - William F Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA; Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | | | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Kempapura Murthy
- Baylor Scott & White Health, Texas A&M College of Medicine, Temple, TX, USA
| | - Nimish R Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
| | | | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | | | | | - Allison L Naleway
- Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA
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16
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Link-Gelles R, Ciesla AA, Rowley EA, Klein NP, Naleway AL, Payne AB, Kharbanda A, Natarajan K, DeSilva MB, Dascomb K, Irving SA, Zerbo O, Reese SE, Wiegand RE, Najdowski M, Ong TC, Rao S, Stockwell MS, Stephens A, Goddard K, Martinez YC, Weber ZA, Fireman B, Hansen J, Timbol J, Grannis SJ, Barron MA, Embi PJ, Ball SW, Gaglani M, Grisel N, Arndorfer J, Tenforde MW, Fleming-Dutra KE. Effectiveness of Monovalent and Bivalent mRNA Vaccines in Preventing COVID-19-Associated Emergency Department and Urgent Care Encounters Among Children Aged 6 Months-5 Years - VISION Network, United States, July 2022-June 2023. MMWR Morb Mortal Wkly Rep 2023; 72:886-892. [PMID: 37590187 PMCID: PMC10441825 DOI: 10.15585/mmwr.mm7233a2] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
On June 19, 2022, the original monovalent mRNA COVID-19 vaccines were approved as a primary series for children aged 6 months-4 years (Pfizer-BioNTech) and 6 months-5 years (Moderna) based on safety, immunobridging, and limited efficacy data from clinical trials. On December 9, 2022, CDC expanded recommendations for use of updated bivalent vaccines to children aged ≥6 months. mRNA COVID-19 vaccine effectiveness (VE) against emergency department or urgent care (ED/UC) encounters was evaluated within the VISION Network during July 4, 2022-June 17, 2023, among children with COVID-19-like illness aged 6 months-5 years. Among children aged 6 months-5 years who received molecular SARS-CoV-2 testing during August 1, 2022-June 17, 2023, VE of 2 monovalent Moderna doses against ED/UC encounters was 29% (95% CI = 12%-42%) ≥14 days after dose 2 (median = 100 days after dose 2; IQR = 63-155 days). Among children aged 6 months-4 years with a COVID-19-like illness who received molecular testing during September 19, 2022-June 17, 2023, VE of 3 monovalent Pfizer-BioNTech doses was 43% (95% CI = 17%-61%) ≥14 days after dose 3 (median = 75 days after dose 3; IQR = 40-139 days). Effectiveness of ≥1 bivalent dose, comparing children with at least a complete primary series and ≥1 bivalent dose to unvaccinated children, irrespective of vaccine manufacturer, was 80% (95% CI = 42%-96%) among children aged 6 months-5 years a median of 58 days (IQR = 32-83 days) after the dose. All children should stay up to date with recommended COVID-19 vaccines, including initiation of COVID-19 vaccination immediately when they are eligible.
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17
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Mayo KR, Basford MA, Carroll RJ, Dillon M, Fullen H, Leung J, Master H, Rura S, Sulieman L, Kennedy N, Banks E, Bernick D, Gauchan A, Lichtenstein L, Mapes BM, Marginean K, Nyemba SL, Ramirez A, Rotundo C, Wolfe K, Xia W, Azuine RE, Cronin RM, Denny JC, Kho A, Lunt C, Malin B, Natarajan K, Wilkins CH, Xu H, Hripcsak G, Roden DM, Philippakis AA, Glazer D, Harris PA. The All of Us Data and Research Center: Creating a Secure, Scalable, and Sustainable Ecosystem for Biomedical Research. Annu Rev Biomed Data Sci 2023; 6:443-464. [PMID: 37561600 DOI: 10.1146/annurev-biodatasci-122120-104825] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
The All of Us Research Program's Data and Research Center (DRC) was established to help acquire, curate, and provide access to one of the world's largest and most diverse datasets for precision medicine research. Already, over 500,000 participants are enrolled in All of Us, 80% of whom are underrepresented in biomedical research, and data are being analyzed by a community of over 2,300 researchers. The DRC created this thriving data ecosystem by collaborating with engaged participants, innovative program partners, and empowered researchers. In this review, we first describe how the DRC is organized to meet the needs of this broad group of stakeholders. We then outline guiding principles, common challenges, and innovative approaches used to build the All of Us data ecosystem. Finally, we share lessons learned to help others navigate important decisions and trade-offs in building a modern biomedical data platform.
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Affiliation(s)
- Kelsey R Mayo
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Melissa A Basford
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Robert J Carroll
- Deparment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
| | - Moira Dillon
- Verily Life Sciences, South San Francisco, California, USA
| | - Heather Fullen
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jesse Leung
- Verily Life Sciences, South San Francisco, California, USA
| | - Hiral Master
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Shimon Rura
- Verily Life Sciences, South San Francisco, California, USA
| | - Lina Sulieman
- Deparment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
| | - Nan Kennedy
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Eric Banks
- Data Sciences Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - David Bernick
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Asmita Gauchan
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Lee Lichtenstein
- Data Sciences Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Brandy M Mapes
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kayla Marginean
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Steve L Nyemba
- Deparment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
| | - Andrea Ramirez
- The All of Us Research Program, National Institutes of Health, Bethesda, Maryland, USA
| | - Charissa Rotundo
- Vanderbilt University Medical Center Enterprise Cybersecurity, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Keri Wolfe
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Weiyi Xia
- Deparment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
| | - Romuladus E Azuine
- The All of Us Research Program, National Institutes of Health, Bethesda, Maryland, USA
| | - Robert M Cronin
- Department of Internal Medicine, The Ohio State University, Columbus, Ohio, USA
| | - Joshua C Denny
- The All of Us Research Program, National Institutes of Health, Bethesda, Maryland, USA
| | - Abel Kho
- Department of Medicine and Institute for Augmented Intelligence in Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Christopher Lunt
- The All of Us Research Program, National Institutes of Health, Bethesda, Maryland, USA
| | - Bradley Malin
- Deparment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Consuelo H Wilkins
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Hua Xu
- Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, Connecticut, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Dan M Roden
- Deparment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | | | - David Glazer
- Verily Life Sciences, South San Francisco, California, USA
| | - Paul A Harris
- Deparment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
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18
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Tenforde MW, Weber ZA, DeSilva MB, Stenehjem E, Yang DH, Fireman B, Gaglani M, Kojima N, Irving SA, Rao S, Grannis SJ, Naleway AL, Kirshner L, Kharbanda AB, Dascomb K, Lewis N, Dalton AF, Ball SW, Natarajan K, Ong TC, Hartmann E, Embi PJ, McEvoy CE, Grisel N, Zerbo O, Dunne MM, Arndorfer J, Goddard K, Dickerson M, Patel P, Timbol J, Griggs EP, Hansen J, Thompson MG, Flannery B, Klein NP. Vaccine Effectiveness Against Influenza-Associated Urgent Care, Emergency Department, and Hospital Encounters During the 2021-2022 Season, VISION Network. J Infect Dis 2023; 228:185-195. [PMID: 36683410 DOI: 10.1093/infdis/jiad015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/12/2023] [Accepted: 01/19/2023] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND Following historically low influenza activity during the 2020-2021 season, the United States saw an increase in influenza circulating during the 2021-2022 season. Most viruses belonged to the influenza A(H3N2) 3C.2a1b 2a.2 subclade. METHODS We conducted a test-negative case-control analysis among adults ≥18 years of age at 3 sites within the VISION Network. Encounters included emergency department/urgent care (ED/UC) visits or hospitalizations with ≥1 acute respiratory illness (ARI) discharge diagnosis codes and molecular testing for influenza. Vaccine effectiveness (VE) was calculated by comparing the odds of influenza vaccination ≥14 days before the encounter date between influenza-positive cases (type A) and influenza-negative and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-negative controls, applying inverse probability-to-be-vaccinated weights, and adjusting for confounders. RESULTS In total, 86 732 ED/UC ARI-associated encounters (7696 [9%] cases) and 16 805 hospitalized ARI-associated encounters (649 [4%] cases) were included. VE against influenza-associated ED/UC encounters was 25% (95% confidence interval (CI), 20%-29%) and 25% (95% CI, 11%-37%) against influenza-associated hospitalizations. VE against ED/UC encounters was lower in adults ≥65 years of age (7%; 95% CI, -5% to 17%) or with immunocompromising conditions (4%; 95% CI, -45% to 36%). CONCLUSIONS During an influenza A(H3N2)-predominant influenza season, modest VE was observed. These findings highlight the need for improved vaccines, particularly for A(H3N2) viruses that are historically associated with lower VE.
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Affiliation(s)
- Mark W Tenforde
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | | | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | | | - Bruce Fireman
- Kaiser Permanente Northern California Division of Research, Kaiser Permanente Vaccine Study Center, Oakland, California, USA
| | - Manjusha Gaglani
- Department of Pediatrics, Section of Pediatric Infectious Diseases, Baylor Scott and White Health, Temple, Texas, USA
- Department of Medical Education, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Noah Kojima
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Suchitra Rao
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
- School of Medicine, Indiana University, Indianapolis, Indiana, USA
| | | | | | | | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Ned Lewis
- Kaiser Permanente Northern California Division of Research, Kaiser Permanente Vaccine Study Center, Oakland, California, USA
| | - Alexandra F Dalton
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
- New York Presbyterian Hospital, New York, New York, USA
| | - Toan C Ong
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Emily Hartmann
- Paso del Norte Health Information Exchange, El Paso, Texas, USA
| | - Peter J Embi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | | | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Ousseny Zerbo
- Kaiser Permanente Northern California Division of Research, Kaiser Permanente Vaccine Study Center, Oakland, California, USA
| | | | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Kristin Goddard
- Kaiser Permanente Northern California Division of Research, Kaiser Permanente Vaccine Study Center, Oakland, California, USA
| | - Monica Dickerson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Palak Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Julius Timbol
- Kaiser Permanente Northern California Division of Research, Kaiser Permanente Vaccine Study Center, Oakland, California, USA
| | - Eric P Griggs
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - John Hansen
- Kaiser Permanente Northern California Division of Research, Kaiser Permanente Vaccine Study Center, Oakland, California, USA
| | - Mark G Thompson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Nicola P Klein
- Kaiser Permanente Northern California Division of Research, Kaiser Permanente Vaccine Study Center, Oakland, California, USA
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19
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Spotnitz M, Acharya N, Cimino JJ, Murphy S, Namjou B, Crimmins N, Walunas T, Liu C, Crosslin D, Benoit B, Rosenthal E, Pacheco JA, Ostropolets A, Reyes Nieva H, Patterson JS, Richter LR, Callahan TJ, Elhussein A, Pang C, Kiryluk K, Nestor J, Khan A, Mohan S, Minty E, Chung W, Wei WQ, Natarajan K, Weng C. A metadata framework for computational phenotypes. JAMIA Open 2023; 6:ooad032. [PMID: 37181728 PMCID: PMC10168627 DOI: 10.1093/jamiaopen/ooad032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/10/2023] [Accepted: 04/21/2023] [Indexed: 05/16/2023] Open
Abstract
With the burgeoning development of computational phenotypes, it is increasingly difficult to identify the right phenotype for the right tasks. This study uses a mixed-methods approach to develop and evaluate a novel metadata framework for retrieval of and reusing computational phenotypes. Twenty active phenotyping researchers from 2 large research networks, Electronic Medical Records and Genomics and Observational Health Data Sciences and Informatics, were recruited to suggest metadata elements. Once consensus was reached on 39 metadata elements, 47 new researchers were surveyed to evaluate the utility of the metadata framework. The survey consisted of 5-Likert multiple-choice questions and open-ended questions. Two more researchers were asked to use the metadata framework to annotate 8 type-2 diabetes mellitus phenotypes. More than 90% of the survey respondents rated metadata elements regarding phenotype definition and validation methods and metrics positively with a score of 4 or 5. Both researchers completed annotation of each phenotype within 60 min. Our thematic analysis of the narrative feedback indicates that the metadata framework was effective in capturing rich and explicit descriptions and enabling the search for phenotypes, compliance with data standards, and comprehensive validation metrics. Current limitations were its complexity for data collection and the entailed human costs.
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Affiliation(s)
- Matthew Spotnitz
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Nripendra Acharya
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - James J Cimino
- Informatics Institute, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Shawn Murphy
- Laboratory of Computer Science, Mass General Brigham, Boston, Massachusetts, USA
- Department of Neurology, Mass General Brigham, Boston, Massachusetts, USA
| | - Bahram Namjou
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA
| | - Nancy Crimmins
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA
| | - Theresa Walunas
- Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Cong Liu
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - David Crosslin
- Division of Biomedical Informatics and Genomics, Tulane University School of Medicine, New Orleans, Louisiana, USA
| | - Barbara Benoit
- Department of Research Information Science & Computing, Mass General Brigham, Boston, Massachusetts, USA
| | | | - Jennifer A Pacheco
- Center for Genetic Medicine, Northwestern University, Chicago, Illinois, USA
| | - Anna Ostropolets
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Harry Reyes Nieva
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Jason S Patterson
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Lauren R Richter
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Tiffany J Callahan
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Ahmed Elhussein
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Chao Pang
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Jordan Nestor
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Sumit Mohan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Evan Minty
- Department of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Wendy Chung
- Department of Pediatrics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, New York, USA
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20
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Adams K, Riddles JJ, Rowley EAK, Grannis SJ, Gaglani M, Fireman B, Hartmann E, Naleway AL, Stenehjem E, Hughes A, Dalton AF, Natarajan K, Dascomb K, Raiyani C, Irving SA, Sloan-Aagard C, Kharbanda AB, DeSilva MB, Dixon BE, Ong TC, Keller J, Dickerson M, Grisel N, Murthy K, Nanez J, Fadel WF, Ball SW, Patel P, Arndorfer J, Mamawala M, Valvi NR, Dunne MM, Griggs EP, Embi PJ, Thompson MG, Link-Gelles R, Tenforde MW. Number needed to vaccinate with a COVID-19 booster to prevent a COVID-19-associated hospitalization during SARS-CoV-2 Omicron BA.1 variant predominance, December 2021-February 2022, VISION Network: a retrospective cohort study. Lancet Reg Health Am 2023; 23:100530. [PMID: 37333688 PMCID: PMC10266334 DOI: 10.1016/j.lana.2023.100530] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 05/17/2023] [Accepted: 05/24/2023] [Indexed: 06/20/2023]
Abstract
Background Understanding the usefulness of additional COVID-19 vaccine doses-particularly given varying disease incidence-is needed to support public health policy. We characterize the benefits of COVID-19 booster doses using number needed to vaccinate (NNV) to prevent one COVID-19-associated hospitalization or emergency department encounter. Methods We conducted a retrospective cohort study of immunocompetent adults at five health systems in four U.S. states during SARS-CoV-2 Omicron BA.1 predominance (December 2021-February 2022). Included patients completed a primary mRNA COVID-19 vaccine series and were either eligible to or received a booster dose. NNV were estimated using hazard ratios for each outcome (hospitalization and emergency department encounters), with results stratified by three 25-day periods and site. Findings 1,285,032 patients contributed 938 hospitalizations and 2076 emergency department encounters. 555,729 (43.2%) patients were aged 18-49 years, 363,299 (28.3%) 50-64 years, and 366,004 (28.5%) ≥65 years. Most patients were female (n = 765,728, 59.6%), White (n = 990,224, 77.1%), and non-Hispanic (n = 1,063,964, 82.8%). 37.2% of patients received a booster and 62.8% received only two doses. Median estimated NNV to prevent one hospitalization was 205 (range 44-615) and NNV was lower across study periods for adults aged ≥65 years (110, 46, and 88, respectively) and those with underlying medical conditions (163, 69, and 131, respectively). Median estimated NNV to prevent one emergency department encounter was 156 (range 75-592). Interpretation The number of patients needed to receive a booster dose was highly dependent on local disease incidence, outcome severity, and patient risk factors for moderate-to-severe disease. Funding Funding was provided by the Centers for Disease Control and Prevention though contract 75D30120C07986 to Westat, Inc. and contract 75D30120C07765 to Kaiser Foundation Hospitals.
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Affiliation(s)
- Katherine Adams
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
- School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Manjusha Gaglani
- Baylor Scott & White Health, Temple, TX, USA
- Texas A&M University College of Medicine, Temple, TX, USA
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Emily Hartmann
- Paso del Norte Health Information Exchange (PHIX), El Paso, TX, USA
| | | | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | | | - Alexandra F Dalton
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
- NewYork-Presbyterian Hospital, New York, NY, USA
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | | | | | - Chantel Sloan-Aagard
- Paso del Norte Health Information Exchange (PHIX), El Paso, TX, USA
- Brigham Young University Department of Public Health, Provo, UT, USA
| | | | | | - Brian E Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
- Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | - Toan C Ong
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Monica Dickerson
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | | | - Juan Nanez
- Paso del Norte Health Information Exchange (PHIX), El Paso, TX, USA
| | - William F Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
- Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | | | - Palak Patel
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | | | - Nimish R Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
| | | | - Eric P Griggs
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Peter J Embi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
- Vanderbilt University Medical Center, Nashville, TN, USA
| | - Mark G Thompson
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ruth Link-Gelles
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Mark W Tenforde
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
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21
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Link-Gelles R, Weber ZA, Reese SE, Payne AB, Gaglani M, Adams K, Kharbanda AB, Natarajan K, DeSilva MB, Dascomb K, Irving SA, Klein NP, Grannis SJ, Ong TC, Embi PJ, Dunne MM, Dickerson M, McEvoy C, Arndorfer J, Naleway AL, Goddard K, Dixon BE, Griggs EP, Hansen J, Valvi N, Najdowski M, Timbol J, Rogerson C, Fireman B, Fadel WF, Patel P, Ray CS, Wiegand R, Ball S, Tenforde MW. Estimates of Bivalent mRNA Vaccine Durability in Preventing COVID-19-Associated Hospitalization and Critical Illness Among Adults with and Without Immunocompromising Conditions - VISION Network, September 2022-April 2023. Am J Transplant 2023; 23:1062-1076. [PMID: 37394267 DOI: 10.1016/j.ajt.2023.06.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Affiliation(s)
- Ruth Link-Gelles
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, CDC.
| | | | | | - Amanda B Payne
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, CDC
| | - Manjusha Gaglani
- Section of Pediatric Infectious Diseases, Department of Pediatrics, Baylor Scott & White Health, Temple, Texas; Department of Medical Education, Texas A&M University College of Medicine, Temple, Texas
| | - Katherine Adams
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC
| | | | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York; NewYork-Presbyterian Hospital, New York, New York
| | | | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | | | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana; School of Medicine, Indiana University, Indianapolis, Indiana
| | - Toan C Ong
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Peter J Embi
- Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Monica Dickerson
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC
| | | | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | | | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | - Brian E Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana; Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana
| | - Eric P Griggs
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, CDC
| | - John Hansen
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | - Nimish Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
| | - Morgan Najdowski
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, CDC
| | - Julius Timbol
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | - Colin Rogerson
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | - William F Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana; Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana
| | - Palak Patel
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC
| | - Caitlin S Ray
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC
| | - Ryan Wiegand
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, CDC
| | | | - Mark W Tenforde
- Influenza Division, National Center for Immunization and Respiratory Diseases, CDC
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22
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Keloth VK, Banda JM, Gurley M, Heider PM, Kennedy G, Liu H, Liu F, Miller T, Natarajan K, V Patterson O, Peng Y, Raja K, Reeves RM, Rouhizadeh M, Shi J, Wang X, Wang Y, Wei WQ, Williams AE, Zhang R, Belenkaya R, Reich C, Blacketer C, Ryan P, Hripcsak G, Elhadad N, Xu H. Representing and utilizing clinical textual data for real world studies: An OHDSI approach. J Biomed Inform 2023; 142:104343. [PMID: 36935011 PMCID: PMC10428170 DOI: 10.1016/j.jbi.2023.104343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 01/21/2023] [Accepted: 03/13/2023] [Indexed: 03/19/2023]
Abstract
Clinical documentation in electronic health records contains crucial narratives and details about patients and their care. Natural language processing (NLP) can unlock the information conveyed in clinical notes and reports, and thus plays a critical role in real-world studies. The NLP Working Group at the Observational Health Data Sciences and Informatics (OHDSI) consortium was established to develop methods and tools to promote the use of textual data and NLP in real-world observational studies. In this paper, we describe a framework for representing and utilizing textual data in real-world evidence generation, including representations of information from clinical text in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), the workflow and tools that were developed to extract, transform and load (ETL) data from clinical notes into tables in OMOP CDM, as well as current applications and specific use cases of the proposed OHDSI NLP solution at large consortia and individual institutions with English textual data. Challenges faced and lessons learned during the process are also discussed to provide valuable insights for researchers who are planning to implement NLP solutions in real-world studies.
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Affiliation(s)
- Vipina K Keloth
- Section of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Juan M Banda
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Michael Gurley
- Lurie Cancer Center, Northwestern University, Chicago, Illinois, USA
| | - Paul M Heider
- Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC, USA
| | - Georgina Kennedy
- Ingham Institute for Applied Medical Research, Sydney, Australia
| | - Hongfang Liu
- Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Feifan Liu
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Timothy Miller
- Computational Health Informatics Program, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Olga V Patterson
- VA Informatics and Computing Infrastructure, Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah, USA; Division of Epidemiology, Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah, USA; Verily Life Sciences, Mountain View, CA, USA
| | - Yifan Peng
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Kalpana Raja
- Section of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Ruth M Reeves
- TN Valley Healthcare System, U.S. Department of Veterans Affairs, Nashville, TN, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Masoud Rouhizadeh
- Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL, USA; Biomedical Informatics and Data Science, Johns Hopkins University, Baltimore, MD, USA
| | - Jianlin Shi
- VA Informatics and Computing Infrastructure, Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah, USA; Division of Epidemiology, Department of Internal Medicine, School of Medicine, University of Utah, Salt Lake City, Utah, USA; Department of Biomedical Informatics, University of Utah, Salt Lake City, USA
| | - Xiaoyan Wang
- Sema4 Mount Sinai Genomics Incorporation, Stamford, CT, USA
| | - Yanshan Wang
- Department of Health Information Management, Department of Biomedical Informatics, and Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Rui Zhang
- Institute for Health Informatics, and Department of Pharmaceutical Care & Health Systems, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Clair Blacketer
- Janssen Pharmaceutical Research and Development LLC, Titusville, NJ, USA; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Patrick Ryan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA; Janssen Pharmaceutical Research and Development LLC, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Noémie Elhadad
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA.
| | - Hua Xu
- Section of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA.
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23
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Link-Gelles R, Weber ZA, Reese SE, Payne AB, Gaglani M, Adams K, Kharbanda AB, Natarajan K, DeSilva MB, Dascomb K, Irving SA, Klein NP, Grannis SJ, Ong TC, Embi PJ, Dunne MM, Dickerson M, McEvoy C, Arndorfer J, Naleway AL, Goddard K, Dixon BE, Griggs EP, Hansen J, Valvi N, Najdowski M, Timbol J, Rogerson C, Fireman B, Fadel WF, Patel P, Ray CS, Wiegand R, Ball S, Tenforde MW. Estimates of Bivalent mRNA Vaccine Durability in Preventing COVID-19-Associated Hospitalization and Critical Illness Among Adults with and Without Immunocompromising Conditions - VISION Network, September 2022-April 2023. MMWR Morb Mortal Wkly Rep 2023; 72:579-588. [PMID: 37227984 DOI: 10.15585/mmwr.mm7221a3] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
On September 1, 2022, CDC's Advisory Committee on Immunization Practices (ACIP) recommended a single bivalent mRNA COVID-19 booster dose for persons aged ≥12 years who had completed at least a monovalent primary series. Early vaccine effectiveness (VE) estimates among adults aged ≥18 years showed receipt of a bivalent booster dose provided additional protection against COVID-19-associated emergency department and urgent care visits and hospitalizations compared with that in persons who had received only monovalent vaccine doses (1); however, insufficient time had elapsed since bivalent vaccine authorization to assess the durability of this protection. The VISION Network* assessed VE against COVID-19-associated hospitalizations by time since bivalent vaccine receipt during September 13, 2022-April 21, 2023, among adults aged ≥18 years with and without immunocompromising conditions. During the first 7-59 days after vaccination, compared with no vaccination, VE for receipt of a bivalent vaccine dose among adults aged ≥18 years was 62% (95% CI = 57%-67%) among adults without immunocompromising conditions and 28% (95% CI = 10%-42%) among adults with immunocompromising conditions. Among adults without immunocompromising conditions, VE declined to 24% (95% CI = 12%-33%) among those aged ≥18 years by 120-179 days after vaccination. VE was generally lower for adults with immunocompromising conditions. A bivalent booster dose provided the highest protection, and protection was sustained through at least 179 days against critical outcomes, including intensive care unit (ICU) admission or in-hospital death. These data support updated recommendations allowing additional optional bivalent COVID-19 vaccine doses for certain high-risk populations. All eligible persons should stay up to date with recommended COVID-19 vaccines.
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24
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Natarajan K, Weng C, Sengupta S. A Model for Multi-Institutional Clinical Data Repository. Stud Health Technol Inform 2023; 302:312-316. [PMID: 37203669 DOI: 10.3233/shti230125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Creating a sustainable model for clinical data infrastructure requires the inclusion of key stakeholders, harmonization of their needs and constraints, integration with data governance considerations, conforming to FAIR principles while maintaining data safety and data quality, and maintaining financial health for contributing organizations and partners. This paper reflects on Columbia University's 30+ years of experiences in designing and developing clinical data infrastructure that synergizes both patient care and clinical research missions. We define the desiderata for a sustainable model and make recommendations of best practices to achieve a sustainable model.
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25
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Pandey S, Anang V, Singh S, Seth S, Bhatt AN, Kalra N, Manda K, Soni R, Roy BG, Natarajan K, Dwarakanath BS. Dietary administration of the glycolytic inhibitor 2-deoxy-D-glucose reduces endotoxemia-induced inflammation and oxidative stress: Implications in PAMP-associated acute and chronic pathology. Front Pharmacol 2023; 14:940129. [PMID: 37234710 PMCID: PMC10206263 DOI: 10.3389/fphar.2023.940129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 04/20/2023] [Indexed: 05/28/2023] Open
Abstract
Pathogen-associated molecular patterns (PAMPs) like bacterial cell wall components and viral nucleic acids are known ligands of innate inflammatory receptors that trigger multiple inflammatory pathways that may result in acute inflammation and oxidative stress-driven tissue and organ toxicity. When dysregulated, this inflammation may lead to acute toxicity and multiorgan failure. Inflammatory events are often driven by high energy demands and macromolecular biosynthesis. Therefore, we proposed that targeting the metabolism of lipopolysaccharide (LPS)-driven inflammatory events, using an energy restriction approach, can be an effective strategy to prevent the acute or chronic detrimental effects of accidental or seasonal bacterial and other pathogenic exposures. In the present study, we investigated the potential of energy restriction mimetic agent (ERMA) 2-deoxy-D-glucose (2-DG) in targeting the metabolism of inflammatory events during LPS-elicited acute inflammatory response. Mice fed with 2-DG as a dietary component in drinking water showed reduced LPS-driven inflammatory processes. Dietary 2-DG reduced LPS-induced lung endothelial damage and oxidative stress by strengthening the antioxidant defense system and limiting the activation and expression of inflammatory proteins, viz., P-Stat-3, NfκΒ, and MAP kinases. This was accompanied by decreased TNF, IL-1β, and IL-6 levels in peripheral blood and bronchoalveolar lavage fluid (BALF). 2-DG also reduced the infiltration of PMNCs (polymorphonuclear cells) in inflamed tissues. Altered glycolysis and improved mitochondrial activity in 2-DG-treated RAW 264.7 macrophage cells suggested possible impairment of macrophage metabolism and, therefore, activation in macrophages. Taken together, the present study suggests that inclusion of glycolytic inhibitor 2-DG as a part of the diet can be helpful in preventing the severity and poor prognosis associated with inflammatory events during bacterial and other pathogenic exposures.
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Affiliation(s)
- Sanjay Pandey
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
- Infectious Disease Immunology Laboratory, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
- Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Vandana Anang
- Infectious Disease Immunology Laboratory, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Saurabh Singh
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
- Infectious Disease Immunology Laboratory, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
- Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Saurabh Seth
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Anant Narayan Bhatt
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Namita Kalra
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Kailash Manda
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Ravi Soni
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - Bal Gangadhar Roy
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
| | - K. Natarajan
- Infectious Disease Immunology Laboratory, Dr. B.R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Bilikere S. Dwarakanath
- Division of Radiation Biosciences, Institute of Nuclear Medicine and Allied Sciences, Delhi, India
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26
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Perry AS, Annis JS, Master H, Nayor M, Hughes A, Kouame A, Natarajan K, Marginean K, Murthy V, Roden DM, Harris PA, Shah R, Brittain EL. Association of Longitudinal Activity Measures and Diabetes Risk: An Analysis From the National Institutes of Health All of Us Research Program. J Clin Endocrinol Metab 2023; 108:1101-1109. [PMID: 36458881 PMCID: PMC10306083 DOI: 10.1210/clinem/dgac695] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 11/18/2022] [Accepted: 11/29/2022] [Indexed: 12/04/2022]
Abstract
CONTEXT Prior studies of the relationship between physical activity and incident type 2 diabetes mellitus (T2DM) relied primarily on questionnaires at a single time point. OBJECTIVE We sought to investigate the relationship between physical activity and incident T2DM with an innovative approach using data from commercial wearable devices linked to electronic health records in a real-world population. METHODS Using All of Us participants' accelerometer data from their personal Fitbit devices, we used a time-varying Cox proportional hazards models with repeated measures of physical activity for the outcome of incident T2DM. We evaluated for effect modification with age, sex, body mass index (BMI), and sedentary time using multiplicative interaction terms. RESULTS From 5677 participants in the All of Us Research Program (median age 51 years; 74% female; 89% White), there were 97 (2%) cases of incident T2DM over a median follow-up period of 3.8 years between 2010 to 2021. In models adjusted for age, sex, and race, the hazard of incident diabetes was reduced by 44% (95% CI, 15%-63%; P = 0.01) when comparing those with an average daily step count of 10 700 to those with 6000. Similar benefits were seen comparing groups based on average duration of various intensities of activity (eg, lightly active, fairly active, very active). There was no evidence for effect modification by age, sex, BMI, or sedentary time. CONCLUSION Greater time in any type of physical activity intensity was associated with lower risk of T2DM irrespective of age, sex, BMI, or sedentary time.
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Affiliation(s)
- Andrew S Perry
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Jeffrey S Annis
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Hiral Master
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Matthew Nayor
- Sections of Cardiovascular Medicine and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Andrew Hughes
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Aymone Kouame
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University, New York, NY 10032, USA
| | - Kayla Marginean
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Venkatesh Murthy
- Department of Medicine and Radiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Dan M Roden
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN 37203, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Paul A Harris
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, USA
- Department of Biomedical Engineering, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Ravi Shah
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
| | - Evan L Brittain
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN 37203, USA
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27
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Klein NP, Demarco M, Fleming-Dutra KE, Stockwell MS, Kharbanda AB, Gaglani M, Rao S, Lewis N, Irving SA, Hartmann E, Natarajan K, Dalton AF, Zerbo O, DeSilva MB, Konatham D, Stenehjem E, Rowley EAK, Ong TC, Grannis SJ, Sloan-Aagard C, Han J, Verani JR, Raiyani C, Dascomb K, Reese SE, Barron MA, Fadel WF, Naleway AL, Nanez J, Dickerson M, Goddard K, Murthy K, Grisel N, Weber ZA, Dixon BE, Patel P, Fireman B, Arndorfer J, Valvi NR, Griggs EP, Hallowell C, Embi PJ, Ball SW, Thompson MG, Tenforde MW, Link-Gelles R. Effectiveness of BNT162b2 COVID-19 Vaccination in Children and Adolescents. Pediatrics 2023; 151:191035. [PMID: 37026401 DOI: 10.1542/peds.2022-060894] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/08/2023] [Indexed: 04/08/2023] Open
Abstract
OBJECTIVES We assessed BNT162b2 vaccine effectiveness (VE) against mild to moderate and severe coronavirus disease 2019 (COVID-19) in children and adolescents through the Omicron BA.4/BA.5 period. METHODS Using VISION Network records from April 2021 to September 2022, we conducted a test-negative, case-control study assessing VE against COVID-19-associated emergency department/urgent care (ED/UC) encounters and hospitalizations using logistic regression, conditioned on month and site, adjusted for covariates. RESULTS We compared 9800 ED/UC cases with 70 232 controls, and 305 hospitalized cases with 2612 controls. During Delta, 2-dose VE against ED/UC encounters at 12 to 15 years was initially 93% (95% confidence interval 89 to 95), waning to 77% (69% to 84%) after ≥150 days. At ages 16 to 17, VE was initially 93% (86% to 97%), waning to 72% (63% to 79%) after ≥150 days. During Omicron, VE at ages 12 to 15 was initially 64% (44% to 77%), waning to 13% (3% to 23%) after 60 days; at ages 16 to 17 VE was 31% (10% to 47%) during days 60 to 149, waning to 7% (-8 to 20%) after 150 days. A monovalent booster increased VE to 54% (40% to 65%) at ages 12 to 15 and 46% (30% to 58%) at ages 16 to 17. At ages 5 to 11, 2-dose VE was 49% (33% to 61%) initially and 41% (29% to 51%) after 150 days. During Delta, VE against hospitalizations at ages 12 to 17 was high (>97%), and at ages 16 to 17 remained 98% (73% to 100%) beyond 150 days; during Omicron, hospitalizations were too infrequent to precisely estimate VE. CONCLUSIONS BNT162b2 protected children and adolescents against mild to moderate and severe COVID-19. VE was lower during Omicron predominance including BA.4/BA.5, waned after dose 2 but increased after a monovalent booster. Children and adolescents should receive all recommended COVID-19 vaccinations.
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Affiliation(s)
- Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | | | | | - Melissa S Stockwell
- Division of Child and Adolescent Health, Department of Pediatrics, Columbia University Vagelos College of Physicians and Surgeons, New York, New York
- Department of Population and Family Health, Columbia University Mailman School of Public Health, New York, New York
- NewYork-Presbyterian Hospital, New York, New York
| | | | - Manjusha Gaglani
- Department of Pediatrics, Section of Pediatric Infectious Diseases, Baylor Scott & White Health, Temple, Texas
- Department of Medical Education, Texas A&M University College of Medicine, Temple, Texas
| | - Suchitra Rao
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | | | - Emily Hartmann
- Paso del Norte Health Information Exchange (PHIX), El Paso, Texas
| | - Karthik Natarajan
- NewYork-Presbyterian Hospital, New York, New York
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Alexandra F Dalton
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | | | - Deepika Konatham
- Department of Pediatrics, Section of Pediatric Infectious Diseases, Baylor Scott & White Health, Temple, Texas
| | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | | | - Toan C Ong
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- School of Medicine, Indiana University, Indianapolis, Indiana
| | - Chantel Sloan-Aagard
- Paso del Norte Health Information Exchange (PHIX), El Paso, Texas
- Brigham Young University Department of Public Health, Provo, Utah
| | - Jungmi Han
- Paso del Norte Health Information Exchange (PHIX), El Paso, Texas
| | - Jennifer R Verani
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Chandni Raiyani
- Department of Pediatrics, Section of Pediatric Infectious Diseases, Baylor Scott & White Health, Temple, Texas
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | | | - Michelle A Barron
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - William F Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Fairbanks School of Public Health, Indiana University, Indianapolis; and
| | | | - Juan Nanez
- Paso del Norte Health Information Exchange (PHIX), El Paso, Texas
| | - Monica Dickerson
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | - Kempapura Murthy
- Department of Pediatrics, Section of Pediatric Infectious Diseases, Baylor Scott & White Health, Temple, Texas
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | | | - Brian E Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Fairbanks School of Public Health, Indiana University, Indianapolis; and
| | - Palak Patel
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California
| | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | - Nimish R Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
| | - Eric P Griggs
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | | | - Peter J Embi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Mark G Thompson
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Mark W Tenforde
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Ruth Link-Gelles
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
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28
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Tenforde MW, Weber ZA, Natarajan K, Klein NP, Kharbanda AB, Stenehjem E, Embi PJ, Reese SE, Naleway AL, Grannis SJ, DeSilva MB, Ong TC, Gaglani M, Han J, Dickerson M, Fireman B, Dascomb K, Irving SA, Vazquez-Benitez G, Rao S, Konatham D, Patel P, Schrader KE, Lewis N, Grisel N, McEvoy C, Murthy K, Griggs EP, Rowley EAK, Zerbo O, Arndorfer J, Dunne MM, Goddard K, Ray C, Zhuang Y, Timbol J, Najdowski M, Yang DH, Hansen J, Ball SW, Link-Gelles R. Early Estimates of Bivalent mRNA Vaccine Effectiveness in Preventing COVID-19-Associated Emergency Department or Urgent Care Encounters and Hospitalizations Among Immunocompetent Adults - VISION Network, Nine States, September-November 2022. MMWR Morb Mortal Wkly Rep 2023; 71:1637-1646. [PMID: 36921274 PMCID: PMC10027383 DOI: 10.15585/mmwr.mm7153a1] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
During June-October 2022, the SARS-CoV-2 Omicron BA.5 sublineage accounted for most of the sequenced viral genomes in the United States, with further Omicron sublineage diversification through November 2022.* Bivalent mRNA vaccines contain an ancestral SARS-CoV-2 strain component plus an updated component of the Omicron BA.4/BA.5 sublineages. On September 1, 2022, a single bivalent booster dose was recommended for adults who had completed a primary vaccination series (with or without subsequent booster doses), with the last dose administered ≥2 months earlier (1). During September 13-November 18, the VISION Network evaluated vaccine effectiveness (VE) of a bivalent mRNA booster dose (after 2, 3, or 4 monovalent doses) compared with 1) no previous vaccination and 2) previous receipt of 2, 3, or 4 monovalent-only mRNA vaccine doses, among immunocompetent adults aged ≥18 years with an emergency department/urgent care (ED/UC) encounter or hospitalization for a COVID-19-like illness.† VE of a bivalent booster dose (after 2, 3, or 4 monovalent doses) against COVID-19-associated ED/UC encounters was 56% compared with no vaccination, 32% compared with monovalent vaccination only with last dose 2-4 months earlier, and 50% compared with monovalent vaccination only with last dose ≥11 months earlier. VE of a bivalent booster dose (after 2, 3, or 4 monovalent doses) against COVID-19-associated hospitalizations was 59% compared with no vaccination, 42% compared with monovalent vaccination only with last dose 5-7 months earlier, and 48% compared with monovalent vaccination only with last dose ≥11 months earlier. Bivalent vaccines administered after 2, 3, or 4 monovalent doses were effective in preventing medically attended COVID-19 compared with no vaccination and provided additional protection compared with past monovalent vaccination only, with relative protection increasing with time since receipt of the last monovalent dose. All eligible persons should stay up to date with recommended COVID-19 vaccinations, including receiving a bivalent booster dose. Persons should also consider taking additional precautions to avoid respiratory illness this winter season, such as masking in public indoor spaces, especially in areas where COVID-19 community levels are high.
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29
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Link-Gelles R, Levy ME, Natarajan K, Reese SE, Naleway AL, Grannis SJ, Klein NP, DeSilva MB, Ong TC, Gaglani M, Hartmann E, Dickerson M, Stenehjem E, Kharbanda AB, Han J, Spark TL, Irving SA, Dixon BE, Zerbo O, McEvoy CE, Rao S, Raiyani C, Sloan-Aagard C, Patel P, Dascomb K, Uhlemann AC, Dunne MM, Fadel WF, Lewis N, Barron MA, Murthy K, Nanez J, Griggs EP, Grisel N, Annavajhala MK, Akinseye A, Valvi NR, Goddard K, Mamawala M, Arndorfer J, Yang DH, Embí PJ, Fireman B, Ball SW, Tenforde MW. Estimation of COVID-19 mRNA Vaccine Effectiveness and COVID-19 Illness and Severity by Vaccination Status During Omicron BA.4 and BA.5 Sublineage Periods. JAMA Netw Open 2023; 6:e232598. [PMID: 36920396 PMCID: PMC10018321 DOI: 10.1001/jamanetworkopen.2023.2598] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/16/2023] Open
Abstract
IMPORTANCE Recent SARS-CoV-2 Omicron variant sublineages, including BA.4 and BA.5, may be associated with greater immune evasion and less protection against COVID-19 after vaccination. OBJECTIVES To evaluate the estimated vaccine effectiveness (VE) of 2, 3, or 4 doses of COVID-19 mRNA vaccination among immunocompetent adults during a period of BA.4 or BA.5 predominant circulation; and to evaluate the relative severity of COVID-19 in hospitalized patients across Omicron BA.1, BA.2 or BA.2.12.1, and BA.4 or BA.5 sublineage periods. DESIGN, SETTING, AND PARTICIPANTS This test-negative case-control study was conducted in 10 states with data from emergency department (ED) and urgent care (UC) encounters and hospitalizations from December 16, 2021, to August 20, 2022. Participants included adults with COVID-19-like illness and molecular testing for SARS-CoV-2. Data were analyzed from August 2 to September 21, 2022. EXPOSURES mRNA COVID-19 vaccination. MAIN OUTCOMES AND MEASURES The outcomes of interest were COVID-19 ED or UC encounters, hospitalizations, and admission to the intensive care unit (ICU) or in-hospital death. VE associated with protection against medically attended COVID-19 was estimated, stratified by care setting and vaccine doses (2, 3, or 4 doses vs 0 doses as the reference group). Among hospitalized patients with COVID-19, demographic and clinical characteristics and in-hospital outcomes were compared across sublineage periods. RESULTS During the BA.4 and BA.5 predominant period, there were 82 229 eligible ED and UC encounters among patients with COVID-19-like illness (median [IQR] age, 51 [33-70] years; 49 682 [60.4%] female patients), and 19 114 patients (23.2%) had test results positive for SARS-CoV-2; among 21 007 hospitalized patients (median [IQR] age, 71 [58-81] years; 11 209 [53.4%] female patients), 3583 (17.1 %) had test results positive for SARS-CoV-2. Estimated VE against hospitalization was 25% (95% CI, 17%-32%) for receipt of 2 vaccine doses at 150 days or more after receipt, 68% (95% CI, 50%-80%) for a third dose 7 to 119 days after receipt, and 36% (95% CI, 29%-42%) for a third dose 120 days or more (median [IQR], 235 [204-262] days) after receipt. Among patients aged 65 years or older who had received a fourth vaccine dose, VE was 66% (95% CI, 53%-75%) at 7 to 59 days after vaccination and 57% (95% CI, 44%-66%) at 60 days or more (median [IQR], 88 [75-105] days) after vaccination. Among hospitalized patients with COVID-19, ICU admission or in-hospital death occurred in 21.4% of patients during the BA.1 period vs 14.7% during the BA.4 and BA.5 period (standardized mean difference: 0.17). CONCLUSIONS AND RELEVANCE In this case-control study of COVID-19 vaccines and illness, VE associated with protection against medically attended COVID-19 illness was lower with increasing time since last dose; estimated VE was higher after receipt of 1 or 2 booster doses compared with a primary series alone.
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Affiliation(s)
- Ruth Link-Gelles
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | | | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
- New York–Presbyterian Hospital, New York, New York
| | | | | | - Shaun J. Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- School of Medicine, Indiana University, Indianapolis
| | - Nicola P. Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | | | - Toan C. Ong
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora
| | - Manjusha Gaglani
- Baylor Scott and White Health, Temple, Texas
- Texas A&M University College of Medicine, Temple
| | - Emily Hartmann
- Paso del Norte Health Information Exchange, El Paso, Texas
| | - Monica Dickerson
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | | | - Jungmi Han
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | | | | | - Brian E. Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Fairbanks School of Public Health, Indiana University, Indianapolis
| | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | | | - Suchitra Rao
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora
| | | | - Chantel Sloan-Aagard
- Paso del Norte Health Information Exchange, El Paso, Texas
- Department of Public Health, Brigham Young University, Provo, Utah
| | - Palak Patel
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | - Anne-Catrin Uhlemann
- Department of Internal Medicine, Division of Infectious Disease, Columbia University Irving Medical Center, New York, New York
| | | | - William F. Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Fairbanks School of Public Health, Indiana University, Indianapolis
| | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | - Michelle A. Barron
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora
| | | | - Juan Nanez
- Paso del Norte Health Information Exchange, El Paso, Texas
| | - Eric P. Griggs
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | - Medini K. Annavajhala
- Department of Internal Medicine, Division of Infectious Disease, Columbia University Irving Medical Center, New York, New York
| | | | - Nimish R. Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
| | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | | | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah
| | | | - Peter J. Embí
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Vanderbilt University Medical Center, Nashville, Tennessee
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | | | - Mark W. Tenforde
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia
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30
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Bozio CH, Butterfield KA, Briggs Hagen M, Grannis S, Drawz P, Hartmann E, Ong TC, Fireman B, Natarajan K, Dascomb K, Gaglani M, DeSilva MB, Yang DH, Midgley CM, Dixon BE, Naleway AL, Grisel N, Liao IC, Reese SE, Fadel WF, Irving SA, Lewis N, Arndorfer J, Murthy K, Riddles J, Valvi NR, Mamawala M, Embi PJ, Thompson MG, Stenehjem E. Protection from COVID-19 mRNA vaccination and prior SARS-CoV-2 infection against COVID-19-associated encounters in adults during Delta and Omicron predominance. J Infect Dis 2023:7045997. [PMID: 36806690 DOI: 10.1093/infdis/jiad040] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 01/27/2023] [Accepted: 02/10/2023] [Indexed: 02/20/2023] Open
Abstract
BACKGROUND Data assessing protection conferred from COVID-19 mRNA vaccination and/or prior SARS-CoV-2 infection during Delta and Omicron predominance periods in the U.S. are limited. METHODS This cohort study included persons ≥18 years who had ≥1 healthcare encounter across four health systems and had been tested for SARS-CoV-2 before August 26, 2021. COVID-19 mRNA vaccination and prior SARS-CoV-2 infection defined the exposure. Cox regression estimated hazard ratios (HRs) for the Delta and Omicron periods; protection was calculated as (1-HR)x100%. RESULTS Compared to unvaccinated and previously uninfected persons, during Delta predominance, protection against COVID-19-associated hospitalizations was high for those 2- or 3-dose vaccinated and previously infected, 3-dose vaccinated alone, and prior infection alone (range:91%-97%, with overlapping 95% confidence intervals (95%CIs)); during Omicron predominance, estimates were lower (range:77%-90%). Protection against COVID-19-associated emergency department/urgent care (ED/UC) encounters during Delta predominance was high for those exposure groups (range:86%-93%); during Omicron predominance, protection remained high for those 3-dose vaccinated with or without a prior infection (76% (95%CI=67%-83%) and 71% (95%CI=67%-73%), respectively). CONCLUSIONS COVID-19 mRNA vaccination and/or prior SARS-CoV-2 infection provided protection against COVID-19-associated hospitalizations and ED/UC encounters regardless of variant. Staying up-to-date with COVID-19 vaccination still provides protection against severe COVID-19 disease, regardless of prior infection.
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Affiliation(s)
- Catherine H Bozio
- Centers for Disease Control and Prevention COVID-19 Emergency Response Team, Atlanta, Georgia, USA
| | | | - Melissa Briggs Hagen
- Centers for Disease Control and Prevention COVID-19 Emergency Response Team, Atlanta, Georgia, USA
| | - Shaun Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA.,Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Paul Drawz
- Division of Nephrology & Hypertension, University of Minnesota, Minneapolis, Minnesota, USA
| | - Emily Hartmann
- Paso Del Norte Health Information Exchange, El Paso, Texas, USA
| | - Toan C Ong
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.,New York Presbyterian Hospital, New York, New York, USA
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Manjusha Gaglani
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA.,Texas A&M University College of Medicine, Temple, Texas
| | | | | | - Claire M Midgley
- Centers for Disease Control and Prevention COVID-19 Emergency Response Team, Atlanta, Georgia, USA
| | - Brian E Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA.,Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA
| | - Allison L Naleway
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, USA
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - I-Chia Liao
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | | | - William F Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA.,Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA
| | - Stephanie A Irving
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, USA
| | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
| | - Kempapura Murthy
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | | | - Nimish R Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA
| | - Mufaddal Mamawala
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Peter J Embi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana, USA.,Regenstrief Institute, Indianapolis, Indiana, USA
| | - Mark G Thompson
- Centers for Disease Control and Prevention COVID-19 Emergency Response Team, Atlanta, Georgia, USA
| | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, Utah, USA
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Ta CN, Zucker JE, Chiu PH, Fang Y, Natarajan K, Weng C. Clinical and temporal characterization of COVID-19 subgroups using patient vector embeddings of electronic health records. J Am Med Inform Assoc 2023; 30:256-272. [PMID: 36255273 PMCID: PMC9620768 DOI: 10.1093/jamia/ocac208] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/05/2022] [Accepted: 10/17/2022] [Indexed: 01/22/2023] Open
Abstract
OBJECTIVE To identify and characterize clinical subgroups of hospitalized Coronavirus Disease 2019 (COVID-19) patients. MATERIALS AND METHODS Electronic health records of hospitalized COVID-19 patients at NewYork-Presbyterian/Columbia University Irving Medical Center were temporally sequenced and transformed into patient vector representations using Paragraph Vector models. K-means clustering was performed to identify subgroups. RESULTS A diverse cohort of 11 313 patients with COVID-19 and hospitalizations between March 2, 2020 and December 1, 2021 were identified; median [IQR] age: 61.2 [40.3-74.3]; 51.5% female. Twenty subgroups of hospitalized COVID-19 patients, labeled by increasing severity, were characterized by their demographics, conditions, outcomes, and severity (mild-moderate/severe/critical). Subgroup temporal patterns were characterized by the durations in each subgroup, transitions between subgroups, and the complete paths throughout the course of hospitalization. DISCUSSION Several subgroups had mild-moderate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections but were hospitalized for underlying conditions (pregnancy, cardiovascular disease [CVD], etc.). Subgroup 7 included solid organ transplant recipients who mostly developed mild-moderate or severe disease. Subgroup 9 had a history of type-2 diabetes, kidney and CVD, and suffered the highest rates of heart failure (45.2%) and end-stage renal disease (80.6%). Subgroup 13 was the oldest (median: 82.7 years) and had mixed severity but high mortality (33.3%). Subgroup 17 had critical disease and the highest mortality (64.6%), with age (median: 68.1 years) being the only notable risk factor. Subgroups 18-20 had critical disease with high complication rates and long hospitalizations (median: 40+ days). All subgroups are detailed in the full text. A chord diagram depicts the most common transitions, and paths with the highest prevalence, longest hospitalizations, lowest and highest mortalities are presented. Understanding these subgroups and their pathways may aid clinicians in their decisions for better management and earlier intervention for patients.
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Affiliation(s)
- Casey N Ta
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - Jason E Zucker
- Division of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Po-Hsiang Chiu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - Yilu Fang
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
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32
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Tenforde MW, Weber ZA, Natarajan K, Klein NP, Kharbanda AB, Stenehjem E, Embi PJ, Reese SE, Naleway AL, Grannis SJ, DeSilva MB, Ong TC, Gaglani M, Han J, Dickerson M, Fireman B, Dascomb K, Irving SA, Vazquez-Benitez G, Rao S, Konatham D, Patel P, Schrader KE, Lewis N, Grisel N, McEvoy C, Murthy K, Griggs EP, Rowley EAK, Zerbo O, Arndorfer J, Dunne MM, Goddard K, Ray C, Zhuang Y, Timbol J, Najdowski M, Yang DH, Hansen J, Ball SW, Link-Gelles R. Early Estimates of Bivalent mRNA Vaccine Effectiveness in Preventing COVID-19-Associated Emergency Department or Urgent Care Encounters and Hospitalizations Among Immunocompetent Adults - VISION Network, Nine States, September-November 2022. MMWR Morb Mortal Wkly Rep 2022; 71:1616-1624. [PMID: 36580430 PMCID: PMC9812442 DOI: 10.15585/mmwr.mm715152e1] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
During June-October 2022, the SARS-CoV-2 Omicron BA.5 sublineage accounted for most of the sequenced viral genomes in the United States, with further Omicron sublineage diversification through November 2022.* Bivalent mRNA vaccines contain an ancestral SARS-CoV-2 strain component plus an updated component of the Omicron BA.4/BA.5 sublineages. On September 1, 2022, a single bivalent booster dose was recommended for adults who had completed a primary vaccination series (with or without subsequent booster doses), with the last dose administered ≥2 months earlier (1). During September 13-November 18, the VISION Network evaluated vaccine effectiveness (VE) of a bivalent mRNA booster dose (after 2, 3, or 4 monovalent doses) compared with 1) no previous vaccination and 2) previous receipt of 2, 3, or 4 monovalent-only mRNA vaccine doses, among immunocompetent adults aged ≥18 years with an emergency department/urgent care (ED/UC) encounter or hospitalization for a COVID-19-like illness.† VE of a bivalent booster dose (after 2, 3, or 4 monovalent doses) against COVID-19-associated ED/UC encounters was 56% compared with no vaccination, 31% compared with monovalent vaccination only with last dose 2-4 months earlier, and 50% compared with monovalent vaccination only with last dose ≥11 months earlier. VE of a bivalent booster dose (after 2, 3, or 4 monovalent doses) against COVID-19-associated hospitalizations was 57% compared with no vaccination, 38% compared with monovalent vaccination only with last dose 5-7 months earlier, and 45% compared with monovalent vaccination only with last dose ≥11 months earlier. Bivalent vaccines administered after 2, 3, or 4 monovalent doses were effective in preventing medically attended COVID-19 compared with no vaccination and provided additional protection compared with past monovalent vaccination only, with relative protection increasing with time since receipt of the last monovalent dose. All eligible persons should stay up to date with recommended COVID-19 vaccinations, including receiving a bivalent booster dose. Persons should also consider taking additional precautions to avoid respiratory illness this winter season, such as masking in public indoor spaces, especially in areas where COVID-19 community levels are high.
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DeSilva MB, Mitchell PK, Klein NP, Dixon BE, Tenforde MW, Thompson MG, Naleway AL, Grannis SJ, Ong TC, Natarajan K, Reese SE, Zerbo O, Kharbanda AB, Patel P, Stenehjem E, Raiyani C, Irving SA, Fadel WF, Rao S, Han J, Reynolds S, Davis JM, Lewis N, McEvoy C, Dickerson M, Dascomb K, Valvi NR, Barron MA, Goddard K, Vazquez-Benitez G, Grisel N, Mamawala M, Embi PJ, Fireman B, Essien IJ, Griggs EP, Arndorfer J, Gaglani M. Protection of 2 and 3 mRNA Vaccine Doses Against Severe Outcomes Among Adults Hospitalized with COVID-19 – VISION Network, August 2021 – March 2022. J Infect Dis 2022; 227:961-969. [PMID: 36415904 DOI: 10.1093/infdis/jiac458] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 11/14/2022] [Accepted: 11/21/2022] [Indexed: 11/24/2022] Open
Abstract
Abstract
Background
We assessed COVID-19 vaccination impact on illness severity among adults hospitalized with COVID-19 August 2021–March 2022.
Methods
We evaluated differences in intensive care unit (ICU) admission, in-hospital death, and length of stay among vaccinated (2 or 3 mRNA vaccine doses) versus unvaccinated patients aged ≥18 years hospitalized for ≥24 hours with COVID-19-like illness (CLI) and positive SARS-CoV-2 molecular testing. We calculated odds ratios for ICU admission and death and subdistribution hazard ratios (SHR) for time to hospital discharge adjusted for age, geographic region, calendar time, and local virus circulation.
Results
We included 27,149 SARS-CoV-2 positive hospitalizations. During both Delta and Omicron-predominant periods, protection against ICU admission was strongest among 3-dose vaccinees compared with unvaccinated patients (Delta OR [CI]: 0.52 [0.28–0.96]); Omicron OR [CI]: 0.69 [0.54–0.87]). During both periods, risk of in-hospital of death was lower among vaccinated compared with unvaccinated but ORs were overlapping; during Omicron, lowest among 3-dose vaccinees (OR [CI] 0.39 [0.28–0.54]). We observed SHR >1 across all vaccination strata in both periods indicating faster discharge for vaccinated patients.
Conclusions
COVID-19 vaccination was associated with lower rates of ICU admission and in-hospital death in both Delta and Omicron periods compared with being unvaccinated.
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Affiliation(s)
- Malini B DeSilva
- HealthPartners Institute , Minneapolis, Minnesota , United States
| | | | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research , Oakland, California , United States
| | - Brian E Dixon
- Center for Biomedical Informatics, Regenstrief Institute , Indianapolis, Indiana , United States
- Fairbanks School of Public Health, Indiana University , Indianapolis, Indiana , United States
| | - Mark W Tenforde
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia , United States
| | - Mark G Thompson
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia , United States
| | - Allison L Naleway
- Center for Health Research, Kaiser Permanente Northwest , Portland, Oregon , United States
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute , Indianapolis, Indiana , United States
- School of Medicine, Indiana University , Indianapolis, Indiana , United States
| | - Toan C Ong
- School of Medicine, University of Colorado Anschutz Medical Campus , Aurora, Colorado , United States
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York , New York
- New York Presbyterian Hospital, New York , New York , United States
| | | | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research , Oakland, California , United States
| | | | - Palak Patel
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia , United States
| | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare , Salt Lake City, Utah , United States
| | | | - Stephanie A Irving
- Center for Health Research, Kaiser Permanente Northwest , Portland, Oregon , United States
| | - William F Fadel
- Center for Biomedical Informatics, Regenstrief Institute , Indianapolis, Indiana , United States
- Fairbanks School of Public Health, Indiana University , Indianapolis, Indiana , United States
| | - Suchitra Rao
- School of Medicine, Indiana University , Indianapolis, Indiana , United States
| | - Jungmi Han
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York , New York
| | - Sue Reynolds
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia , United States
| | | | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research , Oakland, California , United States
| | - Charlene McEvoy
- HealthPartners Institute , Minneapolis, Minnesota , United States
| | - Monica Dickerson
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia , United States
| | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare , Salt Lake City, Utah , United States
| | - Nimish R Valvi
- Center for Biomedical Informatics, Regenstrief Institute , Indianapolis, Indiana , United States
| | - Michelle A Barron
- School of Medicine, University of Colorado Anschutz Medical Campus , Aurora, Colorado , United States
| | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research , Oakland, California , United States
| | | | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare , Salt Lake City, Utah , United States
| | | | - Peter J Embi
- Center for Biomedical Informatics, Regenstrief Institute , Indianapolis, Indiana , United States
- Vanderbilt University Medical Center , Nashville, Tennessee , United States
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research , Oakland, California , United States
| | - Inih J Essien
- HealthPartners Institute , Minneapolis, Minnesota , United States
| | - Eric P Griggs
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, Georgia , United States
| | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare , Salt Lake City, Utah , United States
| | - Manjusha Gaglani
- Texas A&M University College of Medicine , Temple, Texas , United States
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Cho S, Ensari I, Elhadad N, Weng C, Radin JM, Bent B, Desai P, Natarajan K. An interactive fitness-for-use data completeness tool to assess activity tracker data. J Am Med Inform Assoc 2022; 29:2032-2040. [PMID: 36173371 PMCID: PMC9667174 DOI: 10.1093/jamia/ocac166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 07/29/2022] [Accepted: 09/16/2022] [Indexed: 11/12/2022] Open
Abstract
OBJECTIVE To design and evaluate an interactive data quality (DQ) characterization tool focused on fitness-for-use completeness measures to support researchers' assessment of a dataset. MATERIALS AND METHODS Design requirements were identified through a conceptual framework on DQ, literature review, and interviews. The prototype of the tool was developed based on the requirements gathered and was further refined by domain experts. The Fitness-for-Use Tool was evaluated through a within-subjects controlled experiment comparing it with a baseline tool that provides information on missing data based on intrinsic DQ measures. The tools were evaluated on task performance and perceived usability. RESULTS The Fitness-for-Use Tool allows users to define data completeness by customizing the measures and its thresholds to fit their research task and provides a data summary based on the customized definition. Using the Fitness-for-Use Tool, study participants were able to accurately complete fitness-for-use assessment in less time than when using the Intrinsic DQ Tool. The study participants perceived that the Fitness-for-Use Tool was more useful in determining the fitness-for-use of a dataset than the Intrinsic DQ Tool. DISCUSSION Incorporating fitness-for-use measures in a DQ characterization tool could provide data summary that meets researchers needs. The design features identified in this study has potential to be applied to other biomedical data types. CONCLUSION A tool that summarizes a dataset in terms of fitness-for-use dimensions and measures specific to a research question supports dataset assessment better than a tool that only presents information on intrinsic DQ measures.
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Affiliation(s)
- Sylvia Cho
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Ipek Ensari
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine, New York, New York, USA
- Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Noémie Elhadad
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
- Data Science Institute, Columbia University, New York, New York, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
- Data Science Institute, Columbia University, New York, New York, USA
| | - Jennifer M Radin
- Scripps Research Translational Institute, La Jolla, California, USA
| | - Brinnae Bent
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Pooja Desai
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
- Data Science Institute, Columbia University, New York, New York, USA
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Britton A, Embi PJ, Levy ME, Gaglani M, DeSilva MB, Dixon BE, Dascomb K, Patel P, Schrader KE, Klein NP, Ong TC, Natarajan K, Hartmann E, Kharbanda AB, Irving SA, Dickerson M, Dunne MM, Raiyani C, Grannis SJ, Stenehjem E, Zerbo O, Rao S, Han J, Sloan-Aagard C, Griggs EP, Weber ZA, Murthy K, Fadel WF, Grisel N, McEvoy C, Lewis N, Barron MA, Nanez J, Reese SE, Mamawala M, Valvi NR, Arndorfer J, Goddard K, Yang DH, Fireman B, Ball SW, Link-Gelles R, Naleway AL, Tenforde MW. Effectiveness of COVID-19 mRNA Vaccines Against COVID-19-Associated Hospitalizations Among Immunocompromised Adults During SARS-CoV-2 Omicron Predominance - VISION Network, 10 States, December 2021-August 2022. MMWR Morb Mortal Wkly Rep 2022; 71:1335-1342. [PMID: 36264840 PMCID: PMC9590295 DOI: 10.15585/mmwr.mm7142a4] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Persons with moderate-to-severe immunocompromising conditions might have reduced protection after COVID-19 vaccination, compared with persons without immunocompromising conditions (1-3). On August 13, 2021, the Advisory Committee on Immunization Practices (ACIP) recommended that adults with immunocompromising conditions receive an expanded primary series of 3 doses of an mRNA COVID-19 vaccine. ACIP followed with recommendations on September 23, 2021, for a fourth (booster) dose and on September 1, 2022, for a new bivalent mRNA COVID-19 vaccine booster dose, containing components of the BA.4 and BA.5 sublineages of the Omicron (B.1.1.529) variant (4). Data on vaccine effectiveness (VE) of monovalent COVID-19 vaccines among persons with immunocompromising conditions since the emergence of the Omicron variant in December 2021 are limited. In the multistate VISION Network,§ monovalent 2-, 3-, and 4-dose mRNA VE against COVID-19-related hospitalization were estimated among adults with immunocompromising conditions¶ hospitalized with COVID-19-like illness,** using a test-negative design comparing odds of previous vaccination among persons with a positive or negative molecular test result (case-patients and control-patients) for SARS-CoV-2 (the virus that causes COVID-19). During December 16, 2021-August 20, 2022, among SARS-CoV-2 test-positive case-patients, 1,815 (36.3%), 1,387 (27.7%), 1,552 (31.0%), and 251 (5.0%) received 0, 2, 3, and 4 mRNA COVID-19 vaccine doses, respectively. Among test-negative control-patients during this period, 6,928 (23.7%), 7,411 (25.4%), 12,734 (43.6%), and 2,142 (7.3%) received these respective doses. Overall, VE against COVID-19-related hospitalization among adults with immunocompromising conditions hospitalized for COVID-like illness during Omicron predominance was 36% ≥14 days after dose 2, 69% 7-89 days after dose 3, and 44% ≥90 days after dose 3. Restricting the analysis to later periods when Omicron sublineages BA.2/BA.2.12.1 and BA.4/BA.5 were predominant and 3-dose recipients were eligible to receive a fourth dose, VE was 32% ≥90 days after dose 3 and 43% ≥7 days after dose 4. Protection offered by vaccination among persons with immunocompromising conditions during Omicron predominance was moderate even after a 3-dose monovalent primary series or booster dose. Given the incomplete protection against hospitalization afforded by monovalent COVID-19 vaccines, persons with immunocompromising conditions might benefit from updated bivalent vaccine booster doses that target recently circulating Omicron sublineages, in line with ACIP recommendations. Further, additional protective recommendations for persons with immunocompromising conditions, including the use of prophylactic antibody therapy, early access to and use of antivirals, and enhanced nonpharmaceutical interventions such as well-fitting masks or respirators, should also be considered.
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Ferdinands JM, Rao S, Dixon BE, Mitchell PK, DeSilva MB, Irving SA, Lewis N, Natarajan K, Stenehjem E, Grannis SJ, Han J, McEvoy C, Ong TC, Naleway AL, Reese SE, Embi PJ, Dascomb K, Klein NP, Griggs EP, Liao IC, Yang DH, Fadel WF, Grisel N, Goddard K, Patel P, Murthy K, Birch R, Valvi NR, Arndorfer J, Zerbo O, Dickerson M, Raiyani C, Williams J, Bozio CH, Blanton L, Link-Gelles R, Barron MA, Gaglani M, Thompson MG, Fireman B. Waning of vaccine effectiveness against moderate and severe covid-19 among adults in the US from the VISION network: test negative, case-control study. BMJ 2022; 379:e072141. [PMID: 36191948 PMCID: PMC9527398 DOI: 10.1136/bmj-2022-072141] [Citation(s) in RCA: 57] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
OBJECTIVE To estimate the effectiveness of mRNA vaccines against moderate and severe covid-19 in adults by time since second, third, or fourth doses, and by age and immunocompromised status. DESIGN Test negative case-control study. SETTING Hospitals, emergency departments, and urgent care clinics in 10 US states, 17 January 2021 to 12 July 2022. PARTICIPANTS 893 461 adults (≥18 years) admitted to one of 261 hospitals or to one of 272 emergency department or 119 urgent care centers for covid-like illness tested for SARS-CoV-2. MAIN OUTCOME MEASURES The main outcome was waning of vaccine effectiveness with BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) vaccine during the omicron and delta periods, and the period before delta was dominant using logistic regression conditioned on calendar week and geographic area while adjusting for age, race, ethnicity, local virus circulation, immunocompromised status, and likelihood of being vaccinated. RESULTS 45 903 people admitted to hospital with covid-19 (cases) were compared with 213 103 people with covid-like illness who tested negative for SARS-CoV-2 (controls), and 103 287 people admitted to emergency department or urgent care with covid-19 (cases) were compared with 531 168 people with covid-like illness who tested negative for SARS-CoV-2. In the omicron period, vaccine effectiveness against covid-19 requiring admission to hospital was 89% (95% confidence interval 88% to 90%) within two months after dose 3 but waned to 66% (63% to 68%) by four to five months. Vaccine effectiveness of three doses against emergency department or urgent care visits was 83% (82% to 84%) initially but waned to 46% (44% to 49%) by four to five months. Waning was evident in all subgroups, including young adults and individuals who were not immunocompromised; although waning was morein people who were immunocompromised. Vaccine effectiveness increased among most groups after a fourth dose in whom this booster was recommended. CONCLUSIONS Effectiveness of mRNA vaccines against moderate and severe covid-19 waned with time after vaccination. The findings support recommendations for a booster dose after a primary series and consideration of additional booster doses.
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Affiliation(s)
- Jill M Ferdinands
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | - Suchitra Rao
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Brian E Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
- Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | | | | | - Stephanie A Irving
- Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA
| | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
- New York Presbyterian Hospital, New York, NY, USA
| | - Edward Stenehjem
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Shaun J Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jungmi Han
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Toan C Ong
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Allison L Naleway
- Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA
| | | | | | - Kristin Dascomb
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Eric P Griggs
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | | | | | - William F Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
- Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | - Nancy Grisel
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Palak Patel
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | | | | | - Nimish R Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA
| | - Julie Arndorfer
- Division of Infectious Diseases and Clinical Epidemiology, Intermountain Healthcare, Salt Lake City, UT, USA
| | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Monica Dickerson
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | | | - Jeremiah Williams
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | - Catherine H Bozio
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | - Lenee Blanton
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | - Ruth Link-Gelles
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | - Michelle A Barron
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Mark G Thompson
- Centers for Disease Control and Prevention COVID-19 Response Team, Atlanta, GA, USA
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
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Castano VG, Spotnitz M, Waldman GJ, Joiner EF, Choi H, Ostropolets A, Natarajan K, McKhann GM, Ottman R, Neugut AI, Hripcsak G, Youngerman BE. Identification of patients with drug resistant epilepsy in electronic medical record data using the Observational Medical Outcomes Partnership Common Data Model. Epilepsia 2022; 63:2981-2993. [DOI: 10.1111/epi.17409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 09/05/2022] [Accepted: 09/12/2022] [Indexed: 11/03/2022]
Affiliation(s)
- Victor G. Castano
- Department of Neurological Surgery, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Matthew Spotnitz
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Genna J. Waldman
- Department of Neurology, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Evan F. Joiner
- Department of Neurological Surgery, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Hyunmi Choi
- Department of Neurology, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Anna Ostropolets
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Karthik Natarajan
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Guy M. McKhann
- Department of Neurological Surgery, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Ruth Ottman
- Department of Neurology, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
- The Gertrude H. Sergievsky Center Columbia University Irving Medical Center New York New York USA
- Department of Epidemiology, Mailman School of Public Health Columbia University New York New York USA
- Division of Translational Epidemiology and Mental Health Equity New York State Psychiatric Institute New York New York USA
| | - Alfred I. Neugut
- Department of Epidemiology, Mailman School of Public Health Columbia University New York New York USA
- Department of Medicine, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
- Herbert Irving Comprehensive Cancer Center, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - George Hripcsak
- Department of Biomedical Informatics, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
| | - Brett E. Youngerman
- Department of Neurological Surgery, Vagelos College of Physicians and Surgeons Columbia University New York New York USA
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Schrag SJ, Verani JR, Dixon BE, Page JM, Butterfield KA, Gaglani M, Vazquez-Benitez G, Zerbo O, Natarajan K, Ong TC, Lazariu V, Rao S, Beaver R, Ellington SR, Klein NP, Irving SA, Grannis SJ, Kiduko S, Barron MA, Midturi J, Dickerson M, Lewis N, Stockwell MS, Stenehjem E, Fadel WF, Link-Gelles R, Murthy K, Goddard K, Grisel N, Valvi NR, Fireman B, Arndorfer J, Konatham D, Ball S, Thompson MG, Naleway AL. Estimation of COVID-19 mRNA Vaccine Effectiveness Against Medically Attended COVID-19 in Pregnancy During Periods of Delta and Omicron Variant Predominance in the United States. JAMA Netw Open 2022; 5:e2233273. [PMID: 36156146 PMCID: PMC9513651 DOI: 10.1001/jamanetworkopen.2022.33273] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
IMPORTANCE Pregnant people are at high risk for severe COVID-19 but were excluded from mRNA vaccine trials; data on COVID-19 vaccine effectiveness (VE) are needed. OBJECTIVE To evaluate the estimated effectiveness of mRNA vaccination against medically attended COVID-19 among pregnant people during Delta and Omicron predominance. DESIGN, SETTING, AND PARTICIPANTS This test-negative, case-control study was conducted from June 2021 to June 2022 in a network of 306 hospitals and 164 emergency department and urgent care (ED/UC) facilities across 10 US states, including 4517 ED/UC encounters and 975 hospitalizations among pregnant people with COVID-19-like illness (CLI) who underwent SARS-CoV-2 molecular testing. EXPOSURES Two doses (14-149 and ≥150 days prior) and 3 doses (7-119 and ≥120 days prior) of COVID-19 mRNA vaccine (≥1 dose received during pregnancy) vs unvaccinated. MAIN OUTCOMES AND MEASURES Estimated VE against laboratory-confirmed COVID-19-associated ED/UC encounter or hospitalization, based on the adjusted odds ratio (aOR) for prior vaccination; VE was calculated as (1 - aOR) × 100%. RESULTS Among 4517 eligible CLI-associated ED/UC encounters and 975 hospitalizations, 885 (19.6%) and 334 (34.3%) were SARS-CoV-2 positive, respectively; the median (IQR) patient age was 28 (24-32) years and 31 (26-35) years, 537 (12.0%) and 118 (12.0%) were non-Hispanic Black and 1189 (26.0%) and 240 (25.0%) were Hispanic. During Delta predominance, the estimated VE against COVID-19-associated ED/UC encounters was 84% (95% CI, 69% to 92%) for 2 doses within 14 to 149 days, 75% (95% CI, 5% to 93%) for 2 doses 150 or more days prior, and 81% (95% CI, 30% to 95%) for 3 doses 7 to 119 days prior; estimated VE against COVID-19-associated hospitalization was 99% (95% CI, 96% to 100%), 96% (95% CI, 86% to 99%), and 97% (95% CI, 79% to 100%), respectively. During Omicron predominance, for ED/UC encounters, the estimated VE of 2 doses within 14 to 149 days, 2 doses 150 or more days, 3 doses within 7 to 119 days, and 3 doses 120 or more days prior was 3% (95% CI, -49% to 37%), 42% (95% CI, -16% to 72%), 79% (95% CI, 59% to 89%), and -124% (95% CI, -414% to 2%), respectively; for hospitalization, estimated VE was 86% (95% CI, 41% to 97%), 64% (95% CI, -102% to 93%), 86% (95% CI, 28% to 97%), and -53% (95% CI, -1254% to 83%), respectively. CONCLUSIONS AND RELEVANCE In this study, maternal mRNA COVID-19 vaccination, including booster dose, was associated with protection against medically attended COVID-19. VE estimates were higher against COVID-19-associated hospitalization than ED/UC visits and lower against the Omicron variant than the Delta variant. Protection waned over time, particularly during Omicron predominance.
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Affiliation(s)
| | | | - Brian E. Dixon
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Fairbanks School of Public Health, Indiana University, Indianapolis
| | - Jessica M. Page
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Intermountain Healthcare, University of Utah, Salt Lake City
| | | | - Manjusha Gaglani
- Baylor Scott & White Health Temple, Texas
- Texas A&M University College of Medicine, Temple
| | | | - Ousseny Zerbo
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
- NewYork-Presbyterian Hospital, New York
| | - Toan C. Ong
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora
| | | | - Suchitra Rao
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora
| | | | | | - Nicola P. Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | | | - Shaun J. Grannis
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Indiana University School of Medicine, Indianapolis
| | | | - Michelle A. Barron
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora
| | | | | | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | - Melissa S. Stockwell
- NewYork-Presbyterian Hospital, New York
- Division of Child and Adolescent Health, Department of Pediatrics, Columbia University Vagelos College of Physicians and Surgeons, New York, New York
- Department of Population and Family Health, Columbia University Mailman School of Public Health, New York, New York
| | - Edward Stenehjem
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Intermountain Healthcare, University of Utah, Salt Lake City
| | - William F. Fadel
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
- Fairbanks School of Public Health, Indiana University, Indianapolis
| | | | | | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | - Nancy Grisel
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Intermountain Healthcare, University of Utah, Salt Lake City
| | - Nimish R. Valvi
- Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, Indiana
| | - Bruce Fireman
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California Division of Research, Oakland
| | - Julie Arndorfer
- Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Intermountain Healthcare, University of Utah, Salt Lake City
| | | | | | | | - Allison L. Naleway
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
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Natarajan K, Sharma S, Irfana Jesin CP, Kataria R, Nandi GC. One-pot synthesis of α-sulfoximinophosphonate via Kabachnik-Fields reaction. Org Biomol Chem 2022; 20:7036-7039. [PMID: 36040442 DOI: 10.1039/d2ob01355j] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Herein, we disclose a novel approach for the synthesis of hitherto unknown α-sulfoximinophosphonate via the Kabachnik-Fields reaction of aldehyde, dialkylphosphite and sulfoximine in the presence of InCl3 in THF at 70 °C. α-Sulfoximinophosphonate is synthesized in good yields and its synthetic utilities are proved by functionalizing bromine through the Pd-catalyzed Suzuki-Miyaura cross-coupling reaction and reduction of a nitro group through the Béchamp reduction.
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Affiliation(s)
- K Natarajan
- Department of Chemistry, National Institute of Technology-Tiruchirappalli 620015, Tamil Nadu, India.
| | - Suraj Sharma
- Department of Chemistry, National Institute of Technology-Tiruchirappalli 620015, Tamil Nadu, India.
| | - C P Irfana Jesin
- Department of Chemistry, National Institute of Technology-Tiruchirappalli 620015, Tamil Nadu, India.
| | - Ramesh Kataria
- Department of Chemistry & Centre for Advanced Studies in Chemistry, Panjab University, Chandigarh-160014, India
| | - Ganesh Chandra Nandi
- Department of Chemistry, National Institute of Technology-Tiruchirappalli 620015, Tamil Nadu, India.
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Ramirez AH, Sulieman L, Schlueter DJ, Halvorson A, Qian J, Ratsimbazafy F, Loperena R, Mayo K, Basford M, Deflaux N, Muthuraman KN, Natarajan K, Kho A, Xu H, Wilkins C, Anton-Culver H, Boerwinkle E, Cicek M, Clark CR, Cohn E, Ohno-Machado L, Schully SD, Ahmedani BK, Argos M, Cronin RM, O’Donnell C, Fouad M, Goldstein DB, Greenland P, Hebbring SJ, Karlson EW, Khatri P, Korf B, Smoller JW, Sodeke S, Wilbanks J, Hentges J, Mockrin S, Lunt C, Devaney SA, Gebo K, Denny JC, Carroll RJ, Glazer D, Harris PA, Hripcsak G, Philippakis A, Roden DM, Ahmedani B, Cole Johnson CD, Ahsan H, Antoine-LaVigne D, Singleton G, Anton-Culver H, Topol E, Baca-Motes K, Steinhubl S, Wade J, Begale M, Jain P, Sutherland S, Lewis B, Korf B, Behringer M, Gharavi AG, Goldstein DB, Hripcsak G, Bier L, Boerwinkle E, Brilliant MH, Murali N, Hebbring SJ, Farrar-Edwards D, Burnside E, Drezner MK, Taylor A, Channamsetty V, Montalvo W, Sharma Y, Chinea C, Jenks N, Cicek M, Thibodeau S, Holmes BW, Schlueter E, Collier E, Winkler J, Corcoran J, D’Addezio N, Daviglus M, Winn R, Wilkins C, Roden D, Denny J, Doheny K, Nickerson D, Eichler E, Jarvik G, Funk G, Philippakis A, Rehm H, Lennon N, Kathiresan S, Gabriel S, Gibbs R, Gil Rico EM, Glazer D, Grand J, Greenland P, Harris P, Shenkman E, Hogan WR, Igho-Pemu P, Pollan C, Jorge M, Okun S, Karlson EW, Smoller J, Murphy SN, Ross ME, Kaushal R, Winford E, Wallace F, Khatri P, Kheterpal V, Ojo A, Moreno FA, Kron I, Peterson R, Menon U, Lattimore PW, Leviner N, Obedin-Maliver J, Lunn M, Malik-Gagnon L, Mangravite L, Marallo A, Marroquin O, Visweswaran S, Reis S, Marshall G, McGovern P, Mignucci D, Moore J, Munoz F, Talavera G, O'Connor GT, O'Donnell C, Ohno-Machado L, Orr G, Randal F, Theodorou AA, Reiman E, Roxas-Murray M, Stark L, Tepp R, Zhou A, Topper S, Trousdale R, Tsao P, Weidman L, Weiss ST, Wellis D, Whittle J, Wilson A, Zuchner S, Zwick ME. The All of Us Research Program: Data quality, utility, and diversity. Patterns 2022; 3:100570. [PMID: 36033590 PMCID: PMC9403360 DOI: 10.1016/j.patter.2022.100570] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 03/30/2022] [Accepted: 07/14/2022] [Indexed: 11/05/2022]
Abstract
The All of Us Research Program seeks to engage at least one million diverse participants to advance precision medicine and improve human health. We describe here the cloud-based Researcher Workbench that uses a data passport model to democratize access to analytical tools and participant information including survey, physical measurement, and electronic health record (EHR) data. We also present validation study findings for several common complex diseases to demonstrate use of this novel platform in 315,000 participants, 78% of whom are from groups historically underrepresented in biomedical research, including 49% self-reporting non-White races. Replication findings include medication usage pattern differences by race in depression and type 2 diabetes, validation of known cancer associations with smoking, and calculation of cardiovascular risk scores by reported race effects. The cloud-based Researcher Workbench represents an important advance in enabling secure access for a broad range of researchers to this large resource and analytical tools. The All of Us Research Program has released data for over 315,000 participants Demonstration projects support the utility and validity of the All of Us dataset The cloud-based Researcher Workbench provides secure, low-cost compute power
The engagement of participants in the research process and broad availability of data to diverse researchers are essential elements in building precision medicine equitably available for all. The NIH has established the ambitious All of Us Research Program to build one of the most diverse health databases in history with tools to support research to improve human health. Here, we present the initial launch of the Researcher Workbench with data types including surveys, physical measurements, and electronic health record data with validation studies to support researcher use of this novel platform. Broad access for researchers to data like these is a critical step in returning value to participants seeking to support the advancement of precision medicine and improved health for all.
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Link-Gelles R, Levy ME, Gaglani M, Irving SA, Stockwell M, Dascomb K, DeSilva MB, Reese SE, Liao IC, Ong TC, Grannis SJ, McEvoy C, Patel P, Klein NP, Hartmann E, Stenehjem E, Natarajan K, Naleway AL, Murthy K, Rao S, Dixon BE, Kharbanda AB, Akinseye A, Dickerson M, Lewis N, Grisel N, Han J, Barron MA, Fadel WF, Dunne MM, Goddard K, Arndorfer J, Konatham D, Valvi NR, Currey JC, Fireman B, Raiyani C, Zerbo O, Sloan-Aagard C, Ball SW, Thompson MG, Tenforde MW. Effectiveness of 2, 3, and 4 COVID-19 mRNA Vaccine Doses Among Immunocompetent Adults During Periods when SARS-CoV-2 Omicron BA.1 and BA.2/BA.2.12.1 Sublineages Predominated - VISION Network, 10 States, December 2021-June 2022. MMWR Morb Mortal Wkly Rep 2022; 71:931-939. [PMID: 35862287 PMCID: PMC9310634 DOI: 10.15585/mmwr.mm7129e1] [Citation(s) in RCA: 73] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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Spotnitz M, Patterson J, Huser V, Weng C, Natarajan K. Harmonization of Measurement Codes for Concept-Oriented Lab Data Retrieval. Stud Health Technol Inform 2022; 290:12-16. [PMID: 35672961 DOI: 10.3233/shti220022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Measurement concepts are essential to observational healthcare research; however, a lack of concept harmonization limits the quality of research that can be done on multisite research networks. We developed five methods that used a combination of automated, semi-automated and manual approaches for generating measurement concept sets. We validated our concept sets by calculating their frequencies in cohorts from the Columbia University Irving Medical Center (CUIMC) database. For heart transplant patients, the preoperative frequencies of basic metabolic panel concept sets, which we generated by a semi-automated approach, were greater than 99%. We also made concept sets for lumbar puncture and coagulation panels, by automated and manual methods respectively.
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Affiliation(s)
- Matthew Spotnitz
- Columbia University Medical Center Department of Biomedical Informatics
| | - Jason Patterson
- Columbia University Medical Center Department of Biomedical Informatics
| | | | - Chunhua Weng
- Columbia University Medical Center Department of Biomedical Informatics
| | - Karthik Natarajan
- Columbia University Medical Center Department of Biomedical Informatics
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Liu C, Lee J, Ta C, Soroush A, Rogers JR, Kim JH, Natarajan K, Zucker J, Perl Y, Weng C. Risk Factors Associated With SARS-CoV-2 Breakthrough Infections in Fully mRNA-Vaccinated Individuals: Retrospective Analysis. JMIR Public Health Surveill 2022; 8:e35311. [PMID: 35486806 PMCID: PMC9132195 DOI: 10.2196/35311] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 03/29/2022] [Accepted: 04/27/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND COVID-19 messenger RNA (mRNA) vaccines have demonstrated efficacy and effectiveness in preventing symptomatic COVID-19, while being relatively safe in trial studies. However, vaccine breakthrough infections have been reported. OBJECTIVE This study aims to identify risk factors associated with COVID-19 breakthrough infections among fully mRNA-vaccinated individuals. METHODS We conducted a series of observational retrospective analyses using the electronic health records (EHRs) of the Columbia University Irving Medical Center/New York Presbyterian (CUIMC/NYP) up to September 21, 2021. New York City (NYC) adult residences with at least 1 polymerase chain reaction (PCR) record were included in this analysis. Poisson regression was performed to assess the association between the breakthrough infection rate in vaccinated individuals and multiple risk factors-including vaccine brand, demographics, and underlying conditions-while adjusting for calendar month, prior number of visits, and observational days in the EHR. RESULTS The overall estimated breakthrough infection rate was 0.16 (95% CI 0.14-0.18). Individuals who were vaccinated with Pfizer/BNT162b2 (incidence rate ratio [IRR] against Moderna/mRNA-1273=1.66, 95% CI 1.17-2.35) were male (IRR against female=1.47, 95% CI 1.11-1.94) and had compromised immune systems (IRR=1.48, 95% CI 1.09-2.00) were at the highest risk for breakthrough infections. Among all underlying conditions, those with primary immunodeficiency, a history of organ transplant, an active tumor, use of immunosuppressant medications, or Alzheimer disease were at the highest risk. CONCLUSIONS Although we found both mRNA vaccines were effective, Moderna/mRNA-1273 had a lower incidence rate of breakthrough infections. Immunocompromised and male individuals were among the highest risk groups experiencing breakthrough infections. Given the rapidly changing nature of the SARS-CoV-2 pandemic, continued monitoring and a generalizable analysis pipeline are warranted to inform quick updates on vaccine effectiveness in real time.
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Affiliation(s)
- Cong Liu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States
| | - Junghwan Lee
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States
| | - Casey Ta
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States
| | - Ali Soroush
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States
| | - James R Rogers
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States
| | - Jae Hyun Kim
- School of Pharmacy, Jeonbuk National University, Jeonju, Republic of Korea
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States
| | - Jason Zucker
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, United States
| | - Yehoshua Perl
- Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, United States
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, United States
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Spotnitz M, Ostropolets A, Castano VG, Natarajan K, Waldman GJ, Argenziano M, Ottman R, Hripcsak G, Choi H, Youngerman BE. Patient characteristics and antiseizure medication pathways in newly diagnosed epilepsy: Feasibility and pilot results using the common data model in a single-center electronic medical record database. Epilepsy Behav 2022; 129:108630. [PMID: 35276502 DOI: 10.1016/j.yebeh.2022.108630] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/28/2022] [Accepted: 02/14/2022] [Indexed: 11/16/2022]
Abstract
INTRODUCTION Efforts to characterize variability in epilepsy treatment pathways are limited by the large number of possible antiseizure medication (ASM) regimens and sequences, heterogeneity of patients, and challenges of measuring confounding variables and outcomes across institutions. The Observational Health Data Science and Informatics (OHDSI) collaborative is an international data network representing over 1 billion patient records using common data standards. However, few studies have applied OHDSI's Common Data Model (CDM) to the population with epilepsy and none have validated relevant concepts. The goals of this study were to demonstrate the feasibility of characterizing adult patients with epilepsy and ASM treatment pathways using the CDM in an electronic health record (EHR)-derived database. METHODS We validated a phenotype algorithm for epilepsy in adults using the CDM in an EHR-derived database (2001-2020) against source records and a prospectively maintained database of patients with confirmed epilepsy. We obtained the frequency of all antecedent conditions and procedures for patients meeting the epilepsy phenotype criteria and characterized ASM exposure sequences over time and by age and sex. RESULTS The phenotype algorithm identified epilepsy with 73.0-85.0% positive predictive value and 86.3% sensitivity. Many patients had neurologic conditions and diagnoses antecedent to meeting epilepsy criteria. Levetiracetam incrementally replaced phenytoin as the most common first-line agent, but significant heterogeneity remained, particularly in second-line and subsequent agents. Drug sequences included up to 8 unique ingredients and a total of 1,235 unique pathways were observed. CONCLUSIONS Despite the availability of additional ASMs in the last 2 decades and accumulated guidelines and evidence, ASM use varies significantly in practice, particularly for second-line and subsequent agents. Multi-center OHDSI studies have the potential to better characterize the full extent of variability and support observational comparative effectiveness research, but additional work is needed to validate covariates and outcomes.
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Affiliation(s)
- Matthew Spotnitz
- Department of Biomedical Informatics, Columbia University Irving Medical Center, United States
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, United States
| | - Victor G Castano
- Department of Neurological Surgery, Columbia University Irving Medical Center, United States
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, United States
| | - Genna J Waldman
- Department of Neurology, Columbia University Irving Medical Center, United States
| | - Michael Argenziano
- Department of Neurological Surgery, Columbia University Irving Medical Center, United States
| | - Ruth Ottman
- Department of Neurology, Columbia University Irving Medical Center, United States; The Gertrude H. Sergievsky Center, Columbia University Vagelos College of Physicians and Surgeons, United States; Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, United States; Division of Translational Epidemiology, New York State Psychiatric Institute, United States
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, United States
| | - Hyunmi Choi
- Department of Neurology, Columbia University Irving Medical Center, United States
| | - Brett E Youngerman
- Department of Neurological Surgery, Columbia University Irving Medical Center, United States.
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Natarajan K, Prasad N, Dascomb K, Irving SA, Yang DH, Gaglani M, Klein NP, DeSilva MB, Ong TC, Grannis SJ, Stenehjem E, Link-Gelles R, Rowley EA, Naleway AL, Han J, Raiyani C, Benitez GV, Rao S, Lewis N, Fadel WF, Grisel N, Griggs EP, Dunne MM, Stockwell MS, Mamawala M, McEvoy C, Barron MA, Goddard K, Valvi NR, Arndorfer J, Patel P, Mitchell PK, Smith M, Kharbanda AB, Fireman B, Embi PJ, Dickerson M, Davis JM, Zerbo O, Dalton AF, Wondimu MH, Azziz-Baumgartner E, Bozio CH, Reynolds S, Ferdinands J, Williams J, Schrag SJ, Verani JR, Ball S, Thompson MG, Dixon BE. Effectiveness of Homologous and Heterologous COVID-19 Booster Doses Following 1 Ad.26.COV2.S (Janssen [Johnson & Johnson]) Vaccine Dose Against COVID-19-Associated Emergency Department and Urgent Care Encounters and Hospitalizations Among Adults - VISION Network, 10 States, December 2021-March 2022. MMWR Morb Mortal Wkly Rep 2022; 71:495-502. [PMID: 35358170 PMCID: PMC8979598 DOI: 10.15585/mmwr.mm7113e2] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
CDC recommends that all persons aged ≥18 years receive a single COVID-19 vaccine booster dose ≥2 months after receipt of an Ad.26.COV2.S (Janssen [Johnson & Johnson]) adenovirus vector-based primary series vaccine; a heterologous COVID-19 mRNA vaccine is preferred over a homologous (matching) Janssen vaccine for booster vaccination. This recommendation was made in light of the risks for rare but serious adverse events following receipt of a Janssen vaccine, including thrombosis with thrombocytopenia syndrome and Guillain-Barré syndrome† (1), and clinical trial data indicating similar or higher neutralizing antibody response following heterologous boosting compared with homologous boosting (2). Data on real-world vaccine effectiveness (VE) of different booster strategies following a primary Janssen vaccine dose are limited, particularly during the period of Omicron variant predominance. The VISION Network§ determined real-world VE of 1 Janssen vaccine dose and 2 alternative booster dose strategies: 1) a homologous booster (i.e., 2 Janssen doses) and 2) a heterologous mRNA booster (i.e., 1 Janssen dose/1 mRNA dose). In addition, VE of these booster strategies was compared with VE of a homologous booster following mRNA primary series vaccination (i.e., 3 mRNA doses). The study examined 80,287 emergency department/urgent care (ED/UC) visits¶ and 25,244 hospitalizations across 10 states during December 16, 2021-March 7, 2022, when Omicron was the predominant circulating variant.** VE against laboratory-confirmed COVID-19-associated ED/UC encounters was 24% after 1 Janssen dose, 54% after 2 Janssen doses, 79% after 1 Janssen/1 mRNA dose, and 83% after 3 mRNA doses. VE for the same vaccination strategies against laboratory-confirmed COVID-19-associated hospitalizations were 31%, 67%, 78%, and 90%, respectively. All booster strategies provided higher protection than a single Janssen dose against ED/UC visits and hospitalizations during Omicron variant predominance. Vaccination with 1 Janssen/1 mRNA dose provided higher protection than did 2 Janssen doses against COVID-19-associated ED/UC visits and was comparable to protection provided by 3 mRNA doses during the first 120 days after a booster dose. However, 3 mRNA doses provided higher protection against COVID-19-associated hospitalizations than did other booster strategies during the same time interval since booster dose. All adults who have received mRNA vaccines for their COVID-19 primary series vaccination should receive an mRNA booster dose when eligible. Adults who received a primary Janssen vaccine dose should preferentially receive a heterologous mRNA vaccine booster dose ≥2 months later, or a homologous Janssen vaccine booster dose if mRNA vaccine is contraindicated or unavailable. Further investigation of the durability of protection afforded by different booster strategies is warranted.
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Kostka K, Duarte-Salles T, Prats-Uribe A, Sena AG, Pistillo A, Khalid S, Lai LYH, Golozar A, Alshammari TM, Dawoud DM, Nyberg F, Wilcox AB, Andryc A, Williams A, Ostropolets A, Areia C, Jung CY, Harle CA, Reich CG, Blacketer C, Morales DR, Dorr DA, Burn E, Roel E, Tan EH, Minty E, DeFalco F, de Maeztu G, Lipori G, Alghoul H, Zhu H, Thomas JA, Bian J, Park J, Martínez Roldán J, Posada JD, Banda JM, Horcajada JP, Kohler J, Shah K, Natarajan K, Lynch KE, Liu L, Schilling LM, Recalde M, Spotnitz M, Gong M, Matheny ME, Valveny N, Weiskopf NG, Shah N, Alser O, Casajust P, Park RW, Schuff R, Seager S, DuVall SL, You SC, Song S, Fernández-Bertolín S, Fortin S, Magoc T, Falconer T, Subbian V, Huser V, Ahmed WUR, Carter W, Guan Y, Galvan Y, He X, Rijnbeek PR, Hripcsak G, Ryan PB, Suchard MA, Prieto-Alhambra D. Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS. Clin Epidemiol 2022; 14:369-384. [PMID: 35345821 PMCID: PMC8957305 DOI: 10.2147/clep.s323292] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 01/27/2022] [Indexed: 01/20/2023] Open
Abstract
Purpose Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. Patients and Methods We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. Results We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. Conclusion We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.
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Affiliation(s)
- Kristin Kostka
- IQVIA, Cambridge, MA, USA
- OHDSI Center at The Roux Institute, Northeastern University, Portland, ME, USA
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK
| | - Anthony G Sena
- Janssen Research & Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Andrea Pistillo
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Sara Khalid
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK
| | - Lana Y H Lai
- School of Medical Sciences, University of Manchester, Manchester, UK
| | - Asieh Golozar
- Regeneron Pharmaceuticals, Tarrytown, NY, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Dalia M Dawoud
- National Institute for Health and Care Excellence, London, UK
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Adam B Wilcox
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
- Unviersity of Washington Medicine, Seattle, WA, USA
| | - Alan Andryc
- Janssen Research & Development, Titusville, NJ, USA
| | - Andrew Williams
- Tufts Institute for Clinical Research and Health Policy Studies, Boston, MA, USA
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Chi Young Jung
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Daegu Catholic University Medical Center, Daegu, South Korea
| | | | - Christian G Reich
- IQVIA, Cambridge, MA, USA
- OHDSI Center at The Roux Institute, Northeastern University, Portland, ME, USA
| | - Clair Blacketer
- Janssen Research & Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, Dundee, UK
| | - David A Dorr
- Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Edward Burn
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK
| | - Elena Roel
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Eng Hooi Tan
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK
| | - Evan Minty
- O’Brien Institute for Public Health, Faculty of Medicine, University of Calgary, Calgary, Canada
| | | | | | - Gigi Lipori
- University of Florida Health, Gainesville, FL, USA
| | - Hiba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine
| | - Hong Zhu
- Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China
| | - Jason A Thomas
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA
| | - Jiang Bian
- University of Florida Health, Gainesville, FL, USA
| | - Jimyung Park
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea
| | - Jordi Martínez Roldán
- Director of Innovation and Digital Transformation, Hospital del Mar, Barcelona, Spain
| | - Jose D Posada
- Department of Medicine, School of Medicine, Stanford University, Redwood City, CA, USA
| | - Juan M Banda
- Georgia State University, Department of Computer Science, Atlanta, GA, USA
| | - Juan P Horcajada
- Department of Infectious Diseases, Hospital del Mar, Institut Hospital del Mar d’Investigació Mèdica (IMIM), Universitat Autònoma de Barcelona, Universitat Pompeu Fabra, Barcelona, Spain
| | - Julianna Kohler
- United States Agency for International Development, Washington, DC, USA
| | - Karishma Shah
- Botnar Research Centre, NDORMS, University of Oxford, Oxford, UK
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Kristine E Lynch
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Li Liu
- Biomedical Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China
| | - Lisa M Schilling
- Data Science to Patient Value Program, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Martina Recalde
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Mengchun Gong
- Institute of Health Management, Southern Medical University, Guangzhou, People’s Republic of China
| | - Michael E Matheny
- Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Nicole G Weiskopf
- Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Nigam Shah
- Department of Medicine, School of Medicine, Stanford University, Redwood City, CA, USA
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Rae Woong Park
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea
| | - Robert Schuff
- Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | | | - Scott L DuVall
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Seng Chan You
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Seokyoung Song
- Department of Anesthesiology and Pain Medicine, Catholic University of Daegu, School of Medicine, Daegu, South Korea
| | - Sergio Fernández-Bertolín
- Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | | | - Tanja Magoc
- University of Florida Health, Gainesville, FL, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Vignesh Subbian
- College of Engineering, The University of Arizona, Tucson, AZ, USA
| | - Vojtech Huser
- National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Waheed-Ul-Rahman Ahmed
- Botnar Research Centre, NDORMS, University of Oxford, Oxford, UK
- College of Medicine and Health, University of Exeter, St Luke’s Campus, Exeter, UK
| | - William Carter
- Data Science to Patient Value Program, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Yin Guan
- DHC Technologies Co. Ltd., Beijing, People’s Republic of China
| | | | - Xing He
- University of Florida Health, Gainesville, FL, USA
| | - Peter R Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Patrick B Ryan
- Janssen Research & Development, Titusville, NJ, USA
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Marc A Suchard
- Departments of Biostatistics, Computational Medicine, and Human Genetics, University of California, Los Angeles, CA, USA
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Klein NP, Stockwell MS, Demarco M, Gaglani M, Kharbanda AB, Irving SA, Rao S, Grannis SJ, Dascomb K, Murthy K, Rowley EA, Dalton AF, DeSilva MB, Dixon BE, Natarajan K, Stenehjem E, Naleway AL, Lewis N, Ong TC, Patel P, Konatham D, Embi PJ, Reese SE, Han J, Grisel N, Goddard K, Barron MA, Dickerson M, Liao IC, Fadel WF, Yang DH, Arndorfer J, Fireman B, Griggs EP, Valvi NR, Hallowell C, Zerbo O, Reynolds S, Ferdinands J, Wondimu MH, Williams J, Bozio CH, Link-Gelles R, Azziz-Baumgartner E, Schrag SJ, Thompson MG, Verani JR. Effectiveness of COVID-19 Pfizer-BioNTech BNT162b2 mRNA Vaccination in Preventing COVID-19-Associated Emergency Department and Urgent Care Encounters and Hospitalizations Among Nonimmunocompromised Children and Adolescents Aged 5-17 Years - VISION Network, 10 States, April 2021-January 2022. MMWR Morb Mortal Wkly Rep 2022; 71:352-358. [PMID: 35239634 PMCID: PMC8893336 DOI: 10.15585/mmwr.mm7109e3] [Citation(s) in RCA: 109] [Impact Index Per Article: 54.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
The efficacy of the BNT162b2 (Pfizer-BioNTech) vaccine against laboratory-confirmed COVID-19 exceeded 90% in clinical trials that included children and adolescents aged 5-11, 12-15, and 16-17 years (1-3). Limited real-world data on 2-dose mRNA vaccine effectiveness (VE) in persons aged 12-17 years (referred to as adolescents in this report) have also indicated high levels of protection against SARS-CoV-2 (the virus that causes COVID-19) infection and COVID-19-associated hospitalization (4-6); however, data on VE against the SARS-CoV-2 B.1.1.529 (Omicron) variant and duration of protection are limited. Pfizer-BioNTech VE data are not available for children aged 5-11 years. In partnership with CDC, the VISION Network* examined 39,217 emergency department (ED) and urgent care (UC) encounters and 1,699 hospitalizations† among persons aged 5-17 years with COVID-19-like illness across 10 states during April 9, 2021-January 29, 2022,§ to estimate VE using a case-control test-negative design. Among children aged 5-11 years, VE against laboratory-confirmed COVID-19-associated ED and UC encounters 14-67 days after dose 2 (the longest interval after dose 2 in this age group) was 46%. Among adolescents aged 12-15 and 16-17 years, VE 14-149 days after dose 2 was 83% and 76%, respectively; VE ≥150 days after dose 2 was 38% and 46%, respectively. Among adolescents aged 16-17 years, VE increased to 86% ≥7 days after dose 3 (booster dose). VE against COVID-19-associated ED and UC encounters was substantially lower during the Omicron predominant period than the B.1.617.2 (Delta) predominant period among adolescents aged 12-17 years, with no significant protection ≥150 days after dose 2 during Omicron predominance. However, in adolescents aged 16-17 years, VE during the Omicron predominant period increased to 81% ≥7 days after a third booster dose. During the full study period, including pre-Delta, Delta, and Omicron predominant periods, VE against laboratory-confirmed COVID-19-associated hospitalization among children aged 5-11 years was 74% 14-67 days after dose 2, with wide CIs that included zero. Among adolescents aged 12-15 and 16-17 years, VE 14-149 days after dose 2 was 92% and 94%, respectively; VE ≥150 days after dose 2 was 73% and 88%, respectively. All eligible children and adolescents should remain up to date with recommended COVID-19 vaccinations, including a booster dose for those aged 12-17 years.
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Ferdinands JM, Rao S, Dixon BE, Mitchell PK, DeSilva MB, Irving SA, Lewis N, Natarajan K, Stenehjem E, Grannis SJ, Han J, McEvoy C, Ong TC, Naleway AL, Reese SE, Embi PJ, Dascomb K, Klein NP, Griggs EP, Konatham D, Kharbanda AB, Yang DH, Fadel WF, Grisel N, Goddard K, Patel P, Liao IC, Birch R, Valvi NR, Reynolds S, Arndorfer J, Zerbo O, Dickerson M, Murthy K, Williams J, Bozio CH, Blanton L, Verani JR, Schrag SJ, Dalton AF, Wondimu MH, Link-Gelles R, Azziz-Baumgartner E, Barron MA, Gaglani M, Thompson MG, Fireman B. Waning 2-Dose and 3-Dose Effectiveness of mRNA Vaccines Against COVID-19-Associated Emergency Department and Urgent Care Encounters and Hospitalizations Among Adults During Periods of Delta and Omicron Variant Predominance - VISION Network, 10 States, August 2021-January 2022. MMWR Morb Mortal Wkly Rep 2022. [PMID: 35176007 DOI: 10.1558/mmwr.mm7107e2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 03/14/2023]
Abstract
CDC recommends that all persons aged ≥12 years receive a booster dose of COVID-19 mRNA vaccine ≥5 months after completion of a primary mRNA vaccination series and that immunocompromised persons receive a third primary dose.* Waning of vaccine protection after 2 doses of mRNA vaccine has been observed during the period of the SARS-CoV-2 B.1.617.2 (Delta) variant predominance† (1-5), but little is known about durability of protection after 3 doses during periods of Delta or SARS-CoV-2 B.1.1.529 (Omicron) variant predominance. A test-negative case-control study design using data from eight VISION Network sites§ examined vaccine effectiveness (VE) against COVID-19 emergency department/urgent care (ED/UC) visits and hospitalizations among U.S. adults aged ≥18 years at various time points after receipt of a second or third vaccine dose during two periods: Delta variant predominance and Omicron variant predominance (i.e., periods when each variant accounted for ≥50% of sequenced isolates).¶ Persons categorized as having received 3 doses included those who received a third dose in a primary series or a booster dose after a 2 dose primary series (including the reduced-dosage Moderna booster). The VISION Network analyzed 241,204 ED/UC encounters** and 93,408 hospitalizations across 10 states during August 26, 2021-January 22, 2022. VE after receipt of both 2 and 3 doses was lower during the Omicron-predominant than during the Delta-predominant period at all time points evaluated. During both periods, VE after receipt of a third dose was higher than that after a second dose; however, VE waned with increasing time since vaccination. During the Omicron period, VE against ED/UC visits was 87% during the first 2 months after a third dose and decreased to 66% among those vaccinated 4-5 months earlier; VE against hospitalizations was 91% during the first 2 months following a third dose and decreased to 78% ≥4 months after a third dose. For both Delta- and Omicron-predominant periods, VE was generally higher for protection against hospitalizations than against ED/UC visits. All eligible persons should remain up to date with recommended COVID-19 vaccinations to best protect against COVID-19-associated hospitalizations and ED/UC visits.
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Ferdinands JM, Rao S, Dixon BE, Mitchell PK, DeSilva MB, Irving SA, Lewis N, Natarajan K, Stenehjem E, Grannis SJ, Han J, McEvoy C, Ong TC, Naleway AL, Reese SE, Embi PJ, Dascomb K, Klein NP, Griggs EP, Konatham D, Kharbanda AB, Yang DH, Fadel WF, Grisel N, Goddard K, Patel P, Liao IC, Birch R, Valvi NR, Reynolds S, Arndorfer J, Zerbo O, Dickerson M, Murthy K, Williams J, Bozio CH, Blanton L, Verani JR, Schrag SJ, Dalton AF, Wondimu MH, Link-Gelles R, Azziz-Baumgartner E, Barron MA, Gaglani M, Thompson MG, Fireman B. Waning 2-Dose and 3-Dose Effectiveness of mRNA Vaccines Against COVID-19-Associated Emergency Department and Urgent Care Encounters and Hospitalizations Among Adults During Periods of Delta and Omicron Variant Predominance - VISION Network, 10 States, August 2021-January 2022. MMWR Morb Mortal Wkly Rep 2022; 71:255-263. [PMID: 35176007 PMCID: PMC8853475 DOI: 10.15585/mmwr.mm7107e2] [Citation(s) in RCA: 258] [Impact Index Per Article: 129.0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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