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Duh-Leong C, Perrin EM, Heerman WJ, Schildcrout JS, Wallace S, Mendelsohn AL, Lee DC, Flower KB, Sanders LM, Rothman RL, Delamater AM, Gross RS, Wood C, Yin HS. Prenatal Risks to Healthy Food Access and High Birthweight Outcomes. Acad Pediatr 2024; 24:613-618. [PMID: 37659601 PMCID: PMC10904668 DOI: 10.1016/j.acap.2023.08.017] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 08/22/2023] [Accepted: 08/25/2023] [Indexed: 09/04/2023]
Abstract
OBJECTIVE Infants with high birthweight have increased risk for adverse outcomes at birth and across childhood. Prenatal risks to healthy food access may increase odds of high birthweight. We tested whether having a poor neighborhood food environment and/or food insecurity had associations with high birthweight. METHODS We analyzed cross-sectional baseline data in Greenlight Plus, an obesity prevention trial across six US cities (n = 787), which included newborns with a gestational age greater than 34 weeks and a birthweight greater than 2500 g. We assessed neighborhood food environment using the Place-Based Survey and food insecurity using the US Household Food Security Module. We performed logistic regression analyses to assess the individual and additive effects of risk factors on high birthweight. We adjusted for potential confounders: infant sex, race, ethnicity, gestational age, birthing parent age, education, income, and study site. RESULTS Thirty-four percent of birthing parents reported poor neighborhood food environment and/or food insecurity. Compared to those without food insecurity, food insecure families had greater odds of delivering an infant with high birthweight (adjusted odds ratios [aOR] 1.96, 95% confidence intervals [CI]: 1.01, 3.82) after adjusting for poor neighborhood food environment, which was not associated with high birthweight (aOR 1.35, 95% CI: 0.78, 2.34). Each additional risk to healthy food access was associated with a 56% (95% CI: 4%-132%) increase in high birthweight odds. CONCLUSIONS Prenatal risks to healthy food access may increase high infant birthweight odds. Future studies designed to measure neighborhood factors should examine infant birthweight outcomes in the context of prenatal social determinants of health.
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Affiliation(s)
- Carol Duh-Leong
- NYU Grossman School of Medicine (C Duh-Leong, RS Gross, and HS Yin), Division of General Pediatrics, Department of Pediatrics, New York, NY.
| | - Eliana M Perrin
- Johns Hopkins University (EM Perrin), Division of General Pediatrics, Department of Pediatrics, Schools of Medicine and Nursing, Baltimore, Md
| | - William J Heerman
- Vanderbilt University Medical Center (WJ Heerman and S Wallace), Department of Pediatrics, Nashville, Tenn
| | - Jonathan S Schildcrout
- Vanderbilt University Medical Center (JS Schildcrout), Department of Biostatistics, Nashville, Tenn
| | - Shelby Wallace
- Vanderbilt University Medical Center (WJ Heerman and S Wallace), Department of Pediatrics, Nashville, Tenn
| | - Alan L Mendelsohn
- NYU Grossman School of Medicine (AL Mendelsohn), Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, New York, NY
| | - David C Lee
- Ronald O. Perelman Department of Emergency Medicine (DC Lee), NYU Grossman School of Medicine, New York, NY
| | - Kori B Flower
- University of North Carolina at Chapel Hill (KB Flower), Division of General Pediatrics and Adolescent Medicine, UNC School of Medicine, Chapel Hill, NC
| | - Lee M Sanders
- Stanford University School of Medicine (LM Sanders), Division of General Pediatrics, Palo Alto, Calif
| | - Russell L Rothman
- Vanderbilt University Medical Center (RL Rothman), Institute of Medicine and Public Health, Nashville, Tenn
| | - Alan M Delamater
- University of Miami Miller School of Medicine (AM Delamater), Department of Pediatrics, Miami, Fla
| | - Rachel S Gross
- NYU Grossman School of Medicine (C Duh-Leong, RS Gross, and HS Yin), Division of General Pediatrics, Department of Pediatrics, New York, NY
| | - Charles Wood
- Duke University School of Medicine (C Wood), Department of Pediatrics, Division of General Pediatrics and Adolescent Health, Durham, NC
| | - Hsiang Shonna Yin
- NYU Grossman School of Medicine (C Duh-Leong, RS Gross, and HS Yin), Division of General Pediatrics, Department of Pediatrics, New York, NY
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Rummo PE, Kanchi R, Adhikari S, Titus AR, Lee DC, McAlexander T, Thorpe LE, Elbel B. Influence of the food environment on obesity risk in a large cohort of US veterans by community type. Obesity (Silver Spring) 2024; 32:788-797. [PMID: 38298108 DOI: 10.1002/oby.23975] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/30/2023] [Accepted: 12/01/2023] [Indexed: 02/02/2024]
Abstract
OBJECTIVE The aim of this study was to examine relationships between the food environment and obesity by community type. METHODS Using electronic health record data from the US Veterans Administration Diabetes Risk (VADR) cohort, we examined associations between the percentage of supermarkets and fast-food restaurants with obesity prevalence from 2008 to 2018. We constructed multivariable logistic regression models with random effects and interaction terms for year and food environment variables. We stratified models by community type. RESULTS Mean age at baseline was 59.8 (SD = 16.1) years; 93.3% identified as men; and 2,102,542 (41.8%) were classified as having obesity. The association between the percentage of fast-food restaurants and obesity was positive in high-density urban areas (odds ratio [OR] = 1.033; 95% CI: 1.028-1.037), with no interaction by time (p = 0.83). The interaction with year was significant in other community types (p < 0.001), with increasing odds of obesity in each follow-up year. The associations between the percentage of supermarkets and obesity were null in high-density and low-density urban areas and positive in suburban (OR = 1.033; 95% CI: 1.027-1.039) and rural (OR = 1.007; 95% CI: 1.002-1.012) areas, with no interactions by time. CONCLUSIONS Many healthy eating policies have been passed in urban areas; our results suggest such policies might also mitigate obesity risk in nonurban areas.
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Affiliation(s)
- Pasquale E Rummo
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Rania Kanchi
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Samrachana Adhikari
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Andrea R Titus
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - David C Lee
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
- Department of Emergency Medicine, NYU Langone Health, New York, New York, USA
| | - Tara McAlexander
- Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, USA
| | - Lorna E Thorpe
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Brian Elbel
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
- NYU Wagner Graduate School of Public Service, New York, New York, USA
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Hirsch AG, Conderino S, Crume TL, Liese AD, Bellatorre A, Bendik S, Divers J, Anthopolos R, Dixon BE, Guo Y, Imperatore G, Lee DC, Reynolds K, Rosenman M, Shao H, Utidjian L, Thorpe LE. Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network. BMJ Open 2024; 14:e073791. [PMID: 38233060 PMCID: PMC10806714 DOI: 10.1136/bmjopen-2023-073791] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 12/20/2023] [Indexed: 01/19/2024] Open
Abstract
INTRODUCTION Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved. METHODS AND ANALYSIS The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression. ETHICS AND DISSEMINATION The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.
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Affiliation(s)
- Annemarie G Hirsch
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania, USA
| | - Sarah Conderino
- Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA
| | - Tessa L Crume
- Department of Epidemiology, Lifecourse Epidemiology of Adiposity and Diabetes (LEAD), University of Colorado - Anschutz Medical Campus, Aurora, Colorado, USA
| | - Angela D Liese
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, South Carolina, USA
| | - Anna Bellatorre
- Department of Epidemiology, Lifecourse Epidemiology of Adiposity and Diabetes (LEAD), University of Colorado - Anschutz Medical Campus, Aurora, Colorado, USA
| | - Stefanie Bendik
- Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA
| | - Jasmin Divers
- Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, New York, USA
| | - Rebecca Anthopolos
- Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA
| | - Brian E Dixon
- Department of Epidemiology, Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, USA
- Center for Biomedical Informatics, Regenstrief Institute Inc, Indianapolis, Indiana, USA
| | - Yi Guo
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, Florida, USA
| | - Giuseppina Imperatore
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - David C Lee
- Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA
| | - Kristi Reynolds
- Departmnt of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Marc Rosenman
- Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, and Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Hui Shao
- Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, Florida, USA
| | - Levon Utidjian
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Lorna E Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA
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Rony M, Quintero-Arias C, Osorio M, Ararso Y, Norman EM, Ravenell JE, Wall SP, Lee DC. Perceptions of the Healthcare System Among Black Men with Previously Undiagnosed Diabetes and Prediabetes. J Racial Ethn Health Disparities 2023; 10:3150-3158. [PMID: 36520369 PMCID: PMC10267290 DOI: 10.1007/s40615-022-01488-z] [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: 09/27/2022] [Revised: 11/29/2022] [Accepted: 12/02/2022] [Indexed: 12/23/2022]
Abstract
OBJECTIVE Given the significant disparities in diabetes burden and access to care, this study uses qualitative interviews of Black men having HbA1c levels consistent with previously undiagnosed diabetes or prediabetes to understand their perceptions of the healthcare system. RESEARCH DESIGN AND METHODS We recruited Black men from Black-owned barbershops in Brooklyn, NY, who were screened using point-of-care HbA1c tests. Among those with HbA1c levels within prediabetes or diabetes thresholds, qualitative interviews were conducted to uncover prevalent themes related to their overall health status, health behaviors, utilization of healthcare services, and experiences with the healthcare system. We used a theoretical framework from the William and Mohammed medical mistrust model to guide our qualitative analysis. RESULTS Fifty-two Black men without a prior history of diabetes and an HbA1c reading at or above 5.7% were interviewed. Many participants stated that their health was in good condition. Some participants expressed being surprised by their abnormal HbA1c reading because it was not previously mentioned by their healthcare providers. Furthermore, many of our participants shared recent examples of negative interactions with physicians when describing their experiences with the healthcare system. Finally, several participants cited a preference for incorporating non-pharmaceutical options in their diabetes management plans. CONCLUSION To help alleviate the disparity in diabetes burden among Black men, healthcare providers should take a more active role in recognizing and addressing their own implicit biases, engage in understanding the specific healthcare needs and expectations of each patient, and consider emphasizing non-medication approaches to improve glycemic control.
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Affiliation(s)
- Melissa Rony
- Department of Emergency Medicine, NYU School of Medicine, New York, NY, 10016, USA
| | | | - Marcela Osorio
- Department of Emergency Medicine, NYU School of Medicine, New York, NY, 10016, USA
| | - Yonathan Ararso
- Department of Emergency Medicine, NYU School of Medicine, New York, NY, 10016, USA
| | - Elizabeth M Norman
- Steinhardt School of Culture, Education, and Human Development, New York University, New York, NY, 10003, USA
| | - Joseph E Ravenell
- Department of Population Health, NYU School of Medicine, New York, NY, 10016, USA
| | - Stephen P Wall
- Department of Emergency Medicine, NYU School of Medicine, New York, NY, 10016, USA
- Department of Population Health, NYU School of Medicine, New York, NY, 10016, USA
| | - David C Lee
- Department of Emergency Medicine, NYU School of Medicine, New York, NY, 10016, USA.
- Department of Population Health, NYU School of Medicine, New York, NY, 10016, USA.
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Lin JK, Hearn CM, Getzen E, Long Q, Lee DC, Keaveny TM, Jayadevappa R, Robinson KW, Wong YN, Maxwell KN, Narayan V, Haas NB, Takvorian SU, Bikle DD, Chiang JM, Khan AN, Rajapakse CS, Morgans AK, Parikh RB. Validation of Biomechanical Computed Tomography for Fracture Risk Classification in Metastatic Hormone-sensitive Prostate Cancer. Eur Urol Oncol 2023:S2588-9311(23)00230-4. [PMID: 37926618 DOI: 10.1016/j.euo.2023.10.016] [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: 06/12/2023] [Revised: 10/09/2023] [Accepted: 10/20/2023] [Indexed: 11/07/2023]
Abstract
BACKGROUND Guidelines recommend dual-energy x-ray absorptiometry (DXA) screening to assess fracture risk and benefit from antiresorptive therapy in men with metastatic hormone-sensitive prostate cancer (mHSPC) on androgen deprivation therapy (ADT). However, <30% of eligible patients undergo DXA screening. Biomechanical computed tomography (BCT) is a radiomic technique that measures bone mineral density (BMD) and bone strength from computed tomography (CT) scans. OBJECTIVE To evaluate the (1) correlations between BCT- and DXA-assessed BMD, and (2) associations between BCT-assessed metrics and subsequent fracture. DESIGN, SETTING, AND PARTICIPANTS A multicenter retrospective cohort study was conducted among patients with mHSPC between 2013 and 2020 who received CT abdomen/pelvis or positron emission tomography/CT within 48 wk before ADT initiation and during follow-up (48-96 wk after ADT initiation). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS We used univariate logistic regression to assess the associations between BCT measurements and the primary outcomes of subsequent pathologic and nonpathologic fractures. RESULTS AND LIMITATIONS Among 91 eligible patients, the median ([interquartile range) age was 67 yr (62-75), 44 (48.4%) were White, and 41 (45.1%) were Black. During the median follow-up of 82 wk, 17 men (18.6%) developed a pathologic and 15 (16.5%) a nonpathologic fracture. BCT- and DXA-assessed femoral-neck BMD T scores were strongly correlated (R2 = 0.93). On baseline CT, lower BCT-assessed BMD (odds ratio [OR] 1.80, 95% confidence interval or CI [1.10, 3.25], p = 0.03) was associated with an increased risk of a pathologic fracture. Lower femoral strength (OR 1.63, 95% CI [0.99, 2.71], p = 0.06) was marginally associated with an increased risk of a pathologic fracture. Neither BMD (OR 1.52, 95% CI [0.95, 2.63], p = 0.11) nor strength (OR 1.14, 95% CI [0.75, 1.80], p = 0.57) was associated with a nonpathologic fracture. BCT identified nine (9.9%) men eligible for antiresorptive therapy, of whom four (44%) were not treated. Limitations include low fracture numbers resulting in lower power to detect fracture associations. CONCLUSIONS Among men diagnosed with mHSPC, BCT assessments were strongly correlated with DXA, predicted subsequent pathologic fracture, and identified additional men indicated for antiresorptive therapy. PATIENT SUMMARY We assess whether biomechanical computer tomography (BCT) from routine computer tomography (CT) scans can identify fracture risk among patients recently diagnosed with metastatic prostate cancer. We find that BCT and dual-energy x-ray absorptiometry-derived bone mineral density are strongly correlated and that BCT accurately identifies the risk for future fracture. BCT may enable broader fracture risk assessment and facilitate timely interventions to reduce fracture risk in metastatic prostate cancer patients.
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Affiliation(s)
- John K Lin
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Caleb M Hearn
- Division of Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Center for Cancer Care Innovation, Abramson Cancer Center, Philadelphia, PA, USA
| | - Emily Getzen
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Qi Long
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Tony M Keaveny
- O.N. Diagnostics, Berkeley, CA, USA; University of California, Berkeley, Berkeley, CA, USA
| | - Ravishankar Jayadevappa
- Department of Geriatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kyle W Robinson
- Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Yu-Ning Wong
- Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Kara N Maxwell
- Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Vivek Narayan
- Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Naomi B Haas
- Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Samuel U Takvorian
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Philadelphia, PA, USA; Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel D Bikle
- University of California, San Francisco, San Francisco, CA, USA
| | - Janet M Chiang
- University of California, San Francisco, San Francisco, CA, USA
| | - Amna N Khan
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA; Division of Endocrinology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chamith S Rajapakse
- Departments of Radiology and Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Ravi B Parikh
- Division of Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Center for Cancer Care Innovation, Abramson Cancer Center, Philadelphia, PA, USA; Division of Hematology and Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA.
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Lee DC, Orstad SL, Kanchi R, Adhikari S, Rummo PE, Titus AR, Aleman JO, Elbel B, Thorpe LE, Schwartz MD. Demographic, social and geographic factors associated with glycaemic control among US Veterans with new onset type 2 diabetes: a retrospective cohort study. BMJ Open 2023; 13:e075599. [PMID: 37832984 PMCID: PMC10582880 DOI: 10.1136/bmjopen-2023-075599] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 09/07/2023] [Indexed: 10/15/2023] Open
Abstract
OBJECTIVES This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes. DESIGN, SETTING AND PARTICIPANTS We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes. PRIMARY OUTCOME AND METHODS We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas. RESULTS We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.
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Affiliation(s)
- David C Lee
- Emergency Medicine, NYU Grossman School of Medicine, New York City, New York, USA
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
| | - Stephanie L Orstad
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
- Medicine, NYU Grossman School of Medicine, New York City, New York, USA
| | - Rania Kanchi
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
| | - Samrachana Adhikari
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
| | - Pasquale E Rummo
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
| | - Andrea R Titus
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
| | - Jose O Aleman
- Medicine, NYU Grossman School of Medicine, New York City, New York, USA
- Veterans Affairs, VA New York Harbor Healthcare System, New York City, New York, USA
| | - Brian Elbel
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
- Wagner Graduate School of Public Service, NYU, New York City, New York, USA
| | - Lorna E Thorpe
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
| | - Mark D Schwartz
- Population Health, NYU Grossman School of Medicine, New York City, New York, USA
- Veterans Affairs, VA New York Harbor Healthcare System, New York City, New York, USA
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Elbel B, Heng L, Konty KJ, Day SE, Rothbart MW, Abrams C, Lee DC, Thorpe LE, Ellen Schwartz A. COVID-19 vaccines for children: Racial and ethnic disparities in New York City. Prev Med Rep 2023; 35:102357. [PMID: 37593357 PMCID: PMC10428028 DOI: 10.1016/j.pmedr.2023.102357] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 07/07/2023] [Accepted: 07/31/2023] [Indexed: 08/19/2023] Open
Abstract
Vaccination is an indispensable tool to reduce negative outcomes due to COVID-19. Although COVID-19 disproportionately affected lower income and Black and Hispanic communities, these groups have had lower population-level uptake of vaccines. Using detailed cross-sectional data, we examined racial and ethnic group differences in New York City schoolchildren becoming fully vaccinated (two doses) within 6 months of vaccine eligibility. We matched school enrollment data to vaccination data in the Citywide Immunization Registry, a census of all vaccinations delivered in New York City. We used ordinary least squares regression models to predict fully vaccinated status, with key predictors of race and ethnicity using a variety of different control variables, including residential neighborhood or school fixed effects. We also stratified by borough and by age. The sample included all New York City public school students enrolled during the 2021-2022 school year. Asian students were most likely to be vaccinated and Black and White students least likely. Controlling for student characteristics, particularly residential neighborhood or school attended, diminished some of the race and ethnicity differences. Key differences were also present by borough, both overall and by racial and ethnic groups. In sum, racial and ethnic disparities in children's COVID-19 vaccination were present. Vaccination rates varied by the geographic unit of borough; controlling for neighborhood characteristics diminished some disparities by race and ethnicity. Neighborhood demographics and resources, and the attributes, culture and preferences of those who live there may affect vaccination decisions and could be targets of future efforts to increase vaccination rates.
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Affiliation(s)
- Brian Elbel
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
- New York University Wagner Graduate School of Public Service, New York, NY, USA
| | - Lloyd Heng
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Kevin J. Konty
- Bureau of School Health, New York City Department of Health and Mental Hygiene, New York, NY, USA
| | - Sophia E. Day
- Bureau of School Health, New York City Department of Health and Mental Hygiene, New York, NY, USA
| | | | - Courtney Abrams
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - David C. Lee
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
- Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Lorna E. Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Amy Ellen Schwartz
- Joseph R. Biden, Jr. School of Public Policy and Administration, University of Delaware, Newark, DE, USA
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Algur Y, Rummo PE, McAlexander TP, De Silva SSA, Lovasi GS, Judd SE, Ryan V, Malla G, Koyama AK, Lee DC, Thorpe LE, McClure LA. Assessing the association between food environment and dietary inflammation by community type: a cross-sectional REGARDS study. Int J Health Geogr 2023; 22:24. [PMID: 37730612 PMCID: PMC10510199 DOI: 10.1186/s12942-023-00345-4] [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: 03/29/2023] [Accepted: 09/06/2023] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors. OBJECTIVE This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US. METHODS Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003-2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together. RESULTS Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was - 0.004 (SD = 2.5; min = - 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas. CONCLUSIONS The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.
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Affiliation(s)
- Yasemin Algur
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA.
| | - Pasquale E Rummo
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Tara P McAlexander
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
| | - S Shanika A De Silva
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
| | - Gina S Lovasi
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
| | - Suzanne E Judd
- Department of Biostatistics, The University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Victoria Ryan
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
| | - Gargya Malla
- Department of Epidemiology, The University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Alain K Koyama
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - David C Lee
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
- Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Lorna E Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Leslie A McClure
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Nesbitt Hall, 3215 Market Street, Philadelphia, PA, 19104, USA
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Lee DC, Reddy H, Koziatek CA, Klein N, Chitnis A, Creary K, Francois G, Akindutire O, Femia R, Caldwell R. Expanding Diabetes Screening to Identify Undiagnosed Cases Among Emergency Department Patients. West J Emerg Med 2023; 24:962-966. [PMID: 37788038 PMCID: PMC10527841 DOI: 10.5811/westjem.59957] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 05/30/2023] [Accepted: 07/08/2023] [Indexed: 10/04/2023] Open
Abstract
Introduction: Diabetes screening traditionally occurs in primary care settings, but many who are at high risk face barriers to accessing care and therefore delays in diagnosis and treatment. These same high-risk patients do frequently visit emergency departments (ED) and, therefore, might benefit from screening at that time. Our objective in this study was to analyze one year of results from a multisite, ED-based diabetes screening program. Methods: We assessed the demographics of patients screened, identified differences in rates of newly diagnosed diabetes by clinical site, and the geographic distribution of high and low hemoglobin A1c (HbA1c) results. Results: We performed diabetes screening (HbA1c) among 4,211 ED patients 40-70 years old, with a body mass index ≥25, and no prior history of diabetes. Of these patients screened for diabetes, 9% had a HbA1c result consistent with undiagnosed diabetes, and nearly half of these patients had a HbA1c ≥9.0%. Rates of newly diagnosed diabetes were notably higher at EDs located in neighborhoods of lower socioeconomic status. Conclusion: Emergency department-based diabetes screening may be a practical and scalable solution to screen high-risk patients and reduce health disparities experienced in specific neighborhoods and demographic groups.
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Affiliation(s)
- David C Lee
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
- New York University, NYU Grossman School of Medicine, Department of Population Health, New York, New York
- Bellevue Hospital Center, Department of Emergency Medicine, New York, New York
| | - Harita Reddy
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Christian A Koziatek
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
- Bellevue Hospital Center, Department of Emergency Medicine, New York, New York
| | - Noah Klein
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Anup Chitnis
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Kashif Creary
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Gerard Francois
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Olumide Akindutire
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Robert Femia
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
- Bellevue Hospital Center, Department of Emergency Medicine, New York, New York
| | - Reed Caldwell
- New York University, NYU Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York,
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10
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Koziatek CA, Bohart I, Caldwell R, Swartz J, Rosen P, Desai S, Krol K, Neill DB, Lee DC. Neighborhood-Level Risk Factors for Severe Hyperglycemia among Emergency Department Patients without a Prior Diabetes Diagnosis. J Urban Health 2023; 100:802-810. [PMID: 37580543 PMCID: PMC10447789 DOI: 10.1007/s11524-023-00771-6] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/13/2023] [Indexed: 08/16/2023]
Abstract
A person's place of residence is a strong risk factor for important diagnosed chronic diseases such as diabetes. It is unclear whether neighborhood-level risk factors also predict the probability of undiagnosed disease. The objective of this study was to identify neighborhood-level variables associated with severe hyperglycemia among emergency department (ED) patients without a history of diabetes. We analyzed patients without previously diagnosed diabetes for whom a random serum glucose value was obtained in the ED. We defined random glucose values ≥ 200 mg/dL as severe hyperglycemia, indicating probable undiagnosed diabetes. Patient addresses were geocoded and matched with neighborhood-level socioeconomic measures from the American Community Survey and claims-based surveillance estimates of diabetes prevalence. Neighborhood-level exposure variables were standardized based on z-scores, and a series of logistic regression models were used to assess the association of selected exposures and hyperglycemia adjusting for biological and social individual-level risk factors for diabetes. Of 77,882 ED patients without a history of diabetes presenting in 2021, 1,715 (2.2%) had severe hyperglycemia. Many geospatial exposures were associated with uncontrolled hyperglycemia, even after controlling for individual-level risk factors. The most strongly associated neighborhood-level variables included lower markers of educational attainment, higher percentage of households where limited English is spoken, lower rates of white-collar employment, and higher rates of Medicaid insurance. Including these geospatial factors in risk assessment models may help identify important subgroups of patients with undiagnosed disease.
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Affiliation(s)
- Christian A Koziatek
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Isaac Bohart
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Reed Caldwell
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Jordan Swartz
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Perry Rosen
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Sagar Desai
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Katarzyna Krol
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Daniel B Neill
- Courant Institute of Mathematical Sciences, Department of Computer Science, New York University, New York, NY, USA
- Robert F. Wagner Graduate School of Public Service, New York University, New York, NY, USA
- Center for Urban Science and Progress, Tandon School of Engineering, New York University, New York, NY, USA
| | - David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA.
- Department of Population Health, New York University School of Medicine, New York, NY, USA.
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11
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Adhikari S, Titus AR, Baum A, Lopez P, Kanchi R, Orstad SL, Elbel B, Lee DC, Thorpe LE, Schwartz MD. Disparities in routine healthcare utilization disruptions during COVID-19 pandemic among veterans with type 2 diabetes. BMC Health Serv Res 2023; 23:41. [PMID: 36647113 PMCID: PMC9842402 DOI: 10.1186/s12913-023-09057-8] [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: 01/10/2023] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.
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Affiliation(s)
- Samrachana Adhikari
- Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, 4th Floor, #4-54, New York, NY, 10016, USA.
| | - Andrea R. Titus
- grid.137628.90000 0004 1936 8753Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, 4th Floor, #4-54, New York, NY 10016 USA
| | - Aaron Baum
- grid.59734.3c0000 0001 0670 2351Department of Global Health, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Priscilla Lopez
- grid.137628.90000 0004 1936 8753Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, 4th Floor, #4-54, New York, NY 10016 USA
| | - Rania Kanchi
- grid.137628.90000 0004 1936 8753Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, 4th Floor, #4-54, New York, NY 10016 USA
| | - Stephanie L. Orstad
- grid.137628.90000 0004 1936 8753Department of Medicine, New York University Grossman School of Medicine, New York, NY USA
| | - Brian Elbel
- grid.137628.90000 0004 1936 8753Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, 4th Floor, #4-54, New York, NY 10016 USA ,grid.137628.90000 0004 1936 8753Wagner Graduate School of Public Service, New York University, New York, NY USA
| | - David C. Lee
- grid.137628.90000 0004 1936 8753Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, 4th Floor, #4-54, New York, NY 10016 USA ,grid.137628.90000 0004 1936 8753Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, New York, NY USA
| | - Lorna E. Thorpe
- grid.137628.90000 0004 1936 8753Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, 4th Floor, #4-54, New York, NY 10016 USA
| | - Mark D. Schwartz
- grid.137628.90000 0004 1936 8753Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, 4th Floor, #4-54, New York, NY 10016 USA ,grid.413926.b0000 0004 0420 1627VA New York Harbor Healthcare System, New York, NY USA
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12
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Elbel B, Zhou GE, Lee DC, Chen W, Day SE, Konty KJ, Schwartz AE. Analysis of School-Level Vaccination Rates by Race, Ethnicity, and Geography in New York City. JAMA Netw Open 2022; 5:e2231849. [PMID: 36107432 PMCID: PMC9478775 DOI: 10.1001/jamanetworkopen.2022.31849] [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] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
This cross-sectional study of New York City school data examines differences in COVID-19 vaccination rates by race, ethnicity, and borough.
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Affiliation(s)
- Brian Elbel
- Department of Population Health, New York University Grossman School of Medicine, New York
- Wagner Graduate School of Public Service, New York University, New York
| | - Geng Eric Zhou
- Department of Population Health, New York University Grossman School of Medicine, New York
- Wagner Graduate School of Public Service, New York University, New York
| | - David C Lee
- Department of Emergency Medicine, New York University Grossman School of Medicine, New York
| | - Willy Chen
- Maxwell School, Syracuse University, Syracuse, New York
| | - Sophia E Day
- Bureau of School Health, New York City Department of Health and Mental Hygiene, New York
| | - Kevin J Konty
- Bureau of School Health, New York City Department of Health and Mental Hygiene, New York
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13
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McAlexander TP, Malla G, Uddin J, Lee DC, Schwartz BS, Rolka DB, Siegel KR, Kanchi R, Pollak J, Andes L, Carson AP, Thorpe LE, McClure LA. Urban and rural differences in new onset type 2 diabetes: Comparisons across national and regional samples in the diabetes LEAD network. SSM Popul Health 2022; 19:101161. [PMID: 35990409 PMCID: PMC9385670 DOI: 10.1016/j.ssmph.2022.101161] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [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: 02/14/2022] [Revised: 06/28/2022] [Accepted: 06/30/2022] [Indexed: 01/25/2023] Open
Abstract
Introduction Geographic disparities in diabetes burden exist throughout the United States (US), with many risk factors for diabetes clustering at a community or neighborhood level. We hypothesized that the likelihood of new onset type 2 diabetes (T2D) would differ by community type in three large study samples covering the US. Research design and methods We evaluated the likelihood of new onset T2D by a census tract-level measure of community type, a modification of RUCA designations (higher density urban, lower density urban, suburban/small town, and rural) in three longitudinal US study samples (REGARDS [REasons for Geographic and Racial Differences in Stroke] cohort, VADR [Veterans Affairs Diabetes Risk] cohort, Geisinger electronic health records) representing the CDC Diabetes LEAD (Location, Environmental Attributes, and Disparities) Network. Results In the REGARDS sample, residing in higher density urban community types was associated with the lowest odds of new onset T2D (OR [95% CI]: 0.80 [0.66, 0.97]) compared to rural community types; in the Geisinger sample, residing in higher density urban community types was associated with the highest odds of new onset T2D (OR [95% CI]: 1.20 [1.06, 1.35]) compared to rural community types. In the VADR sample, suburban/small town community types had the lowest hazard ratios of new onset T2D (HR [95% CI]: 0.99 [0.98, 1.00]). However, in a regional stratified analysis of the VADR sample, the likelihood of new onset T2D was consistent with findings in the REGARDS and Geisinger samples, with highest likelihood of T2D in the rural South and in the higher density urban communities of the Northeast and West regions; likelihood of T2D did not differ by community type in the Midwest. Conclusions The likelihood of new onset T2D by community type varied by region of the US. In the South, the likelihood of new onset T2D was higher among those residing in rural communities.
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Affiliation(s)
- Tara P. McAlexander
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA
| | - Gargya Malla
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jalal Uddin
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - David C. Lee
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
- Department of Emergency Medicine, NYU Grossman School of Medicine, New York, NY, USA
| | - Brian S. Schwartz
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Deborah B. Rolka
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Karen R. Siegel
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Rania Kanchi
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Jonathan Pollak
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Linda Andes
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39213, USA
| | - Lorna E. Thorpe
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | - Leslie A. McClure
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA
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14
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Thorpe LE, Adhikari S, Lopez P, Kanchi R, McClure LA, Hirsch AG, Howell CR, Zhu A, Alemi F, Rummo P, Ogburn EL, Algur Y, Nordberg CM, Poulsen MN, Long L, Carson AP, DeSilva SA, Meeker M, Schwartz BS, Lee DC, Siegel KR, Imperatore G, Elbel B. Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples. Diabetes Care 2022; 45:798-810. [PMID: 35104336 PMCID: PMC9016733 DOI: 10.2337/dc21-1693] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 01/05/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural. RESULTS Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways. CONCLUSIONS Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.
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Affiliation(s)
- Lorna E. Thorpe
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Samrachana Adhikari
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Priscilla Lopez
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Rania Kanchi
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Leslie A. McClure
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | | | - Carrie R. Howell
- Division of Preventive Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, AL
| | - Aowen Zhu
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - Farrokh Alemi
- Department of Health Administration and Policy, George Mason University, Fairfax, VA
| | - Pasquale Rummo
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
| | - Elizabeth L. Ogburn
- Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD
| | - Yasemin Algur
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Cara M. Nordberg
- Department of Population Health Sciences, Geisinger, Danville, PA
| | | | - Leann Long
- Department of Biostatistics, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - April P. Carson
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL
| | - Shanika A. DeSilva
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Melissa Meeker
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA
| | - Brian S. Schwartz
- Department of Population Health Sciences, Geisinger, Danville, PA
- Department of Environmental Health and Engineering, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD
| | - David C. Lee
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
- Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY
| | - Karen R. Siegel
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Giuseppina Imperatore
- Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA
| | - Brian Elbel
- Department of Population Health, New York University Grossman School of Medicine, New York, NY
- New York University Wagner Graduate School of Public Service, New York, NY
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15
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McAlexander TP, Algur Y, Schwartz BS, Rummo PE, Lee DC, Siegel KR, Ryan V, Lee NL, Malla G, McClure LA. Categorizing community type for epidemiologic evaluation of community factors and chronic disease across the United States. Soc Sci Humanit Open 2022; 5:100250. [PMID: 35369036 PMCID: PMC8974313 DOI: 10.1016/j.ssaho.2022.100250] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Existing classifications of community type do not differentiate urban cores from surrounding non-rural areas, an important distinction for analyses of community features and their impact on health. Inappropriately classified community types can introduce serious methodologic flaws in epidemiologic studies and invalid inferences from findings. To address this, we evaluate a modification of the United States Department of Agriculture's Rural Urban Commuting Area codes at the census tract, propose a four-level categorization of community type, and compare this with existing classifications for epidemiologic analyses. Compared to existing classifications, our method resulted in clearer geographic delineations of community types within urban areas.
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Affiliation(s)
- Tara P. McAlexander
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, Pennsylvania, United States
| | - Yasemin Algur
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, Pennsylvania, United States
| | - Brian S. Schwartz
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States
| | - Pasquale E. Rummo
- Department of Population Health, NYU School of Medicine, New York, New York, United States
| | - David C. Lee
- Department of Population Health, NYU School of Medicine, New York, New York, United States
- Department of Emergency Medicine, NYU School of Medicine, New York, New York, United States
| | - Karen R. Siegel
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Victoria Ryan
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, Pennsylvania, United States
| | - Nora L. Lee
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, Pennsylvania, United States
| | - Gargya Malla
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - Leslie A. McClure
- Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, Pennsylvania, United States
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16
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Jansen D, Dickstein DR, Erazo K, Stacom E, Lee DC, Wainwright SK. Hyperbaric oxygen for COVID-19 patients with severe hypoxia prior to vaccine availability. Undersea Hyperb Med 2022; 49:295-305. [PMID: 36001562 DOI: 10.22462/05.06.2022.3] [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
INTRODUCTION Few treatments have demonstrated mortality benefits among hospitalized hypoxic COVID-19 patients. We evaluated the use of hyperbaric oxygen (HBO2) therapy as a therapeutic intervention among hospitalized patients with a high oxygen requirement prior to vaccine approval. METHODS We extracted data on patients with COVID-19 hypoxia who required oxygen supplementation ranging from a 6L nasal cannula up to a high-flow nasal cannula at 100% FiO2 at 60L/minute with a 100% non-rebreather mask at 15 L/minute and were eligible for off-label HBO2 therapy from October 2020 to February 2021. We followed the Monitored Emergency use of Unregistered and Investigational Interventions or (MEURI) in conjunction with the consistent re-evaluation of the protocol using the Plan-Do-Study-Act (PDSA) tool [1]. We compared patient characteristics and used Fisher's exact test and a survival analysis to assess the primary endpoint of inpatient death. RESULTS HBO2 therapy was offered to 36 patients, of which 24 received treatment and 12 did not receive treatment. Patients who did not receive treatment were significantly older (p ≺ 0.01) and had worse baseline hypoxia (p = 0.06). Three of the 24 (13%) patients who received treatment died compared to six of 12 (50%) patients who did not receive treatment (RR ratio: 0.25, p = 0.04, 95% CI: 0.08 to 0.83). In the survival analysis, there was a statistically significant reduction in inpatient mortality in the treatment group (HR: 0.19, p = 0.02, 95% CI: 0.05-0.74). However, after adjusting for age and baseline hypoxia, there was no difference in inpatient mortality (hazard ratio: 0.48, p = 0.42, 95% CI: 0.08-2.86). CONCLUSION The survival benefit of HBO2 therapy observed in our unadjusted analysis suggests that there may be therapeutic benefits of HBO2 in treating COVID-19 hypoxia as an adjunct to standard care.
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Affiliation(s)
- Deepa Jansen
- Department of Internal Medicine, Yale New Haven Health - Greenwich Hospital
| | - Daniel R Dickstein
- Department of Internal Medicine, Yale New Haven Health - Greenwich Hospital
| | - Kasandra Erazo
- Department of Internal Medicine, Yale New Haven Health - Greenwich Hospital
| | - Ellen Stacom
- Department of Hyperbaric Oxygen and Wound Care, Yale New Haven Health - Greenwich Hospital
| | - David C Lee
- Department of Emergency Medicine, NYU Grossman School of Medicine
- Department of Population Health, NYU Grossman School of Medicine
| | - Sandra K Wainwright
- Department of Pulmonary and Critical Care Medicine, Yale New Haven Health - Greenwich Hospital
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17
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Affiliation(s)
- Muhammad Naeem Awan
- Department of Zoology, University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan
| | | | - Muhammad Ali Nawaz
- Department of Animal Sciences, Quaid-e-Azam University, Islamabad, Pakistan
| | - Shoab Hameed
- Department of Animal Sciences, Quaid-e-Azam University, Islamabad, Pakistan
| | - Muhammad Kabir
- Department of Wildlife and Forestry, University of Haripur, Haripur, Pakistan
| | - David C. Lee
- School of Applied Sciences, University of South Wales, Pontypridd, UK
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18
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Kanchi R, Lopez P, Rummo PE, Lee DC, Adhikari S, Schwartz MD, Avramovic S, Siegel KR, Rolka DB, Imperatore G, Elbel B, Thorpe LE. Longitudinal Analysis of Neighborhood Food Environment and Diabetes Risk in the Veterans Administration Diabetes Risk Cohort. JAMA Netw Open 2021; 4:e2130789. [PMID: 34714343 PMCID: PMC8556617 DOI: 10.1001/jamanetworkopen.2021.30789] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 08/20/2021] [Indexed: 11/25/2022] Open
Abstract
Importance Diabetes causes substantial morbidity and mortality among adults in the US, yet its incidence varies across the country, suggesting that neighborhood factors are associated with geographical disparities in diabetes. Objective To examine the association between neighborhood food environment and risk of incident type 2 diabetes across different community types (high-density urban, low-density urban, suburban, and rural). Design, Setting, and Participants This is a national cohort study of 4 100 650 US veterans without type 2 diabetes. Participants entered the cohort between 2008 and 2016 and were followed up through 2018. The median (IQR) duration of follow-up was 5.5 (2.6-9.8) person-years. Data were obtained from Veterans Affairs electronic health records. Incident type 2 diabetes was defined as 2 encounters with type 2 diabetes International Classification of Diseases, Ninth Revision or Tenth Revision codes, a prescription for diabetes medication other than metformin or acarbose alone, or 1 encounter with type 2 diabetes International Classification of Diseases Ninth Revision or Tenth Revision codes and 2 instances of elevated hemoglobin A1c (≥6.5%). Data analysis was performed from October 2020 to March 2021. Exposures Five-year mean counts of fast-food restaurants and supermarkets relative to other food outlets at baseline were used to generate neighborhood food environment measures. The association between food environment and time to incident diabetes was examined using piecewise exponential models with 2-year interval of person-time and county-level random effects stratifying by community types. Results The mean (SD) age of cohort participants was 59.4 (17.2) years. Most of the participants were non-Hispanic White (2 783 756 participants [76.3%]) and male (3 779 555 participants [92.2%]). The relative density of fast-food restaurants was positively associated with a modestly increased risk of type 2 diabetes in all community types. The adjusted hazard ratio (aHR) was 1.01 (95% CI, 1.00-1.02) in high-density urban communities, 1.01 (95% CI, 1.01-1.01) in low-density urban communities, 1.02 (95% CI, 1.01-1.03) in suburban communities, and 1.01 (95% CI, 1.01-1.02) in rural communities. The relative density of supermarkets was associated with lower type 2 diabetes risk only in suburban (aHR, 0.97; 95% CI, 0.96-0.99) and rural (aHR, 0.99; 95% CI, 0.98-0.99) communities. Conclusions and Relevance These findings suggest that neighborhood food environment measures are associated with type 2 diabetes among US veterans in multiple community types and that food environments are potential avenues for action to address the burden of diabetes. Tailored interventions targeting the availability of supermarkets may be associated with reduced diabetes risk, particularly in suburban and rural communities, whereas restrictions on fast-food restaurants may help in all community types.
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Affiliation(s)
- Rania Kanchi
- Department of Population Health, NYU Langone Health, New York, New York
| | - Priscilla Lopez
- Department of Population Health, NYU Langone Health, New York, New York
| | - Pasquale E. Rummo
- Department of Population Health, NYU Langone Health, New York, New York
| | - David C. Lee
- Department of Population Health, NYU Langone Health, New York, New York
- Department of Emergency Medicine, NYU Langone Health, New York, New York
| | | | - Mark D. Schwartz
- Department of Population Health, NYU Langone Health, New York, New York
- VA New York Harbor Healthcare System, New York, New York
| | - Sanja Avramovic
- Department of Health Administration and Policy, George Mason University, Fairfax, Virginia
| | - Karen R. Siegel
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Deborah B. Rolka
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Giuseppina Imperatore
- Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Brian Elbel
- Department of Population Health, NYU Langone Health, New York, New York
- NYU Wagner Graduate School of Public Service, New York, New York
| | - Lorna E. Thorpe
- Department of Population Health, NYU Langone Health, New York, New York
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19
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Gomes C, Zuniga M, Crotty KA, Qian K, Tovar NC, Lin LH, Argyropoulos KV, Clancy R, Izmirly P, Buyon J, Lee DC, Yasnot-Acosta MF, Li H, Cotzia P, Rodriguez A. Autoimmune anti-DNA and anti-phosphatidylserine antibodies predict development of severe COVID-19. Life Sci Alliance 2021; 4:4/11/e202101180. [PMID: 34504035 PMCID: PMC8441539 DOI: 10.26508/lsa.202101180] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/18/2021] [Accepted: 08/18/2021] [Indexed: 11/30/2022] Open
Abstract
COVID-19 induces high levels of autoimmune anti-DNA and anti-phosphatidylserine antibodies that are detected in some patients upon hospital admission and predict later development of severe disease. High levels of autoimmune antibodies are observed in COVID-19 patients but their specific contribution to disease severity and clinical manifestations remains poorly understood. We performed a retrospective study of 115 COVID-19 hospitalized patients with different degrees of severity to analyze the generation of autoimmune antibodies to common antigens: a lysate of erythrocytes, the lipid phosphatidylserine (PS) and DNA. High levels of IgG autoantibodies against erythrocyte lysates were observed in a large percentage (up to 36%) of patients. Anti-DNA and anti-PS antibodies determined upon hospital admission correlated strongly with later development of severe disease, showing a positive predictive value of 85.7% and 92.8%, respectively. Patients with positive values for at least one of the two autoantibodies accounted for 24% of total severe cases. Statistical analysis identified strong correlations between anti-DNA antibodies and markers of cell injury, coagulation, neutrophil levels and erythrocyte size. Anti-DNA and anti-PS autoantibodies may play an important role in the pathogenesis of COVID-19 and could be developed as predictive biomarkers for disease severity and specific clinical manifestations.
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Affiliation(s)
- Claudia Gomes
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Marisol Zuniga
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Kelly A Crotty
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Kun Qian
- Division of Biostatistics, Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Nubia Catalina Tovar
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY, USA.,Universidad de Córdoba, Montería, Córdoba, Colombia.,Universidad Del Sinú, Montería, Córdoba, Colombia
| | - Lawrence Hsu Lin
- Department of Pathology, New York University Grossman School of Medicine, New York, NY, USA
| | - Kimon V Argyropoulos
- Department of Pathology, New York University Grossman School of Medicine, New York, NY, USA
| | - Robert Clancy
- Division of Rheumatology, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Peter Izmirly
- Division of Rheumatology, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Jill Buyon
- Division of Rheumatology, Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - David C Lee
- Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | | | - Huilin Li
- Division of Biostatistics, Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA
| | - Paolo Cotzia
- Department of Pathology, New York University Grossman School of Medicine, New York, NY, USA
| | - Ana Rodriguez
- Department of Microbiology, New York University Grossman School of Medicine, New York, NY, USA
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20
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Estrella A, Scheidell J, Khan M, Castelblanco D, Mijanovich T, Lee DC, Gelberg L, Doran KM. Cross-sectional Analysis of Food Insecurity and Frequent Emergency Department Use. West J Emerg Med 2021; 22:911-918. [PMID: 35354018 PMCID: PMC8328160 DOI: 10.5811/westjem.2021.3.50981] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 03/08/2021] [Indexed: 11/11/2022] Open
Abstract
INTRODUCTION Emergency department (ED) patients have higher than average levels of food insecurity. We examined the association between multiple measures of food insecurity and frequent ED use in a random sample of ED patients. METHODS We completed survey questionnaires with randomly sampled adult patients from an urban public hospital ED (n = 2,312). We assessed food insecurity using four questions from the United States Department of Agriculture Household Food Security Survey. The primary independent variable was any food insecurity, defined as an affirmative response to any of the four items. Frequent ED use was defined as self-report of ≥4 ED visits in the past year. We examined the relationship between patient food insecurity and frequent ED use using bivariate and multivariable analyses and examined possible mediation by anxiety/depression and overall health status. RESULTS One-third (30.9%) of study participants reported frequent ED use, and half (50.8%) reported any food insecurity. Prevalence of food insecurity was higher among frequent vs. non-frequent ED users, 62.8% vs 45.4% (P <0.001). After controlling for potential confounders, food insecurity remained significantly associated with frequent ED use (adjusted odds ratio 1.48, 95% confidence interval, 1.20-1.83). This observed association was partially attenuated when anxiety/depression and overall health status were added to models. CONCLUSION The high observed prevalence of food insecurity suggests that efforts to improve care of ED patients should assess and address this need. Further research is needed to assess whether addressing food insecurity may play an important role in efforts to reduce frequent ED use for some patients.
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Affiliation(s)
- Alex Estrella
- UMMS-Baystate, Department of Emergency Medicine, Springfield, Massachusetts
| | - Joy Scheidell
- New York University School of Medicine, NYU Langone Health, Department of Population Health, New York, New York
| | - Maria Khan
- New York University School of Medicine, NYU Langone Health, Department of Population Health, New York, New York
| | - Donna Castelblanco
- New York City Department of Health and Mental Hygiene, New York, New York
| | - Tod Mijanovich
- New York University Steinhardt School of Culture, Education, and Human Development, Department of Applied Statistics, Social Science, and Humanities, New York, New York
| | - David C Lee
- New York University School of Medicine, Departments of Emergency Medicine and Population Health, New York, New York
| | - Lillian Gelberg
- David Geffen School of Medicine at UCLA, Department of Family Medicine, Los Angeles, California.,UCLA Fielding School of Public Health, Department of Health Policy and Management, Los Angeles, California.,VA Greater Los Angeles Healthcare System, Office of Healthcare Transformation and Innovation, Los Angeles, California
| | - Kelly M Doran
- New York University School of Medicine, Departments of Emergency Medicine and Population Health, New York, New York
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21
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Bakker EA, Lee DC, Hopman MTE, Thijssen DHJ, Eijsvogels TMH. Impact of cardiovascular health status on the association between changes in physical activity and major cardiovascular events and mortality among 88,320 adults: outcomes of the Lifelines Cohort Study. Eur J Prev Cardiol 2021. [DOI: 10.1093/eurjpc/zwab061.191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public grant(s) – National budget only. Main funding source(s): The Lifelines Biobank initiative received funding from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen [UMCG], University Groningen and the Northern Provinces of the Netherlands. The work of T.M.H.E is supported by the Netherlands Heart Foundation [Senior E-Dekker grant #2017T051].
Background. Regular physical activity (PA) improves health. Many observational studies investigated the association between PA and health at a single time-point, but PA might change over time.
Purpose. To examine the association between change in PA and major adverse cardiovascular events (MACE) and all-cause mortality, and to investigate the impact of cardiovascular health status at baseline on these outcomes.
Methods. This study used data from the Lifelines Cohort Study (N = 88,320). Self-reported PA volumes were presented as Metabolic Equivalent of Task (MET) min/week. Change in PA was calculated by subtracting MET-min/week at the first assessment from the second assessment (median interval: 4 yrs), and 5 groups were created; large reduction (< -1500), moderate reduction (-1500 to -250), no change (-250 to 250), moderate improvement (-250 to 250) and large improvement (>1500). The outcome was a combination of MACE and all-cause mortality.
Results. During a median follow-up of 7 years, 667 events occurred among healthy individuals (43 ± 12 yrs, 1% of 69,818) and 599 in individuals with CVRF (55 ± 11 yrs, 3% of 18,502). Adjusted for confounders and baseline PA, healthy individuals with a large reduction in PA had a greater risk of incident MACE and mortality (Table). In CVRF, moderate to large improvements in PA were associated with reductions in adverse outcomes. Risk estimates became stronger in individuals with lower baseline PA (<2000 MET-min/week), Table).
Conclusions. Maintaining PA in healthy individuals and increasing PA in individuals with CVRF over time is important to prevent MACE and mortality. The impact of changes in PA was stronger for individuals with lower baseline PA.
Table. Change of PA, MACE and mortality. Changes in PA Healthy CVRF Large reduction 1.40 [1.02;1.93] 1.27 [0.95;1.70] Moderate reduction 1.22 [0.89;1.68] 0.97 [0.72;1.30] No changes Ref Ref Moderate improvement 1.04 [0.74;1.44] 0.65 [0.47;0.91] Large improvement 0.96 [0.71;1.31] 0.69 [0.51; 0.94] Individuals with lower baseline PA Large reduction 2.24 [0.96;5.21] 2.85 [1.44;5.63] Moderate reduction 1.77 [1.10;2.84] 1.33 [0.89;1.98] No changes Ref Ref Moderate improvement 1.16 [0.73;1.83] 0.49 [0.31;0.76] Large improvement 0.77 [0.48;1.23] 0.58 [0.39;0.86]
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Affiliation(s)
- EA Bakker
- Radboud Institute for Health Sciences, Physiology, Nijmegen, Netherlands (The)
| | - DC Lee
- Iowa State University, Department of Kinesiology, Ames, United States of America
| | - MTE Hopman
- Radboud Institute for Health Sciences, Physiology, Nijmegen, Netherlands (The)
| | - DHJ Thijssen
- Radboud Institute for Health Sciences, Physiology, Nijmegen, Netherlands (The)
| | - TMH Eijsvogels
- Radboud Institute for Health Sciences, Physiology, Nijmegen, Netherlands (The)
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22
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Umar M, Hussain M, Malik MF, Awan MN, Lee DC. Avian Community Composition and Spatio-Temporal Patterns at Deva Vatala National Park, Azad Jammu and Kashmir, Pakistan. PAK J ZOOL 2021. [DOI: 10.17582/journal.pjz/20190711190734] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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23
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Izzy M, Addissie BD, Arab JP, Hilscher MB, Cartee A, Lee DC, Lee Y, Fletcher JG, Keaveny TM, Sanchez W. Triple-Phase Computed Tomography May Replace Dual-Energy X-ray Absorptiometry Scan for Evaluation of Osteoporosis in Liver Transplant Candidates. Liver Transpl 2021; 27:341-348. [PMID: 33098253 DOI: 10.1002/lt.25926] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 09/12/2020] [Accepted: 10/02/2020] [Indexed: 01/13/2023]
Abstract
Assessment of bone density is an important part of liver transplantation (LT) evaluation for early identification and treatment of osteoporosis. Dual-energy X-ray absorptiometry (DXA) is currently the standard clinical test for osteoporosis; however, it may contribute to the appointment burden on LT candidates during the cumbersome evaluation process, and there are limitations affecting its accuracy. In this study, we evaluate the utility of biomechanical analysis of vertebral images obtained during dual-energy abdominal triple-phase computed tomography (TPCT) in diagnosing osteoporosis among LT candidates. We retrospectively reviewed cases evaluated for LT between January 2017 and March 2018. All patients who underwent TPCT within 3 months of DXA were included. The biomechanical computed tomography (BCT) analysis was performed at a centralized laboratory (O.N. Diagnostics, Berkeley, CA) by 2 trained analysts blinded to the DXA data. DXA-based osteoporosis was defined as a T score ≤-2.5 at the hip or spine. BCT-based osteoporosis was defined as vertebral strength ≤4500 N for women or ≤6500 N for men or trabecular volumetric bone mineral density ≤80 mg/cm3 . Comparative data were available for 91 patients who had complete data for both DXA and BCT: 31 women and 60 men, age 54 ± 11 years (mean ± standard deviation), mean body mass index 28 ± 6 kg/m2 . Using DXA as the clinical reference, sensitivity of BCT to detect DXA-defined osteoporosis was 83.3% (20/24 patients) and negative predictive value was 91.7%; specificity and positive predictive value were 65.7% and 46.5%, respectively. BCT analysis of vertebral images on triple-phase computed tomography, routinely obtained during transplant evaluation, can reliably rule out osteoporosis in LT candidates. Patients with suspicion of osteoporosis on TPCT may need further evaluation by DXA.
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Affiliation(s)
- Manhal Izzy
- Division of Gastroenterology, Hepatology, and Nutrition, Vanderbilt University Medical Center, Nashville, TN
| | - Benyam D Addissie
- Division of Gastroenterology and Hepatology, Geisinger Medical Center, Danville, PA
| | - Juan Pablo Arab
- Departamento de Gastroenterologia, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Moira B Hilscher
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
| | - Amanda Cartee
- Division of Gastroenterology and Hepatology, University of Michigan, Ann Harbor, MI
| | | | - Yong Lee
- Department of Radiology, Mayo Clinic, Rochester, MN
| | | | - Tony M Keaveny
- Department of Mechanical Engineering, University of California, Berkeley, CA.,Department of Mechanical Engineering, Department of Bioengineering, University of California, Berkeley, CA
| | - William Sanchez
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN
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24
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Hong N, Lee DC, Khosla S, Keaveny TM, Rhee Y. Comparison of Vertebral and Femoral Strength Between White and Asian Adults Using Finite Element Analysis of Computed Tomography Scans. J Bone Miner Res 2020; 35:2345-2354. [PMID: 32750185 PMCID: PMC9260814 DOI: 10.1002/jbmr.4149] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [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: 05/15/2020] [Revised: 07/20/2020] [Accepted: 07/30/2020] [Indexed: 11/09/2022]
Abstract
Given non-optimal testing rates for dual-energy X-ray absorptiometry (DXA) and the high use of computed tomography (CT) in some Asian countries, biomechanical computed tomography analysis (BCT)-based bone strength testing, which utilizes previously taken clinical CT scans, may improve osteoporosis testing rates. However, an understanding of ethnic differences in such bone strength measurements between Whites and Asians is lacking, which is an obstacle to clinical interpretation. Using previously taken CT and DXA scans, we analyzed bone strength and bone mineral density (BMD) at the hip and spine in two sex- and age-matched community-based cohorts, aged 40 to 80 years: Whites (Rochester, MN, USA) and Koreans (Seoul, South Korea). For both the spine and femur, the age dependence of bone strength was similar for both groups, White (n = 371; women n = 202, 54.5%) and Korean (n = 396; women n = 199, 50.3%). For both sexes, mean spine strength did not differ between groups, but femur strength was 9% to 14% higher in Whites (p ≤ 0.001), an effect that became non-significant after weight adjustment (p = 0.375). For Koreans of both sexes, the fragile bone strength thresholds for classifying osteoporosis, when derived from regional DXA BMD T-score references, equaled the clinically validated thresholds for Whites (in women and men, femoral strength, 3000 N and 3500 N; vertebral strength 4500 N and 6500 N, respectively). Using these thresholds, classifications for osteoporosis for Koreans based on bone strength versus based on DXA BMD T-scores were consistent (89.1% to 94.4% agreement) at both the hip and spine and for both sexes. The BCT-based, clinically validated bone strength thresholds for Whites also applied to Koreans, which may facilitate clinical interpretation of CT-based bone strength measurements for Koreans. © 2020 American Society for Bone and Mineral Research (ASBMR).
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Affiliation(s)
- Namki Hong
- Department of Internal Medicine, Endocrine Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | | | - Sundeep Khosla
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - Tony M Keaveny
- Departments of Mechanical Engineering and Bioengineering, University of California, Berkeley, CA, USA
| | - Yumie Rhee
- Department of Internal Medicine, Endocrine Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
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25
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Lee DC, McGraw NA, Doran KM, Mengotto AK, Wiener SL, Vinson AJ, Thorpe LE. Comparing methods of performing geographically targeted rural health surveillance. Emerg Themes Epidemiol 2020; 17:3. [PMID: 33292290 PMCID: PMC7686693 DOI: 10.1186/s12982-020-00090-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 11/17/2020] [Indexed: 11/26/2022] Open
Abstract
Background Worsening socioeconomic conditions in rural America have been fueling increases in chronic disease and poor health. The goal of this study was to identify cost-effective methods of deploying geographically targeted health surveys in rural areas, which often have limited resources. These health surveys were administered in New York’s rural Sullivan County, which has some of the poorest health outcomes in the entire state. Methods Comparisons were made for response rates, estimated costs, respondent demographics, and prevalence estimates of a brief health survey delivered by mail and phone using address-based sampling, and in-person using convenience sampling at a sub-county level in New York’s rural Sullivan County during 2017. Results Overall response rates were 27.0% by mail, 8.2% by phone, and 71.4% for convenience in-person surveys. Costs to perform phone surveys were substantially higher than mailed or convenience in-person surveys. All modalities had lower proportions of Hispanic respondents compared to Census estimates. Unadjusted and age-adjusted prevalence estimates were similar between mailed and in-person surveys, but not for phone surveys. Conclusions These findings are consistent with declining response rates of phone surveys, which obtained an inadequate sample of rural residents. Though in-person surveys had higher response rates, convenience sampling failed to obtain a geographically distributed sample of rural residents. Of modalities tested, mailed surveys provided the best opportunity to perform geographically targeted rural health surveillance.
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Affiliation(s)
- David C Lee
- Ronald O. Perelman Department of Emergency Medicine, NYU School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA. .,Department of Population Health, NYU School of Medicine, New York, NY, USA.
| | - Nancy A McGraw
- Sullivan County Public Health Services, Liberty, NY, USA
| | - Kelly M Doran
- Ronald O. Perelman Department of Emergency Medicine, NYU School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA.,Department of Population Health, NYU School of Medicine, New York, NY, USA
| | - Amanda K Mengotto
- Ronald O. Perelman Department of Emergency Medicine, NYU School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Sara L Wiener
- Ronald O. Perelman Department of Emergency Medicine, NYU School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Andrew J Vinson
- Ronald O. Perelman Department of Emergency Medicine, NYU School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Lorna E Thorpe
- Department of Population Health, NYU School of Medicine, New York, NY, USA
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Treglia D, Johns EL, Schretzman M, Berman J, Culhane DP, Lee DC, Doran KM. When Crises Converge: Hospital Visits Before And After Shelter Use Among Homeless New Yorkers. Health Aff (Millwood) 2020; 38:1458-1467. [PMID: 31479375 DOI: 10.1377/hlthaff.2018.05308] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
People who are homeless use more hospital-based care than average, yet little is known about how hospital and shelter use are interrelated. We examined the timing of emergency department (ED) visits and hospitalizations relative to entry into and exit from New York City homeless shelters, using an analysis of linked health care and shelter administrative databases. In the year before shelter entry and the year following shelter exit, 39.3 percent and 43.3 percent, respectively, of first-time adult shelter users had an ED visit or hospitalization. Hospital visits-particularly ED visits-began to increase several months before shelter entry and declined over several months after shelter exit, with spikes in ED visits and hospitalizations in the days immediately before shelter entry and following shelter exit. We recommend cross-system collaborations to better understand and address the co-occurring health and housing needs of vulnerable populations.
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Affiliation(s)
- Dan Treglia
- Dan Treglia is a postdoctoral fellow in the School of Social Policy and Practice, University of Pennsylvania, in Philadelphia
| | - Eileen L Johns
- Eileen L. Johns is director of policy and research at the New York City Center for Innovation through Data Intelligence
| | - Maryanne Schretzman
- Maryanne Schretzman is executive director of the New York City Center for Innovation through Data Intelligence
| | - Jacob Berman
- Jacob Berman is a research analyst at the New York City Center for Innovation through Data Intelligence
| | - Dennis P Culhane
- Dennis P. Culhane holds the Dana and Andrew Stone Chair in Social Policy at the University of Pennsylvania
| | - David C Lee
- David C. Lee is an assistant professor in the Departments of Emergency Medicine and Population Health, New York University School of Medicine, in New York City
| | - Kelly M Doran
- Kelly M. Doran ( ) is an assistant professor in the Departments of Emergency Medicine and Population Health, New York University School of Medicine
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Akhavan AR, Habboushe JP, Gulati R, Iheagwara O, Watterson J, Thomas S, Swartz JL, Koziatek CA, Lee DC. Risk Stratification of COVID-19 Patients Using Ambulatory Oxygen Saturation in the Emergency Department. West J Emerg Med 2020; 21:5-14. [PMID: 33052820 PMCID: PMC7673885 DOI: 10.5811/westjem.2020.8.48701] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Accepted: 08/09/2020] [Indexed: 01/08/2023] Open
Abstract
INTRODUCTION It is difficult to determine illness severity for coronavirus disease 2019 (COVID-19) patients, especially among stable-appearing emergency department (ED) patients. We evaluated patient outcomes among ED patients with a documented ambulatory oxygen saturation measurement. METHODS This was a retrospective chart review of ED patients seen at New York University Langone Health during the peak of the COVID-19 pandemic in New York City. We identified ED patients who had a documented ambulatory oxygen saturation. We studied the outcomes of high oxygen requirement (defined as >4 liters per minute) and mechanical ventilation among admitted patients and bounceback admissions among discharged patients. We also performed logistic regression and compared the performance of different ambulatory oxygen saturation cutoffs in predicting these outcomes. RESULTS Between March 15-April 14, 2020, 6194 patients presented with fever, cough, or shortness of breath at our EDs. Of these patients, 648 (11%) had a documented ambulatory oxygen saturation, of which 165 (24%) were admitted. Notably, admitted and discharged patients had similar initial vital signs. However, the average ambulatory oxygen saturation among admitted patients was significantly lower at 89% compared to 96% among discharged patients (p<0.01). Among admitted patients with an ambulatory oxygen saturation, 30% had high oxygen requirements and 8% required mechanical ventilation. These rates were predicted by low ambulatory oxygen saturation (p<0.01). Among discharged patients, 50 (10%) had a subsequent ED visit resulting in admission. Although bounceback admissions were predicted by ambulatory oxygen saturation at the first ED visit (p<0.01), our analysis of cutoffs suggested that this association may not be clinically useful. CONCLUSION Measuring ambulatory oxygen saturation can help ED clinicians identify patients who may require high levels of oxygen or mechanical ventilation during admission. However, it is less useful for identifying which patients may deteriorate clinically in the days after ED discharge and require subsequent hospitalization.
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Affiliation(s)
- Arvin R Akhavan
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Joseph P Habboushe
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Rajneesh Gulati
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Oluchi Iheagwara
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Joanna Watterson
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Shawn Thomas
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Jordan L Swartz
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - Christian A Koziatek
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York
| | - David C Lee
- New York University Grossman School of Medicine, Ronald O. Perelman Department of Emergency Medicine, New York, New York.,New York University Grossman School of Medicine, Department of Population Health, New York, New York
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Ramadan L, Koziatek CA, Caldwell JR, Pecoriello J, Kuhner C, Subaiya S, Lee DC. Pulmonary thromboembolism in COVID-19: Evaluating the role of D-dimer and computed tomography pulmonary angiography results. Am J Emerg Med 2020; 46:786-787. [PMID: 32928606 PMCID: PMC7834565 DOI: 10.1016/j.ajem.2020.08.096] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 08/22/2020] [Accepted: 08/31/2020] [Indexed: 12/19/2022] Open
Affiliation(s)
- Leena Ramadan
- Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, United States of America.
| | - Christian A Koziatek
- Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, United States of America
| | - J Reed Caldwell
- Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, United States of America
| | - Jillian Pecoriello
- Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, United States of America
| | - Christopher Kuhner
- Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, United States of America
| | - Saleena Subaiya
- Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, United States of America
| | - David C Lee
- Ronald O. Perelman Department of Emergency Medicine, NYU Grossman School of Medicine, United States of America; Department of Population Health, NYU Grossman School of Medicine, United States of America
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Zhou S, AbdelWahab A, Horáček BM, MacInnis PJ, Warren JW, Davis JS, Elsokkari I, Lee DC, MacIntyre CJ, Parkash R, Gray CJ, Gardner MJ, Marcoux C, Choudhury R, Trayanova NA, Sapp JL. Prospective Assessment of an Automated Intraprocedural 12-Lead ECG-Based System for Localization of Early Left Ventricular Activation. Circ Arrhythm Electrophysiol 2020; 13:e008262. [PMID: 32538133 DOI: 10.1161/circep.119.008262] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [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] [Indexed: 11/16/2022]
Abstract
BACKGROUND To facilitate ablation of ventricular tachycardia (VT), an automated localization system to identify the site of origin of left ventricular activation in real time using the 12-lead ECG was developed. The objective of this study was to prospectively assess its accuracy. METHODS The automated site of origin localization system consists of 3 steps: (1) localization of ventricular segment based on population templates, (2) population-based localization within a segment, and (3) patient-specific site localization. Localization error was assessed by the distance between the known reference site and the estimated site. RESULTS In 19 patients undergoing 21 catheter ablation procedures of scar-related VT, site of origin localization accuracy was estimated using 552 left ventricular endocardial pacing sites pooled together and 25 VT-exit sites identified by contact mapping. For the 25 VT-exit sites, localization error of the population-based localization steps was within 10 mm. Patient-specific site localization achieved accuracy of within 3.5 mm after including up to 11 pacing (training) sites. Using 3 remotes (67.8±17.0 mm from the reference VT-exit site), and then 5 close pacing sites, resulted in localization error of 7.2±4.1 mm for the 25 identified VT-exit sites. In 2 emulated clinical procedure with 2 induced VTs, the site of origin localization system achieved accuracy within 4 mm. CONCLUSIONS In this prospective validation study, the automated localization system achieved estimated accuracy within 10 mm and could thus provide clinical utility.
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Affiliation(s)
- Shijie Zhou
- Department of Biomedical Engineering (S.Z., N.A.T.), Johns Hopkins University, Baltimore, MD.,Alliance for Cardiovascular Diagnostic and Treatment Innovation (S.Z., N.A.T.), Johns Hopkins University, Baltimore, MD.,Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Amir AbdelWahab
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - B Milan Horáček
- School of Biomedical Engineering (B.M.H.), Dalhousie University, Halifax, NS, Canada
| | - Paul J MacInnis
- Departments of Physiology and Biophysics (P.J.M., J.W.W., J.L.S.), Dalhousie University, Halifax, NS, Canada
| | - James W Warren
- Departments of Physiology and Biophysics (P.J.M., J.W.W., J.L.S.), Dalhousie University, Halifax, NS, Canada
| | - Jason S Davis
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Ihab Elsokkari
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - David C Lee
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Ciorsti J MacIntyre
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Ratika Parkash
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Chris J Gray
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Martin J Gardner
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Curtis Marcoux
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Rajin Choudhury
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.)
| | - Natalia A Trayanova
- Department of Biomedical Engineering (S.Z., N.A.T.), Johns Hopkins University, Baltimore, MD.,Alliance for Cardiovascular Diagnostic and Treatment Innovation (S.Z., N.A.T.), Johns Hopkins University, Baltimore, MD
| | - John L Sapp
- Heart Rhythm Service, Cardiology Division, Department of Medicine, Queen Elizabeth II Health Sciences Centre, Halifax, NS, Canada (S.Z., A.A., J.S.D., I.E., D.C.L., C.J.M., R.P., C.J.G., M.J.G., C.M., R.C., J.L.S.).,Departments of Physiology and Biophysics (P.J.M., J.W.W., J.L.S.), Dalhousie University, Halifax, NS, Canada.,Medicine (J.L.S.), Dalhousie University, Halifax, NS, Canada
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Koziatek CA, Rubin A, Lakdawala V, Lee DC, Swartz J, Auld E, Smith SW, Reddy H, Jamin C, Testa P, Femia R, Caspers C. Assessing the Impact of a Rapidly Scaled Virtual Urgent Care in New York City During the COVID-19 Pandemic. J Emerg Med 2020; 59:610-618. [PMID: 32737005 PMCID: PMC7290166 DOI: 10.1016/j.jemermed.2020.06.041] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 06/01/2020] [Accepted: 06/06/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND The coronavirus disease (COVID)-19 pandemic quickly challenged New York City health care systems. Telemedicine has been suggested to manage acute complaints and divert patients from in-person care. OBJECTIVES The objective of this study was to describe and assess the impact of a rapidly scaled virtual urgent care platform during the COVID-19 pandemic. METHODS This was a retrospective cohort study of all patients who presented to a virtual urgent care platform over 1 month during the COVID-19 pandemic surge. We described scaling our telemedicine urgent care capacity, described patient clinical characteristics, assessed for emergency department (ED) referrals, and analyzed postvisit surveys. RESULTS During the study period, a total of 17,730 patients were seen via virtual urgent care; 454 (2.56%) were referred to an ED. The most frequent diagnoses were COVID-19 related or upper respiratory symptoms. Geospatial analysis indicated a wide catchment area. There were 251 providers onboarded to the platform; at peak, 62 providers supplied 364 h of coverage in 1 day. The average patient satisfaction score was 4.4/5. There were 2668 patients (15.05%) who responded to the postvisit survey; 1236 (49.35%) would have sought care in an ED (11.86%) or in-person urgent care (37.49%). CONCLUSIONS A virtual urgent care platform was scaled to manage a volume of more than 800 patients a day across a large catchment area during the pandemic surge. About half of the patients would otherwise have presented to an ED or urgent care in person. Virtual urgent care is an option for appropriate patients while minimizing in-person visits during the COVID-19 pandemic.
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Affiliation(s)
- Christian A Koziatek
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
| | - Ada Rubin
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
| | - Viraj Lakdawala
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
| | - David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York; Department of Population Health, New York University Grossman School of Medicine, New York, New York
| | - Jordan Swartz
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
| | - Elizabeth Auld
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
| | - Silas W Smith
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York; Institute for Innovations in Medical Education, New York University School of Medicine, New York, New York
| | - Harita Reddy
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
| | - Catherine Jamin
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
| | - Paul Testa
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York
| | - Robert Femia
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
| | - Christopher Caspers
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York; Department of Emergency Medicine, Bellevue Hospital Center, New York, New York
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Chan PY, Perlman SE, Lee DC, Smolen JR, Lim S. Neighborhood-Level Chronic Disease Surveillance: Utility of Primary Care Electronic Health Records and Emergency Department Claims Data. J Public Health Manag Pract 2020; 28:E109-E118. [PMID: 32487918 DOI: 10.1097/phh.0000000000001142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
CONTEXT Disease burden may vary substantively across neighborhoods in an urban setting. Yet, data available for monitoring chronic conditions at the neighborhood level are scarce. Large health care data sets have potential to complement population health surveillance. Few studies have examined the utility of health care data for neighborhood-level surveillance. OBJECTIVE We examined the use of primary care electronic health records (EHRs) and emergency department (ED) claims for identifying neighborhoods with higher chronic disease burden and neighborhood-level prevalence estimation. DESIGN Comparison of hypertension and diabetes estimates from EHRs and ED claims with survey-based estimates. SETTING Forty-two United Hospital Fund neighborhoods in New York City. PARTICIPANTS The EHR sample comprised 708 452 patients from the Hub Population Health System (the Hub) in 2015, and the ED claim sample comprised 1 567 870 patients from the Statewide Planning and Research Cooperative System in 2015. We derived survey-based estimates from 2012 to 2016 Community Health Survey (n = 44 189). MAIN OUTCOME MEASURE We calculated hypertension and diabetes prevalence estimates by neighborhood from each data source. We obtained Pearson correlation and absolute difference between EHR-based or claims-based estimates and survey-based estimates. RESULTS Both EHR-based and claims-based estimates correlated strongly with survey-based estimates for hypertension (0.91 and 0.72, respectively) and diabetes (0.83 and 0.82, respectively) and identified similar neighborhoods of higher burden. For hypertension, 10 and 17 neighborhoods from the EHRs and ED claims, respectively, had an absolute difference of more than 5 percentage points from the survey-based estimate. For diabetes, 15 and 4 neighborhoods from the EHRs and ED claims, respectively, differed from the survey-based estimate by more than 5 percentage points. CONCLUSIONS Both EHRs and ED claims data are useful for identifying neighborhoods with greater disease burden and have potential for monitoring chronic conditions at the neighborhood level.
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Affiliation(s)
- Pui Ying Chan
- Divisions of Epidemiology (Ms Chan and Perlman and Dr Lim) and Prevention and Primary Care (Ms Smolen), New York City Department of Health and Mental Hygiene, Long Island City, New York; and Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, New York (Dr Lee)
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Howe JG, Hill RS, Stroncek JD, Shaul JL, Favell D, Cheng RR, Engelke K, Genant HK, Lee DC, Keaveny TM, Bouxsein ML, Huber B. Treatment of bone loss in proximal femurs of postmenopausal osteoporotic women with AGN1 local osteo-enhancement procedure (LOEP) increases hip bone mineral density and hip strength: a long-term prospective cohort study. Osteoporos Int 2020; 31:921-929. [PMID: 31802158 PMCID: PMC7170985 DOI: 10.1007/s00198-019-05230-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 11/07/2019] [Indexed: 12/14/2022]
Abstract
UNLABELLED This first-in-human study of AGN1 LOEP demonstrated that this minimally-invasive treatment durably increased aBMD in femurs of osteoporotic postmenopausal women. AGN1 resorption was coupled with new bone formation by 12 weeks and that new bone was maintained for at least 5-7 years resulting in substantially increased FEA-estimated femoral strength. INTRODUCTION This first-in-human study evaluated feasibility, safety, and in vivo response to treating proximal femurs of postmenopausal osteoporotic women with a minimally-invasive local osteo-enhancement procedure (LOEP) to inject a resorbable triphasic osteoconductive implant material (AGN1). METHODS This prospective cohort study enrolled 12 postmenopausal osteoporotic (femoral neck T-score ≤ - 2.5) women aged 56 to 89 years. AGN1 LOEP was performed on left femurs; right femurs were untreated controls. Subjects were followed-up for 5-7 years. Outcomes included adverse events, proximal femur areal bone mineral density (aBMD), AGN1 resorption, and replacement with bone by X-ray and CT, and finite element analysis (FEA) estimated hip strength. RESULTS Baseline treated and control femoral neck aBMD was equivalent. Treated femoral neck aBMD increased by 68 ± 22%, 59 ± 24%, and 58 ± 27% over control at 12 and 24 weeks and 5-7 years, respectively (p < 0.001, all time points). Using conservative assumptions, FEA-estimated femoral strength increased by 41%, 37%, and 22% at 12 and 24 weeks and 5-7 years, respectively (p < 0.01, all time points). Qualitative analysis of X-ray and CT scans demonstrated that AGN1 resorption and replacement with bone was nearly complete by 24 weeks. By 5-7 years, AGN1 appeared to be fully resorbed and replaced with bone integrated with surrounding trabecular and cortical bone. No procedure- or device-related serious adverse events (SAEs) occurred. CONCLUSIONS Treating femurs of postmenopausal osteoporotic women with AGN1 LOEP results in a rapid, durable increase in aBMD and femoral strength. These results support the use and further clinical study of this approach in osteoporotic patients at high risk of hip fracture.
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Affiliation(s)
- J G Howe
- AgNovos Healthcare LLC, Rockville, MD, USA
| | - R S Hill
- AgNovos Healthcare LLC, Rockville, MD, USA.
| | | | - J L Shaul
- AgNovos Healthcare LLC, Rockville, MD, USA
| | - D Favell
- AgNovos Healthcare LLC, Rockville, MD, USA
| | - R R Cheng
- AgNovos Healthcare LLC, Rockville, MD, USA
| | - K Engelke
- Bioclinica-Synarc, Inc., Hamburg, Germany
- FAU University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
| | - H K Genant
- University of California San Francisco, San Francisco, CA, USA
- Bioclinica-Synarc, Inc., Newark, CA, USA
| | - D C Lee
- O.N. Diagnostics, Berkeley, CA, USA
| | - T M Keaveny
- University of California Berkeley, Berkley, CA, USA
| | - M L Bouxsein
- Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - B Huber
- Mansfield Orthopedics, Morrisville, VT, USA
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Osorio M, Ravenell JE, Sevick MA, Ararso Y, Young T, Wall SP, Lee DC. Community-Based Hemoglobin A1C Testing in Barbershops to Identify Black Men With Undiagnosed Diabetes. JAMA Intern Med 2020; 180:596-597. [PMID: 31985740 PMCID: PMC6990850 DOI: 10.1001/jamainternmed.2019.6867] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
This cross-sectional study evaluates the use of hemoglobin A1c testing at barbershops owned by black individuals for timely diagnosis of diabetes among black men and suggests appropriate methods for care.
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Affiliation(s)
- Marcela Osorio
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York
| | - Joseph E Ravenell
- Department of Population Health, New York University School of Medicine, New York
| | - Mary A Sevick
- Department of Population Health, New York University School of Medicine, New York
| | - Yonathan Ararso
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York
| | - Ta'Loria Young
- Touro College of Osteopathic Medicine, New York, New York
| | - Stephen P Wall
- Department of Population Health, New York University School of Medicine, New York
| | - David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York.,Department of Population Health, New York University School of Medicine, New York
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Feldman JM, Lee DC, Lopez P, Rummo PE, Hirsch AG, Carson AP, McClure LA, Elbel B, Thorpe LE. Assessing county-level determinants of diabetes in the United States (2003-2012). Health Place 2020; 63:102324. [PMID: 32217279 DOI: 10.1016/j.healthplace.2020.102324] [Citation(s) in RCA: 2] [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: 08/09/2019] [Revised: 01/19/2020] [Accepted: 03/02/2020] [Indexed: 01/03/2023]
Abstract
Using data from the United States Behavioral Risk Factor Surveillance System (2003-2012; N = 3,397,124 adults), we estimated associations between prevalent diabetes and four county-level exposures (fast food restaurant density, convenience store density, unemployment, active commuting). All associations confirmed our a priori hypotheses in conventional multilevel analyses that pooled across years. In contrast, using a random-effects within-between model, we found weak, ambiguous evidence that within-county changes in exposures were associated with within-county change in odds of diabetes. Decomposition revealed that the pooled associations were largely driven by time-invariant, between-county factors that may be more susceptible to confounding versus within-county associations.
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Affiliation(s)
- Justin M Feldman
- Department of Population Health, NYU School of Medicine, New York, NY, USA.
| | - David C Lee
- Department of Population Health, NYU School of Medicine, New York, NY, USA
| | - Priscilla Lopez
- Department of Population Health, NYU School of Medicine, New York, NY, USA
| | - Pasquale E Rummo
- Department of Population Health, NYU School of Medicine, New York, NY, USA
| | - Annemarie G Hirsch
- Department of Epidemiology and Health Services Research, Geisinger Health System, Danville, PA, USA
| | - April P Carson
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Leslie A McClure
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
| | - Brian Elbel
- Department of Population Health, NYU School of Medicine, New York, NY, USA
| | - Lorna E Thorpe
- Department of Population Health, NYU School of Medicine, New York, NY, USA
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Smith SW, Lee DC, Goldfrank LR. Reflections on Mortality and Uncertainty in Emergency Medicine. JAMA Intern Med 2020; 180:88-90. [PMID: 31682680 DOI: 10.1001/jamainternmed.2019.4858] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Affiliation(s)
- Silas W Smith
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY.,Institute for Innovations in Medical Education, NYU Langone Health, New York, NY
| | - David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY.,Department of Population Health, New York University School of Medicine, New York, NY
| | - Lewis R Goldfrank
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY
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Lee DC, Feldman JM, Osorio M, Koziatek CA, Nguyen MV, Nagappan A, Shim CJ, Vinson AJ, Thorpe LE, McGraw NA. Improving the geographical precision of rural chronic disease surveillance by using emergency claims data: a cross-sectional comparison of survey versus claims data in Sullivan County, New York. BMJ Open 2019; 9:e033373. [PMID: 31740475 PMCID: PMC6887089 DOI: 10.1136/bmjopen-2019-033373] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
OBJECTIVES Some of the most pressing health problems are found in rural America. However, the surveillance needed to track and prevent disease in these regions is lacking. Our objective was to perform a comprehensive health survey of a single rural county to assess the validity of using emergency claims data to estimate rural disease prevalence at a sub-county level. DESIGN We performed a cross-sectional study of chronic disease prevalence estimates using emergency department (ED) claims data versus mailed health surveys designed to capture a substantial proportion of residents in New York's rural Sullivan County. SETTING Sullivan County, a rural county ranked second-to-last for health outcomes in New York State. PARTICIPANTS Adult residents of Sullivan County aged 25 years and older who responded to the health survey in 2017-2018 or had at least one ED visit in 2011-2015. OUTCOME MEASURES We compared age and gender-adjusted prevalence of hypertension, hyperlipidaemia, diabetes, cancer, asthma and chronic obstructive pulmonary disease/emphysema among nine sub-county areas. RESULTS Our county-wide mailed survey obtained 6675 completed responses for a response rate of 30.4%. This sample represented more than 12% of the estimated 53 020 adults in Sullivan County. Using emergency claims data, we identified 34 576 adults from Sullivan County who visited an ED at least once during 2011-2015. At a sub-county level, prevalence estimates from mailed surveys and emergency claims data correlated especially well for diabetes (r=0.90) and asthma (r=0.85). Other conditions were not well correlated (range: 0.23-0.46). Using emergency claims data, we created more geographically detailed maps of disease prevalence using geocoded addresses. CONCLUSIONS For select conditions, emergency claims data may be useful for tracking disease prevalence in rural areas and providing more geographically detailed estimates. For rural regions lacking robust health surveillance, emergency claims data can inform how to geographically target efforts to prevent chronic disease.
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Affiliation(s)
- David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York City, New York, USA
- Department of Population Health, New York University School of Medicine, New York City, New York, USA
| | - Justin M Feldman
- Department of Population Health, New York University School of Medicine, New York City, New York, USA
| | - Marcela Osorio
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York City, New York, USA
| | - Christian A Koziatek
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York City, New York, USA
| | - Michael V Nguyen
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York City, New York, USA
| | - Ashwini Nagappan
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York City, New York, USA
| | - Christopher J Shim
- California Northstate University College of Medicine, Elk Grove, California, USA
| | - Andrew J Vinson
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York City, New York, USA
| | - Lorna E Thorpe
- Department of Population Health, New York University School of Medicine, New York City, New York, USA
| | - Nancy A McGraw
- Sullivan County Public Health Services, Liberty, New York, USA
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Atwal M, Swan RL, Rowe C, Lee KC, Lee DC, Armstrong L, Cowell IG, Austin CA. Intercalating TOP2 Poisons Attenuate Topoisomerase Action at Higher Concentrations. Mol Pharmacol 2019; 96:475-484. [PMID: 31399497 PMCID: PMC6744389 DOI: 10.1124/mol.119.117259] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 08/02/2019] [Indexed: 12/18/2022] Open
Abstract
Topoisomerase II (TOP2) poisons are effective cytotoxic anticancer agents that stabilize the normally transient TOP2-DNA covalent complexes formed during the enzyme reaction cycle. These drugs include etoposide, mitoxantrone, and the anthracyclines doxorubicin and epirubicin. Anthracyclines also exert cell-killing activity via TOP2-independent mechanisms, including DNA adduct formation, redox activity, and lipid peroxidation. Here, we show that anthracyclines and another intercalating TOP2 poison, mitoxantrone, stabilize TOP2-DNA covalent complexes less efficiently than etoposide, and at higher concentrations they suppress the formation of TOP2-DNA covalent complexes, thus behaving as TOP2 poisons at low concentration and inhibitors at high concentration. We used induced pluripotent stem cell (iPSC)-derived human cardiomyocytes as a model to study anthracycline-induced damage in cardiac cells. Using immunofluorescence, our study is the first to demonstrate the presence of topoisomerase IIβ (TOP2B) as the only TOP2 isoform in iPSC-derived cardiomyocytes. In these cells, etoposide robustly induced TOP2B covalent complexes, but we could not detect doxorubicin-induced TOP2-DNA complexes, and doxorubicin suppressed etoposide-induced TOP2-DNA complexes. In vitro, etoposide-stabilized DNA cleavage was attenuated by doxorubicin, epirubicin, or mitoxantrone. Clinical use of anthracyclines is associated with cardiotoxicity. The observations in this study have potentially important clinical consequences regarding the effectiveness of anticancer treatment regimens when TOP2-targeting drugs are used in combination. These observations suggest that inhibition of TOP2B activity, rather than DNA damage resulting from TOP2 poisoning, may play a role in doxorubicin cardiotoxicity. SIGNIFICANCE STATEMENT: We show that anthracyclines and mitoxantrone act as topoisomerase II (TOP2) poisons at low concentration but attenuate TOP2 activity at higher concentration, both in cells and in in vitro cleavage experiments. Inhibition of type II topoisomerases suppresses the action of other drugs that poison TOP2. Thus, combinations containing anthracyclines or mitoxantrone and etoposide may reduce the activity of etoposide as a TOP2 poison and thus reduce the efficacy of drug combinations.
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Affiliation(s)
- Mandeep Atwal
- Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, United Kingdom (M.A., R.L.S., C.R., K.C.L., I.G.C., C.A.A.) and Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (D.C.L., L.A.)
| | - Rebecca L Swan
- Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, United Kingdom (M.A., R.L.S., C.R., K.C.L., I.G.C., C.A.A.) and Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (D.C.L., L.A.)
| | - Chloe Rowe
- Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, United Kingdom (M.A., R.L.S., C.R., K.C.L., I.G.C., C.A.A.) and Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (D.C.L., L.A.)
| | - Ka C Lee
- Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, United Kingdom (M.A., R.L.S., C.R., K.C.L., I.G.C., C.A.A.) and Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (D.C.L., L.A.)
| | - David C Lee
- Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, United Kingdom (M.A., R.L.S., C.R., K.C.L., I.G.C., C.A.A.) and Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (D.C.L., L.A.)
| | - Lyle Armstrong
- Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, United Kingdom (M.A., R.L.S., C.R., K.C.L., I.G.C., C.A.A.) and Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (D.C.L., L.A.)
| | - Ian G Cowell
- Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, United Kingdom (M.A., R.L.S., C.R., K.C.L., I.G.C., C.A.A.) and Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (D.C.L., L.A.)
| | - Caroline A Austin
- Institute for Cell and Molecular Biosciences, Newcastle University, Newcastle upon Tyne, United Kingdom (M.A., R.L.S., C.R., K.C.L., I.G.C., C.A.A.) and Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom (D.C.L., L.A.)
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Lee DC, Young T, Koziatek CA, Shim CJ, Osorio M, Vinson AJ, Ravenell JE, Wall SP. Age Disparities Among Patients With Type 2 Diabetes and Associated Rates of Hospital Use and Diabetic Complications. Prev Chronic Dis 2019; 16:E101. [PMID: 31370917 PMCID: PMC6716392 DOI: 10.5888/pcd16.180681] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Introduction Although screening for diabetes is recommended at age 45, some populations may be at greater risk at earlier ages. Our objective was to quantify age disparities among patients with type 2 diabetes in New York City. Methods Using all-payer hospital claims data for New York City, we performed a cross-sectional analysis of patients with type 2 diabetes identified from emergency department visits during the 5-year period 2011–2015. We estimated type 2 diabetes prevalence at each year of life, the age distribution of patients stratified by decade, and the average age of patients by sex, race/ethnicity, and geographic location. Results We identified 576,306 unique patients with type 2 diabetes. These patients represented more than half of all people with type 2 diabetes in New York City. Patients in racial/ethnic minority groups were on average 5.5 to 8.4 years younger than non-Hispanic white patients. At age 45, type 2 diabetes prevalence was 10.9% among non-Hispanic black patients and 5.2% among non-Hispanic white patients. In our geospatial analyses, patients with type 2 diabetes were on average 6 years younger in hotspots of diabetes-related emergency department use and inpatient hospitalizations. The average age of patients with type 2 diabetes was also 1 to 2 years younger in hotspots of microvascular diabetic complications. Conclusion We identified profound age disparities among patients with type 2 diabetes in racial/ethnic minority groups and in neighborhoods with poor health outcomes. The younger age of these patients may be due to earlier onset of diabetes and/or earlier death from diabetic complications. Our findings demonstrate the need for geographically targeted interventions that promote earlier diagnosis and better glycemic control.
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Affiliation(s)
- David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 227 East 30th St, 1st Floor, New York, New York 10016. .,Department of Population Health, New York University School of Medicine, New York, New York
| | - Ta'Loria Young
- Touro College of Osteopathic Medicine, New York, New York
| | - Christian A Koziatek
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, New York
| | - Christopher J Shim
- California Northstate University College of Medicine, Elk Grove, California
| | - Marcela Osorio
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, New York
| | - Andrew J Vinson
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, New York
| | - Joseph E Ravenell
- Department of Population Health, New York University School of Medicine, New York, New York
| | - Stephen P Wall
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, New York.,Department of Population Health, New York University School of Medicine, New York, New York
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Lee DC, de Cesar Netto C, Staggers JR, Siegel R, Chen R, Bae SY, Schon LC. Clinical and radiographic outcomes of the Kramer osteotomy in the treatment of bunionette deformity. Foot Ankle Surg 2018; 24:530-534. [PMID: 29409268 DOI: 10.1016/j.fas.2017.07.004] [Citation(s) in RCA: 3] [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: 05/02/2017] [Revised: 06/28/2017] [Accepted: 07/05/2017] [Indexed: 02/04/2023]
Abstract
BACKGROUND Bunionette deformity is a painful bony prominence of the 5th metatarsal. We evaluated outcomes of using a Kramer osteotomy to treat this condition. METHODS Retrospective study of patients treated with a Kramer osteotomy from 2003 and 2016. Outcome measures included Foot Functional Index (FFI) and radiographic measurements. RESULTS 38 patients (43 feet) with an average follow-up of 55 months. Mean postoperative FFI1 was 19.4. Mean 4-5 IMA2 improved 3.9°, from 8.3° preoperatively to 4.4° on final postoperative films (p<0.01). Mean MTP-53 angle improved 13.2° from 13.6° preoperatively to 0.4° at final follow-up (p<0.01). There were 5 delayed unions (11.6%) and 1 non-union (2.3%). CONCLUSIONS The Kramer osteotomy is an effective treatment option in patients with bunionette deformity, with significant correction of the 4-5 IM2 and MTP-53 angles and few complications.
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Affiliation(s)
- David C Lee
- Department of Orthopaedic Surgery, MedStar Union Memorial Hospital, Baltimore, MD, United States; Department of Orthopedic Surgery, Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Cesar de Cesar Netto
- Department of Orthopaedic Surgery, MedStar Union Memorial Hospital, Baltimore, MD, United States; Department of Orthopaedic Surgery, University of Alabama at Birmingham, Birmingham, AL, United States.
| | - Jackson Rucker Staggers
- Department of Orthopaedic Surgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Rebecca Siegel
- Department of Orthopaedic Surgery, MedStar Union Memorial Hospital, Baltimore, MD, United States
| | - Richard Chen
- Department of Orthopaedic Surgery, MedStar Union Memorial Hospital, Baltimore, MD, United States
| | - Su-Young Bae
- Department of Orthopaedic Surgery, MedStar Union Memorial Hospital, Baltimore, MD, United States
| | - Lew C Schon
- Department of Orthopaedic Surgery, MedStar Union Memorial Hospital, Baltimore, MD, United States
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Lee DC, Yi SS, Athens JK, Vinson AJ, Wall SP, Ravenell JE. Using Geospatial Analysis and Emergency Claims Data to Improve Minority Health Surveillance. J Racial Ethn Health Disparities 2018; 5:712-720. [PMID: 28791583 PMCID: PMC5803484 DOI: 10.1007/s40615-017-0415-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [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: 04/17/2017] [Revised: 07/16/2017] [Accepted: 07/20/2017] [Indexed: 11/24/2022]
Abstract
Traditional methods of health surveillance often under-represent racial and ethnic minorities. Our objective was to use geospatial analysis and emergency claims data to estimate local chronic disease prevalence separately for specific racial and ethnic groups. We also performed a regression analysis to identify associations between median household income and local disease prevalence among Black, Hispanic, Asian, and White adults in New York City. The study population included individuals who visited an emergency department at least once from 2009 to 2013. Our main outcomes were geospatial estimates of diabetes, hypertension, and asthma prevalence by Census tract as stratified by race and ethnicity. Using emergency claims data, we identified 4.9 million unique New York City adults with 28.5% of identifying as Black, 25.2% Hispanic, and 6.1% Asian. Age-adjusted disease prevalence was highest among Black and Hispanic adults for diabetes (13.4 and 13.1%), hypertension (28.7 and 24.1%), and asthma (9.9 and 10.1%). Correlation between disease prevalence maps demonstrated moderate overlap between Black and Hispanic adults for diabetes (0.49), hypertension (0.57), and asthma (0.58). In our regression analysis, we found that the association between low income and high disease prevalence was strongest for Hispanic adults, whereas increases in income had more modest reductions in disease prevalence for Black adults, especially for diabetes. Our geographically detailed maps of disease prevalence generate actionable evidence that can help direct health interventions to those communities with the highest health disparities. Using these novel geographic approaches, we reveal the underlying epidemiology of chronic disease for a racially and culturally diverse population.
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Affiliation(s)
- David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA.
- Department of Population Health, New York University School of Medicine, 227 East 30th Street, New York, NY, 10016, USA.
| | - Stella S Yi
- Department of Population Health, New York University School of Medicine, 227 East 30th Street, New York, NY, 10016, USA
| | - Jessica K Athens
- Department of Population Health, New York University School of Medicine, 227 East 30th Street, New York, NY, 10016, USA
| | - Andrew J Vinson
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
| | - Stephen P Wall
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, 462 First Avenue, Room A345, New York, NY, 10016, USA
- Department of Population Health, New York University School of Medicine, 227 East 30th Street, New York, NY, 10016, USA
| | - Joseph E Ravenell
- Department of Population Health, New York University School of Medicine, 227 East 30th Street, New York, NY, 10016, USA
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Adams AL, Fischer H, Kopperdahl DL, Lee DC, Black DM, Bouxsein ML, Fatemi S, Khosla S, Orwoll ES, Siris ES, Keaveny TM. Osteoporosis and Hip Fracture Risk From Routine Computed Tomography Scans: The Fracture, Osteoporosis, and CT Utilization Study (FOCUS). J Bone Miner Res 2018; 33:1291-1301. [PMID: 29665068 PMCID: PMC6155990 DOI: 10.1002/jbmr.3423] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [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: 10/03/2017] [Revised: 02/19/2018] [Accepted: 03/06/2018] [Indexed: 01/22/2023]
Abstract
Methods now exist for analyzing previously taken clinical computed tomography (CT) scans to measure a dual-energy X-ray absorptiometry (DXA)-equivalent bone mineral density (BMD) at the hip and a finite element analysis-derived femoral strength. We assessed the efficacy of this "biomechanical CT" (BCT) approach for identifying patients at high risk of incident hip fracture in a large clinical setting. Using a case-cohort design sampled from 111,694 women and men aged 65 or older who had a prior hip CT scan, a DXA within 3 years of the CT, and no prior hip fracture, we compared those with subsequent hip fracture (n = 1959) with randomly selected sex-stratified controls (n = 1979) and analyzed their CT scans blinded to all other data. We found that the age-, race-, and body mass index (BMI)-adjusted hazard ratio (HR; per standard deviation) for femoral strength was significant before (women: HR = 2.8, 95% confidence interval [CI] 2.2-3.5; men: 2.8, 2.1-3.7) and after adjusting also for the (lowest) hip BMD T-score by BCT (women: 2.1, 1.4-3.2; men: 2.7, 1.6-4.6). The hazard ratio for the hip BMD T-score was similar between BCT and DXA for both sexes (women: 2.1, 1.8-2.5 BCT versus 2.1, 1.7-2.5 DXA; men: 2.8, 2.1-3.8 BCT versus 2.5, 2.0-3.2 DXA) and was higher than for the (lowest) spine/hip BMD T-score by DXA (women: 1.6, 1.4-1.9; men: 2.1, 1.6-2.7). Compared with the latter as a clinical-practice reference and using both femoral strength and the hip BMD T-score from BCT, sensitivity for predicting hip fracture was higher for BCT (women: 0.66 versus 0.59; men: 0.56 versus 0.48), with comparable respective specificity (women: 0.66 versus 0.67; men: 0.76 versus 0.78). We conclude that BCT analysis of previously acquired routine abdominal or pelvic CT scans is at least as effective as DXA testing for identifying patients at high risk of hip fracture. © 2018 American Society for Bone and Mineral Research.
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Affiliation(s)
- Annette L Adams
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Heidi Fischer
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | | | | | - Dennis M Black
- Departments of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Mary L Bouxsein
- Orthopedic Biomechanics Laboratory, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Shireen Fatemi
- Department of Endocrinology, Kaiser Permanente Southern California, Panorama City, CA, USA
| | - Sundeep Khosla
- Kogod Center on Aging and Division of Endocrinology, Mayo Clinic, Rochester, MN, USA
| | - Eric S Orwoll
- Bone and Mineral Unit, Oregon Health and Science University, Portland, OR, USA
| | - Ethel S Siris
- Toni Stabile Osteoporosis Center, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Tony M Keaveny
- Departments of Mechanical Engineering and Bioengineering, University of California, Berkeley, CA, USA
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Lee DC, Jiang Q, Tabaei BP, Elbel B, Koziatek CA, Konty KJ, Wu WY. Using Indirect Measures to Identify Geographic Hot Spots of Poor Glycemic Control: Cross-sectional Comparisons With an A1C Registry. Diabetes Care 2018; 41:1438-1447. [PMID: 29691230 PMCID: PMC6014542 DOI: 10.2337/dc18-0181] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 03/27/2018] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Focusing health interventions in places with suboptimal glycemic control can help direct resources to neighborhoods with poor diabetes-related outcomes, but finding these areas can be difficult. Our objective was to use indirect measures versus a gold standard, population-based A1C registry to identify areas of poor glycemic control. RESEARCH DESIGN AND METHODS Census tracts in New York City (NYC) were characterized by race, ethnicity, income, poverty, education, diabetes-related emergency visits, inpatient hospitalizations, and proportion of adults with diabetes having poor glycemic control, based on A1C >9.0% (75 mmol/mol). Hot spot analyses were then performed, using the Getis-Ord Gi* statistic for all measures. We then calculated the sensitivity, specificity, positive and negative predictive values, and accuracy of using the indirect measures to identify hot spots of poor glycemic control found using the NYC A1C Registry data. RESULTS Using A1C Registry data, we identified hot spots in 42.8% of 2,085 NYC census tracts analyzed. Hot spots of diabetes-specific inpatient hospitalizations, diabetes-specific emergency visits, and age-adjusted diabetes prevalence estimated from emergency department data, respectively, had 88.9%, 89.6%, and 89.5% accuracy for identifying the same hot spots of poor glycemic control found using A1C Registry data. No other indirect measure tested had accuracy >80% except for the proportion of minority residents, which had 86.2% accuracy. CONCLUSIONS Compared with demographic and socioeconomic factors, health care utilization measures more accurately identified hot spots of poor glycemic control. In places without a population-based A1C registry, mapping diabetes-specific health care utilization may provide actionable evidence for targeting health interventions in areas with the highest burden of uncontrolled diabetes.
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Affiliation(s)
- David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY .,Department of Population Health, New York University School of Medicine, New York, NY
| | - Qun Jiang
- New York City Department of Health and Mental Hygiene, New York, NY
| | - Bahman P Tabaei
- New York City Department of Health and Mental Hygiene, New York, NY
| | - Brian Elbel
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY.,Wagner Graduate School of Public Service, New York University, New York, NY
| | - Christian A Koziatek
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY
| | - Kevin J Konty
- New York City Department of Health and Mental Hygiene, New York, NY
| | - Winfred Y Wu
- New York City Department of Health and Mental Hygiene, New York, NY
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Martin EL, Schlienz NJ, Herrmann ES, Budney AJ, Lee DC, Hampson A, Smith M, Leoutsakos JS, Stitzer ML, Vandrey RG. 1000 Targeting Sleep in Adults Seeking Treatment for Cannabis Use Disorder. Sleep 2018. [DOI: 10.1093/sleep/zsy061.999] [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] [Indexed: 11/13/2022] Open
Affiliation(s)
- E L Martin
- Johns Hopkins University School of Medicine, Baltimore, MD
| | - N J Schlienz
- Johns Hopkins University School of Medicine, Baltimore, MD
| | | | - A J Budney
- Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - D C Lee
- Johns Hopkins University School of Medicine, Baltimore, MD
| | - A Hampson
- National Institute on Drug Abuse, Baltimore, MD
| | - M Smith
- Johns Hopkins University School of Medicine, Baltimore, MD
| | - J S Leoutsakos
- Johns Hopkins University School of Medicine, Baltimore, MD
| | - M L Stitzer
- Johns Hopkins University School of Medicine, Baltimore, MD
| | - R G Vandrey
- Johns Hopkins University School of Medicine, Baltimore, MD
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44
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Lee DC, Gallagher MP, Gopalan A, Osorio M, Vinson AJ, Wall SP, Ravenell JE, Sevick MA, Elbel B. Identifying Geographic Disparities in Diabetes Prevalence Among Adults and Children Using Emergency Claims Data. J Endocr Soc 2018; 2:460-470. [PMID: 29719877 PMCID: PMC5920312 DOI: 10.1210/js.2018-00001] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 03/29/2018] [Indexed: 02/02/2023] Open
Abstract
Geographic surveillance can identify hotspots of disease and reveal associations between health and the environment. Our study used emergency department surveillance to investigate geographic disparities in type 1 and type 2 diabetes prevalence among adults and children. Using all-payer emergency claims data from 2009 to 2013, we identified unique New York City residents with diabetes and geocoded their location using home addresses. Geospatial analysis was performed to estimate diabetes prevalence by New York City Census tract. We also used multivariable regression to identify neighborhood-level factors associated with higher diabetes prevalence. We estimated type 1 and type 2 diabetes prevalence at 0.23% and 10.5%, respectively, among adults and 0.20% and 0.11%, respectively, among children in New York City. Pediatric type 1 diabetes was associated with higher income (P = 0.001), whereas adult type 2 diabetes was associated with lower income (P < 0.001). Areas with a higher proportion of nearby restaurants categorized as fast food had a higher prevalence of all types of diabetes (P < 0.001) except for pediatric type 2 diabetes. Type 2 diabetes among children was only higher in neighborhoods with higher proportions of African American residents (P < 0.001). Our findings identify geographic disparities in diabetes prevalence that may require special attention to address the specific needs of adults and children living in these areas. Our results suggest that the food environment may be associated with higher type 1 diabetes prevalence. However, our analysis did not find a robust association with the food environment and pediatric type 2 diabetes, which was predominantly focused in African American neighborhoods.
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Affiliation(s)
- David C Lee
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, New York.,Department of Population Health, New York University School of Medicine, New York, New York
| | - Mary Pat Gallagher
- Division of Endocrinology, Department of Pediatrics, New York University School of Medicine, New York, New York
| | - Anjali Gopalan
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Marcela Osorio
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, New York
| | - Andrew J Vinson
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, New York
| | - Stephen P Wall
- Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, New York
| | - Joseph E Ravenell
- Department of Population Health, New York University School of Medicine, New York, New York
| | - Mary Ann Sevick
- Department of Population Health, New York University School of Medicine, New York, New York
| | - Brian Elbel
- Department of Population Health, New York University School of Medicine, New York, New York.,Wagner Graduate School of Public Service, New York University, New York, New York
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45
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Richmond NL, Meyer ML, Hollowell AG, Isenberg EE, Domeier RM, Swor RA, Hendry PL, Peak DA, Rathlev NK, Jones JS, Lee DC, Jones CW, Platts-Mills TF. Social Support and Pain Outcomes After Trauma Exposure Among Older Adults: A Multicenter Longitudinal Study. Clin J Pain 2018; 34:366-374. [PMID: 28915155 PMCID: PMC5837905 DOI: 10.1097/ajp.0000000000000545] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [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: 02/06/2023]
Abstract
OBJECTIVES Certain forms of social support have been shown to improve pain-coping behaviors and pain outcomes in older adults with chronic pain, but little is known about the effect of social support on pain outcomes in older adults following trauma exposure. METHODS We analyzed data from a prospective longitudinal study of adults aged 65 years and older presenting to an emergency department after a motor vehicle collision (MVC) to characterize the relationship between perceived social support and MVC-related pain after trauma overall and by subgroups based on sex, depressive symptoms, and marital status. RESULTS In our sample (N=176), patients with low perceived social support had higher pain severity 6 weeks after MVC than patients with high perceived social support after adjustment for age, sex, race, and education (4.2 vs. 3.2, P=0.04). The protective effect of social support on pain severity at 6 weeks was more pronounced in men and in married individuals. Patients with low social support were less likely to receive an opioid prescription in the emergency department (15% vs. 32%, P=0.03), but there was no difference in opioid use at 6 weeks (22% vs. 20%, P=0.75). DISCUSSION Among older adults experiencing trauma, low perceived social support was associated with higher levels of pain at 6 weeks.
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Affiliation(s)
| | | | | | | | - Robert M Domeier
- Department of Emergency Medicine, Chapel Hill, NC, St. Joseph Mercy Health System, Ann Arbor
| | - Robert A Swor
- Department of Emergency Medicine, William Beaumont Hospital, Royal Oak, MI
| | - Phyllis L Hendry
- Department of Emergency Medicine, University of Florida College of Medicine Jacksonville, Jacksonville, FL
| | - David A Peak
- Department of Emergency Medicine, Massachusetts General Hospital, Boston
| | - Niels K Rathlev
- Department of Emergency Medicine, Baystate Medical Center, Springfield, MA
| | - Jeffrey S Jones
- Department of Emergency Medicine, Spectrum Health-Butterworth Campus, Grand Rapids, MI
| | - David C Lee
- Department of Emergency Medicine, North Shore University Hospital, Evanston, IL
| | | | - Timothy F Platts-Mills
- Departments of Emergency Medicine
- Anesthesiology, UNC Division of Geriatrics and Center for Aging and Health, University of North Carolina
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46
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Lee DC, Hoffmann PF, Kopperdahl DL, Keaveny TM. Phantomless calibration of CT scans for measurement of BMD and bone strength-Inter-operator reanalysis precision. Bone 2017; 103:325-333. [PMID: 28778598 PMCID: PMC5636218 DOI: 10.1016/j.bone.2017.07.029] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [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: 10/21/2016] [Revised: 06/01/2017] [Accepted: 07/21/2017] [Indexed: 01/22/2023]
Abstract
Patient-specific phantomless calibration of computed tomography (CT) scans has the potential to simplify and expand the use of pre-existing clinical CT for quantitative bone densitometry and bone strength analysis for diagnostic and monitoring purposes. In this study, we quantified the inter-operator reanalysis precision errors for a novel implementation of patient-specific phantomless calibration, using air and either aortic blood or hip adipose tissue as internal calibrating reference materials, and sought to confirm the equivalence between phantomless and (traditional) phantom-based measurements. CT scans of the spine and hip for 25 women and 15 men (mean±SD age of 67±9years, range 41-86years), one scan per anatomic site per patient, were analyzed independently by two analysts using the VirtuOst software (O.N. Diagnostics, Berkeley, CA). The scans were acquired at 120kVp, with a slice thickness/increment of 3mm or less, on nine different CT scanner models across 24 different scanners. The main parameters assessed were areal bone mineral density (BMD) at the hip (total hip and femoral neck), trabecular volumetric BMD at the spine, and vertebral and femoral strength by finite element analysis; other volumetric BMD measures were also assessed. We found that the reanalysis precision errors for all phantomless measurements were ≤0.5%, which was as good as for phantom calibration. Regression analysis indicated equivalence of the phantom- versus phantomless-calibrated measurements (slope not different than unity, R2≥0.98). Of the main parameters assessed, non-significant paired mean differences (n=40) between the two measurements ranged from 0.6% for hip areal BMD to 1.1% for mid-vertebral trabecular BMD. These results indicate that phantom-equivalent measurements of both BMD and finite element-derived bone strength can be reliably obtained from CT scans using patient-specific phantomless calibration.
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Affiliation(s)
| | | | | | - Tony M Keaveny
- Department of Mechanical Engineering, University of California, Berkeley, CA, USA; Department of Bioengineering, University of California, Berkeley, CA, USA.
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47
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DiMaggio CJ, Avraham JB, Lee DC, Frangos SG, Wall SP. The Epidemiology of Emergency Department Trauma Discharges in the United States. Acad Emerg Med 2017; 24:1244-1256. [PMID: 28493608 DOI: 10.1111/acem.13223] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 02/16/2017] [Accepted: 02/20/2017] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Injury-related morbidity and mortality is an important emergency medicine and public health challenge in the United States. Here we describe the epidemiology of traumatic injury presenting to U.S. emergency departments (EDs), define changes in types and causes of injury among the elderly and the young, characterize the role of trauma centers and teaching hospitals in providing emergency trauma care, and estimate the overall economic burden of treating such injuries. METHODS We conducted a secondary retrospective, repeated cross-sectional study of the Nationwide Emergency Department Data Sample (NEDS), the largest all-payer ED survey database in the United States. Main outcomes and measures were survey-adjusted counts, proportions, means, and rates with associated standard errors (SEs) and 95% confidence intervals. We plotted annual age-stratified ED discharge rates for traumatic injury and present tables of proportions of common injuries and external causes. We modeled the association of Level I or II trauma center care with injury fatality using a multivariable survey-adjusted logistic regression analysis that controlled for age, sex, injury severity, comorbid diagnoses, and teaching hospital status. RESULTS There were 181,194,431 (SE = 4,234) traumatic injury discharges from U.S. EDs between 2006 and 2012. There was a mean year-to-year decrease of 143 (95% CI = -184.3 to -68.5) visits per 100,000 U.S. population during the study period. The all-age, all-cause case-fatality rate for traumatic injuries across U.S. EDs during the study period was 0.17% (SE = 0.001%). The case-fatality rate for the most severely injured averaged 4.8% (SE = 0.001%), and severely injured patients were nearly four times as likely to be seen in Level I or II trauma centers (relative risk = 3.9 [95% CI = 3.7 to 4.1]). The unadjusted risk ratio, based on group counts, for the association of Level I or II trauma centers with mortality was risk ratio = 4.9 (95% CI = 4.5 to 5.3); however, after sex, age, injury severity, and comorbidities were accounted for, Level I or II trauma centers were not associated with an increased risk of fatality (odds ratio = 0.96 [95% CI = 0.79 to 1.18]). There were notable changes at the extremes of age in types and causes of ED discharges for traumatic injury between 2009 and 2012. Age-stratified rates of diagnoses of traumatic brain injury increased 29.5% (SE = 2.6%) for adults older than 85 and increased 44.9% (SE = 1.3%) for children younger than 18. Firearm-related injuries increased 31.7% (SE = 0.2%) in children 5 years and younger. The total inflation-adjusted cost of ED injury care in the United States between 2006 and 2012 was $99.75 billion (SE = $0.03 billion). CONCLUSIONS Emergency departments are a sensitive barometer of the continuing impact of traumatic injury as an important cause of morbidity and mortality in the United States. Level I or II trauma centers remain a bulwark against the tide of severe trauma in the United States, but the types and causes of traumatic injury in the United States are changing in consequential ways, particularly at the extremes of age, with traumatic brain injuries and firearm-related trauma presenting increased challenges.
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Affiliation(s)
- Charles J. DiMaggio
- Department of Surgery; Division of Acute Care and Trauma Surgery; New York University School of Medicine; New York NY
- Department of Population Health; New York University School of Medicine; New York NY
| | - Jacob B. Avraham
- Department of Surgery; Division of Acute Care and Trauma Surgery; New York University School of Medicine; New York NY
| | - David C. Lee
- Ronald O. Perelman Department of Emergency Medicine; New York University School of Medicine; New York NY
- Department of Population Health; New York University School of Medicine; New York NY
| | - Spiros G. Frangos
- Department of Surgery; Division of Acute Care and Trauma Surgery; New York University School of Medicine; New York NY
| | - Stephen P. Wall
- Ronald O. Perelman Department of Emergency Medicine; New York University School of Medicine; New York NY
- Department of Population Health; New York University School of Medicine; New York NY
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48
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Platts-Mills TF, Nebolisa BC, Flannigan SA, Richmond NL, Domeier RM, Swor RA, Hendry PL, Peak DA, Rathlev NK, Jones JS, Lee DC, Jones CW, McLean SA. Post-Traumatic Stress Disorder among Older Adults Experiencing Motor Vehicle Collision: A Multicenter Prospective Cohort Study. Am J Geriatr Psychiatry 2017; 25:953-963. [PMID: 28506605 PMCID: PMC5563265 DOI: 10.1016/j.jagp.2017.03.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [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: 11/01/2016] [Revised: 03/17/2017] [Accepted: 03/20/2017] [Indexed: 01/27/2023]
Abstract
OBJECTIVE To characterize risk factors for and consequences of post-traumatic stress disorder (PTSD) among older adults evaluated in the emergency department (ED) following motor vehicle collision (MVC). DESIGN Prospective multicenter longitudinal study (2011-2015). SETTING 9 EDs across the United States. PARTICIPANTS Adults aged 65 years and older who presented to an ED after MVC without severe injuries. MEASUREMENTS PTSD symptoms were assessed 6 months after the ED visit using the Impact of Event Scale-Revised. RESULTS Of 223 patients, clinically significant PTSD symptoms at 6 months were observed in 21% (95% CI 16%-26%). PTSD symptoms were more common in patients who did not have a college degree, had depressive symptoms prior to the MVC, perceived the MVC as life-threatening, had severe ED pain, and expected their physical or emotional recovery time to be greater than 30 days. Three factors (ED pain severity [0-10 scale], perceived life-threatening MVC [0-10 scale], and pre-MVC depressive symptoms [yes to either of two questions]), predicted 6-month PTSD symptoms with an area under the curve of 0.76. Compared to patients without PTSD symptoms, those with PTSD symptoms were at higher risk for persistent pain (72% versus 30%), functional decline (67% versus 42%), and new disability (49% versus 18%). CONCLUSIONS Among older adults treated in the ED following MVC, clinically significant PTSD symptoms at 6 months were present in 21% of patients and were associated with adverse health outcomes. Increased risk for PTSD development can be identified with moderate accuracy using information readily available in the ED.
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Affiliation(s)
| | - Bo C. Nebolisa
- University of North Carolina at Chapel Hill, School of Medicine
| | - Sean A. Flannigan
- University of North Carolina at Chapel Hill, Department of Emergency Medicine
| | | | | | - Robert A. Swor
- William Beaumont Hospital, Department of Emergency Medicine
| | - Phyllis L. Hendry
- University of Florida College of Medicine Jacksonville, Department of Emergency Medicine
| | - David A. Peak
- Massachusetts General Hospital, Department of Emergency Medicine
| | | | - Jeffrey S. Jones
- Spectrum Health — Butterworth Campus, Department of Emergency Medicine
| | - David C. Lee
- North Shore University Hospital, Department of Emergency Medicine
| | | | - Samuel A. McLean
- University of North Carolina at Chapel Hill, Department of Emergency Medicine
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49
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Farge D, Burt RK, Oliveira MC, Mousseaux E, Rovira M, Marjanovic Z, de Vries-Bouwstra J, Del Papa N, Saccardi R, Shah SJ, Lee DC, Denton C, Alexander T, Kiely DG, Snowden JA. Cardiopulmonary assessment of patients with systemic sclerosis for hematopoietic stem cell transplantation: recommendations from the European Society for Blood and Marrow Transplantation Autoimmune Diseases Working Party and collaborating partners. Bone Marrow Transplant 2017; 52:1495-1503. [PMID: 28530671 PMCID: PMC5671927 DOI: 10.1038/bmt.2017.56] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Accepted: 01/29/2017] [Indexed: 02/07/2023]
Abstract
Systemic sclerosis (SSc) is a rare disabling autoimmune disease with a similar mortality to many cancers. Two randomized controlled trials of autologous hematopoietic stem cell transplantation (AHSCT) for SSc have shown significant improvement in organ function, quality of life and long-term survival compared to standard therapy. However, transplant-related mortality (TRM) ranged from 3–10% in patients undergoing HSCT. In SSc, the main cause of non-transplant and TRM is cardiac related. We therefore updated the previously published guidelines for cardiac evaluation, which should be performed in dedicated centers with expertize in HSCT for SSc. The current recommendations are based on pre-transplant cardiopulmonary evaluations combining pulmonary function tests, echocardiography, cardiac magnetic resonance imaging and invasive hemodynamic testing, initiated at Northwestern University (Chicago) and subsequently discussed and endorsed within the EBMT ADWP in 2016.
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Affiliation(s)
- D Farge
- Department of Internal Medicine, Unité Clinique de Médecine Interne, Maladies Auto-immunes et Pathologie Vasculaire, UF 04, Hôpital Saint-Louis, AP-HP Assistance Publique des Hôpitaux de Paris, INSERM UMRS 1160, Paris Denis Diderot University, Paris, France
| | - R K Burt
- Department of Medicine, Division of Immunotherapy, Northwestern University, Chicago, IL, USA
| | - M-C Oliveira
- Departamento de Clínica Médica, Center for Cell-based Therapy, Regional Blood Center of Ribeirão Preto, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | - E Mousseaux
- Hôpital Européen Georges Pompidou, AP-HP Assistance Publique des Hôpitaux de Paris, INSERM UMR 970, Université Paris Descartes, Paris, France
| | - M Rovira
- Department of Hematology, HSCT Unit, Hospital Clinic, Barcelona, Spain
| | - Z Marjanovic
- Department of Hematology, Saint-Antoine Hospital Paris, Assistance Publique des Hôpitaux de Paris, APHP, Paris, France
| | | | - N Del Papa
- Department of Rheumatology, Scleroderma Clinic, Osp. G. Pini, Milan, Italy
| | - R Saccardi
- Department of Hematology, Cord Blood Bank, Careggi University Hospital, Florence, Italy
| | - S J Shah
- Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - D C Lee
- Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - C Denton
- UCL Division of Medicine Royal Free Campus, London, UK
| | - T Alexander
- Department of Rheumatology and Clinical Immunology, Charité University Medicine Berlin, Berlin, Germany
| | - D G Kiely
- Sheffield Pulmonary Vascular Disease Unit, M-floor, Royal Hallamshire Hospital, Sheffield, UK
| | - J A Snowden
- Department of Haematology, Sheffield Teaching Hospitals NHS Foundation Trust, University of Sheffield, Sheffield, UK
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50
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Lee DC, Yi SS, Fong HF, Athens JK, Ravenell JE, Sevick MA, Wall SP, Elbel B. Identifying Local Hot Spots of Pediatric Chronic Diseases Using Emergency Department Surveillance. Acad Pediatr 2017; 17:267-274. [PMID: 28385326 PMCID: PMC5385887 DOI: 10.1016/j.acap.2016.10.017] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [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: 06/24/2016] [Revised: 10/25/2016] [Accepted: 10/28/2016] [Indexed: 01/30/2023]
Abstract
OBJECTIVE To use novel geographic methods and large-scale claims data to identify the local distribution of pediatric chronic diseases in New York City. METHODS Using a 2009 all-payer emergency claims database, we identified the proportion of unique children aged 0 to 17 with diagnosis codes for specific medical and psychiatric conditions. As a proof of concept, we compared these prevalence estimates to traditional health surveys and registry data using the most geographically granular data available. In addition, we used home addresses to map local variation in pediatric disease burden. RESULTS We identified 549,547 New York City children who visited an emergency department at least once in 2009. Though our sample included more publicly insured and uninsured children, we found moderate to strong correlations of prevalence estimates when compared to health surveys and registry data at prespecified geographic levels. Strongest correlations were found for asthma and mental health conditions by county among younger children (0.88, P = .05 and 0.99, P < .01, respectively). Moderate correlations by neighborhood were identified for obesity and cancer (0.53 and 0.54, P < .01). Among adolescents, correlations by health districts were strong for obesity (0.95, P = .05), and depression estimates had a nonsignificant, but strong negative correlation with suicide attempts (-0.88, P = .12). Using SaTScan, we also identified local hot spots of pediatric chronic disease. CONCLUSIONS For conditions easily identified in claims data, emergency department surveillance may help estimate pediatric chronic disease prevalence with higher geographic resolution. More studies are needed to investigate limitations of these methods and assess reliability of local disease estimates.
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Affiliation(s)
- David C. Lee
- Ronald O. Perelman Department of Emergency Medicine, NYU School of Medicine, 462 First Avenue, Room A345, New York, NY 10016,Department of Population Health, NYU School of Medicine, 227 East 30th Street, New York, NY 10016
| | - Stella S. Yi
- Department of Population Health, NYU School of Medicine, 227 East 30th Street, New York, NY 10016
| | - Hiu-Fai Fong
- Division of General Pediatrics, Department of Medicine, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115,Department of Pediatrics, Harvard Medical School, 25 Shattuck Street; Boston, MA 02115
| | - Jessica K. Athens
- Department of Population Health, NYU School of Medicine, 227 East 30th Street, New York, NY 10016
| | - Joseph E. Ravenell
- Department of Population Health, NYU School of Medicine, 227 East 30th Street, New York, NY 10016
| | - Mary Ann Sevick
- Department of Population Health, NYU School of Medicine, 227 East 30th Street, New York, NY 10016
| | - Stephen P. Wall
- Ronald O. Perelman Department of Emergency Medicine, NYU School of Medicine, 462 First Avenue, Room A345, New York, NY 10016
| | - Brian Elbel
- Department of Population Health, NYU School of Medicine, 227 East 30th Street, New York, NY 10016,Wagner Graduate School of Public Service, New York University, 295 Lafayette Street, New York, NY 10012
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