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Perrin EC, South AM, Cius EG. Disordered eating among military adolescents presenting for annual health visits at a naval clinic. Eat Behav 2025; 57:101949. [PMID: 39965303 DOI: 10.1016/j.eatbeh.2025.101949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2024] [Revised: 02/04/2025] [Accepted: 02/04/2025] [Indexed: 02/20/2025]
Abstract
INTRODUCTION The purpose of this study was to estimate disordered eating behavior (DEB) prevalence in military dependent adolescents, compare it to previous reports in the general adolescent population, and investigate whether obesity, sex and gender, or key military-specific demographics (parent in the military, parental active duty [AD] status, military branch, number of lifetime moves, number of parental deployments) are associated with higher DEB risk. METHODS Retrospective cross-sectional study of military dependents aged 11-19 years seen in an adolescent clinic at a naval medical center for annual health maintenance visits. We manually abstracted body mass index, gender, sex, military demographics, and ChEAT-26 eating disorder screening results from electronic health records. We compared DEB prevalence to established estimates from the general adolescent population (p0 = 0.1) and estimated DEB risk by obesity, gender, sex, and military demographics. RESULTS Of 92 participants, 49 % identified as male; 9 % had obesity, 63 % had an AD parent, and 81 % were Navy families. DEB prevalence was 13 %, no different from the general population. Obesity and having a parent in the Air Force were associated with higher ChEAT-26 score. There was no significant difference in DEB risk by gender or sex. CONCLUSIONS DEB prevalence in military-dependent adolescents is estimated at 13 %, similar to previous reports in the general population, and obesity is associated with higher DEB risk. Military dependent males may have comparable DEB risk to females, reinforcing the importance of universal DEB screening in adolescents, and of changing the narrative of who is at risk for DEB.
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Affiliation(s)
- Ella C Perrin
- Department of Pediatrics, Naval Medical Center San Diego, 34800 Bob Wilson Drive, San Diego, CA 92134, United States of America.
| | - Andrew M South
- Department of Pediatrics, Section of Nephrology, Atrium Health Levine Children's Brenner Children's Hospital, Wake Forest School of Medicine, Medical Center Boulevard, Winston Salem, NC 27157, United States of America.
| | - Elizabeth G Cius
- Department of Pediatrics, Naval Medical Center San Diego, 34800 Bob Wilson Drive, San Diego, CA 92134, United States of America.
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South AM, Giammattei VC, Bagley KW, Bakhoum CY, Beasley WH, Bily MB, Biswas S, Bridges AM, Byfield RL, Campbell JF, Chanchlani R, Chen A, D'Agostino McGowan L, Downs SM, Fergeson GM, Greenberg JH, Hill-Horowitz TA, Jensen ET, Kallash M, Kamel M, Kiessling SG, Kline DM, Laisure JR, Liu G, Londeree J, Lucas CB, Mannemuddhu SS, Mao KR, Misurac JM, Murphy MO, Nugent JT, Onugha EA, Pudupakkam A, Redmond KM, Riar S, Sethna CB, Siddiqui S, Thumann AL, Uss SR, Vincent CL, Viviano IV, Walsh MJ, White BD, Woroniecki RP, Wu M, Yamaguchi I, Yun E, Weaver DJ. The Study of the Epidemiology of Pediatric Hypertension Registry (SUPERHERO): rationale and methods. Am J Epidemiol 2024; 193:1650-1661. [PMID: 38881045 PMCID: PMC11637526 DOI: 10.1093/aje/kwae116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 04/29/2024] [Accepted: 06/07/2024] [Indexed: 06/18/2024] Open
Abstract
Despite increasing prevalence of hypertension in youth and high adult cardiovascular mortality rates, the long-term consequences of youth-onset hypertension remain unknown. This is due to limitations of prior research, such as small sample sizes, reliance on manual record review, and limited analytic methods, that did not address major biases. The Study of the Epidemiology of Pediatric Hypertension (SUPERHERO) is a multisite, retrospective registry of youth evaluated by subspecialists for hypertension disorders. Sites obtain harmonized electronic health record data using standardized biomedical informatics scripts validated with randomized manual record review. Inclusion criteria are index visit for International Classification of Diseases, 10th Revision (ICD-10) code-defined hypertension disorder on or after January 1, 2015, and age < 19 years. We exclude patients with ICD-10 code-defined pregnancy, kidney failure on dialysis, or kidney transplantation. Data include demographics, anthropomorphics, US Census Bureau tract, histories, blood pressure, ICD-10 codes, medications, laboratory and imaging results, and ambulatory blood pressure. SUPERHERO leverages expertise in epidemiology, statistics, clinical care, and biomedical informatics to create the largest and most diverse registry of youth with newly diagnosed hypertension disorders. SUPERHERO's goals are to reduce CVD burden across the life course and establish gold-standard biomedical informatics methods for youth with hypertension disorders.
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Affiliation(s)
- Andrew M South
- Section of Nephrology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
- Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Victoria C Giammattei
- Section of Nephrology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Kiri W Bagley
- Section of Nephrology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Christine Y Bakhoum
- Section of Nephrology, Department of Pediatrics, Yale University School of Medicine, New Haven, CT 06519, United States
| | - William H Beasley
- Developmental and Behavioral Pediatrics, Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, United States
| | - Morgan B Bily
- Division of Nephrology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, United States
| | - Shupti Biswas
- Department of Pediatrics, Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, New Hyde Park, NY 11040, United States
| | - Aaron M Bridges
- Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
- Clinical and Translational Science Institute, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Rushelle L Byfield
- Division of Nephrology and Hypertension, Department of Pediatrics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, United States
| | - Jessica Fallon Campbell
- Division of Nephrology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, United States
| | - Rahul Chanchlani
- Division of Nephrology, Department of Pediatrics, McMaster University, Hamilton, ON L8N 1H4, Canada
| | - Ashton Chen
- Section of Nephrology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Lucy D'Agostino McGowan
- Department of Statistical Sciences, Wake Forest University, Winston Salem, NC 27157, United States
| | - Stephen M Downs
- Department of Pediatrics-General, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Gina M Fergeson
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, United States
| | - Jason H Greenberg
- Section of Nephrology, Department of Pediatrics, Yale University School of Medicine, New Haven, CT 06519, United States
| | - Taylor A Hill-Horowitz
- Division of Nephrology, Department of Pediatrics, Cohen Children’s Medical Center, Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, NY 11040, United States
| | - Elizabeth T Jensen
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Mahmoud Kallash
- Division of Nephrology and Hypertension, Department of Pediatrics, Ohio State College of Medicine, Columbus, OH 43205, United States
| | - Margret Kamel
- Division of Nephrology, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, United States
| | - Stefan G Kiessling
- Division of Nephrology, Department of Pediatrics, University of Kentucky College of Medicine, Lexington, KY 40506, United States
| | - David M Kline
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - John R Laisure
- Section of Nephrology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Gang Liu
- Division of Pediatric Research, Department of Pediatrics, Atrium Health Levine Children's, Charlotte, NC 28207, United States
| | - Jackson Londeree
- Division of Nephrology, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, United States
| | - Caroline B Lucas
- Section of Nephrology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Sai Sudha Mannemuddhu
- Division of Pediatric Nephrology, East Tennessee Children's Hospital, University of Tennessee at Knoxville, Knoxville, TN 37916, United States
| | - Kuo-Rei Mao
- IS Enterprise Reporting, Texas Children's Hospital, Baylor College of Medicine, Houston, TX 77030, United States
| | - Jason M Misurac
- Division of Nephrology, Dialysis, and Transplantation, Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA 52242, United States
| | - Margaret O Murphy
- Division of Nephrology, Department of Pediatrics, University of Kentucky College of Medicine, Lexington, KY 40506, United States
| | - James T Nugent
- Section of Nephrology, Department of Pediatrics, Yale University School of Medicine, New Haven, CT 06519, United States
| | - Elizabeth A Onugha
- Division of Nephrology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, United States
| | - Ashna Pudupakkam
- Division of Nephrology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, United States
| | - Kathy M Redmond
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, United States
| | - Sandeep Riar
- Division of Nephrology, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, United States
| | - Christine B Sethna
- Division of Nephrology, Department of Pediatrics, Cohen Children’s Medical Center, Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, NY 11040, United States
| | - Sahar Siddiqui
- Division of Nephrology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, United States
| | - Ashley L Thumann
- General and Community Pediatrics, Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, United States
| | - Stephen R Uss
- Yale Center for Clinical Investigation, Yale University School of Medicine, New Haven, CT 06519, United States
| | - Carol L Vincent
- Section of Nephrology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Irina V Viviano
- Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
- Clinical and Translational Science Institute, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Michael J Walsh
- Section of Cardiology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC 27157, United States
| | - Blanche D White
- Division of Nephrology and Hypertension, Department of Pediatrics, Atrium Health Levine Children's, Charlotte, NC 28203, United States
| | - Robert P Woroniecki
- Division of Nephrology, Department of Pediatrics, Stony Brook Medicine, Stony Brook, NY 11794, United States
| | - Michael Wu
- McMaster University School of Medicine, Hamilton, ON L8N 1H4, Canada
| | - Ikuyo Yamaguchi
- Department of Pediatrics, Division of Nephrology, University of Oklahoma College of Medicine, Oklahoma City, OK 73104, United States
| | - Emily Yun
- Division of Nephrology, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, United States
| | - Donald J Weaver
- Division of Nephrology and Hypertension, Department of Pediatrics, Atrium Health Levine Children's, Charlotte, NC 28203, United States
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Brouwer ECJ, Floyd WN, Jensen ET, O'Connell N, Shaltout HA, Washburn LK, South AM. Risk of Obesity and Unhealthy Central Adiposity in Adolescents Born Preterm With Very Low Birthweight Compared to Term-Born Peers. Child Obes 2024; 20:485-493. [PMID: 38387005 PMCID: PMC11535456 DOI: 10.1089/chi.2023.0115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Background: Early-life factors such as preterm birth or very low birthweight (VLBW) are associated with increased cardiovascular disease risk. However, it remains unknown whether this is due to an increased risk of obesity (unhealthy central adiposity) because studies have predominantly defined obesity based on BMI, an imprecise adiposity measure. Objective: Investigate if adolescents born preterm with VLBW have a higher risk of unhealthy central adiposity compared to term-born peers. Study Design: Cross-sectional analysis of data from a prospective cohort study of 177 individuals born preterm with VLBW (<1500 g) and 51 term-born peers (birthweight ≥2500 g). Individuals with congenital anomalies, genetic syndromes, or major health conditions were excluded. Height, weight, waist circumference, skin fold thickness, and dual energy X-ray absorptiometry body composition were measured at age 14 years. We calculated BMI percentiles and defined overweight/obesity as BMI ≥85th percentile for age and sex. We estimated the preterm-term differences in overweight/obesity prevalence and adiposity distribution with multivariable generalized linear models. Results: There was no difference in small for gestational age status or overweight/obesity prevalence. Compared to term, youth born preterm with VLBW had lower BMI z-score [β -0.38, 95% confidence limits (CL) -0.75 to -0.02] but no differences in adiposity apart from subscapular-to-triceps ratio (STR; β 0.18, 95% CL 0.08 to 0.28). Conclusions: Adolescents born preterm with VLBW had smaller body size than their term-born peers and had no differences in central adiposity except greater STR.
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Affiliation(s)
| | - Whitney N. Floyd
- Wake Forest University School of Medicine, Winston Salem, NC, USA
| | - Elizabeth T. Jensen
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC, USA
| | - Nathaniel O'Connell
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC, USA
| | - Hossam A. Shaltout
- Department of Obstetrics and Gynecology and Wake Forest University School of Medicine, Winston Salem, NC, USA
| | - Lisa K. Washburn
- Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC, USA
| | - Andrew M. South
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC, USA
- Section of Nephrology, Department of Pediatrics, Brenner Children's, Wake Forest University School of Medicine, Winston Salem, NC, USA
- Center on Diabetes, Obesity and Metabolism, Wake Forest University School of Medicine, Winston Salem, NC, USA
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Gassen J, Mengelkoch S, Slavich GM. Human immune and metabolic biomarker levels, and stress-biomarker associations, differ by season: Implications for biomedical health research. Brain Behav Immun Health 2024; 38:100793. [PMID: 38813082 PMCID: PMC11133497 DOI: 10.1016/j.bbih.2024.100793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 05/02/2024] [Indexed: 05/31/2024] Open
Abstract
Although seasonal changes in physiology are well documented, little is known about how human immune and metabolic markers vary across seasons, and no studies have examined how stress → health biomarker associations differ across the year. To investigate these issues, we analyzed data from 2118 participants of the Midlife in the United States (MIDUS) study to determine whether there were differences in (a) levels of 19 immune and metabolic markers, and (b) the association between perceived stress and each biomarker across the year. Results of component-wide boosted generalized additive models revealed seasonal patterning for most biomarkers, with immune proteins generally peaking when days were shorter. Moreover, whereas levels of hemoglobin A1C rose from late fall to spring, triglycerides were elevated in the summer and fall, and high-density lipoprotein decreased steadily from January to December. Urinary cortisol and cortisone exhibited opposite patterns, peaking at the beginning and end of the year, respectively. Most critically, we found that the effects of perceived stress on 18 of the 19 health biomarkers assessed varied by month of measurement. In some cases, these differences involved the magnitude of the stress → biomarker association but, in other cases, it was the direction of the effect that changed. Studies that do not account for month of biomarker assessment may thus yield misleading or unreproducible results.
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Affiliation(s)
- Jeffrey Gassen
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - Summer Mengelkoch
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
| | - George M. Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA
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Tully NW, Chappell MC, Evans JK, Jensen ET, Shaltout HA, Washburn LK, South AM. The role of preterm birth in stress-induced sodium excretion in young adults. J Hypertens 2024; 42:1086-1093. [PMID: 38690907 PMCID: PMC11068094 DOI: 10.1097/hjh.0000000000003705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
BACKGROUND Early-life programming due to prematurity and very low birth weight (VLBW, <1500 g) is believed to contribute to development of hypertension, but the mechanisms remain unclear. Experimental data suggest that altered pressure natriuresis (increased renal perfusion pressure promoting sodium excretion) may be a contributing mechanism. We hypothesize that young adults born preterm will have a blunted pressure natriuresis response to mental stress compared with those born term. METHODS In this prospective cohort study of 190 individuals aged 18-23 years, 156 born preterm with VLBW and 34 controls born term with birth weight at least 2500 g, we measured urine sodium/creatinine before and after a mental stress test and continuous blood pressure before and during the stress test. Participants were stratified into groups by the trajectory at which mean arterial pressure (MAP) increased following the test. The group with the lowest MAP trajectory was the reference group. We used generalized linear models to assess poststress urine sodium/creatinine relative to the change in MAP trajectory and assessed the difference between groups by preterm birth status. RESULTS Participants' mean age was 19.8 years and 57% were women. Change in urine sodium/creatinine per unit increase in MAP when comparing middle trajectory group against the reference group was greater in those born preterm [β 5.4%, 95% confidence interval (95% CI) -11.4 to 5.3] than those born term (β 38.5%, 95% CI -0.04 to 92.0), interaction term P = 0.002. CONCLUSION We observed that, as blood pressure increased following mental stress, young adults born preterm exhibited decreased sodium excretion relative to term-born individuals.
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Affiliation(s)
| | - Mark C. Chappell
- Department of Surgery-Hypertension and Vascular Research, Wake Forest University School of Medicine
| | - Joni K. Evans
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine
| | - Elizabeth T. Jensen
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine
| | - Hossam A. Shaltout
- Department of Surgery-Hypertension and Vascular Research, Wake Forest University School of Medicine
- Department of Obstetrics and Gynecology, Wake Forest University School of Medicine
| | - Lisa K. Washburn
- Department of Pediatrics, Wake Forest University School of Medicine
| | - Andrew M. South
- Department of Surgery-Hypertension and Vascular Research, Wake Forest University School of Medicine
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine
- Section of Nephrology, Department of Pediatrics, Wake Forest University School of Medicine, Winston Salem, NC, USA
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Martinuka O, Hazard D, Marateb HR, Mansourian M, Mañanas MÁ, Romero S, Rubio-Rivas M, Wolkewitz M. Methodological biases in observational hospital studies of COVID-19 treatment effectiveness: pitfalls and potential. Front Med (Lausanne) 2024; 11:1362192. [PMID: 38576716 PMCID: PMC10991758 DOI: 10.3389/fmed.2024.1362192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 02/20/2024] [Indexed: 04/06/2024] Open
Abstract
Introduction This study aims to discuss and assess the impact of three prevalent methodological biases: competing risks, immortal-time bias, and confounding bias in real-world observational studies evaluating treatment effectiveness. We use a demonstrative observational data example of COVID-19 patients to assess the impact of these biases and propose potential solutions. Methods We describe competing risks, immortal-time bias, and time-fixed confounding bias by evaluating treatment effectiveness in hospitalized patients with COVID-19. For our demonstrative analysis, we use observational data from the registry of patients with COVID-19 who were admitted to the Bellvitge University Hospital in Spain from March 2020 to February 2021 and met our predefined inclusion criteria. We compare estimates of a single-dose, time-dependent treatment with the standard of care. We analyze the treatment effectiveness using common statistical approaches, either by ignoring or only partially accounting for the methodological biases. To address these challenges, we emulate a target trial through the clone-censor-weight approach. Results Overlooking competing risk bias and employing the naïve Kaplan-Meier estimator led to increased in-hospital death probabilities in patients with COVID-19. Specifically, in the treatment effectiveness analysis, the Kaplan-Meier estimator resulted in an in-hospital mortality of 45.6% for treated patients and 59.0% for untreated patients. In contrast, employing an emulated trial framework with the weighted Aalen-Johansen estimator, we observed that in-hospital death probabilities were reduced to 27.9% in the "X"-treated arm and 40.1% in the non-"X"-treated arm. Immortal-time bias led to an underestimated hazard ratio of treatment. Conclusion Overlooking competing risks, immortal-time bias, and confounding bias leads to shifted estimates of treatment effects. Applying the naïve Kaplan-Meier method resulted in the most biased results and overestimated probabilities for the primary outcome in analyses of hospital data from COVID-19 patients. This overestimation could mislead clinical decision-making. Both immortal-time bias and confounding bias must be addressed in assessments of treatment effectiveness. The trial emulation framework offers a potential solution to address all three methodological biases.
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Affiliation(s)
- Oksana Martinuka
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Derek Hazard
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Hamid Reza Marateb
- Biomedical Engineering Research Center (CREB), Automatic Control Department (ESAII), Universitat Politècnica de Catalunya-Barcelona Tech (UPC), Barcelona, Spain
- Department of Artificial Intelligence, Smart University of Medical Sciences, Tehran, Iran
| | - Marjan Mansourian
- Biomedical Engineering Research Center (CREB), Automatic Control Department (ESAII), Universitat Politècnica de Catalunya-Barcelona Tech (UPC), Barcelona, Spain
- Department of Epidemiology and Biostatistics, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Miguel Ángel Mañanas
- Biomedical Engineering Research Center (CREB), Automatic Control Department (ESAII), Universitat Politècnica de Catalunya-Barcelona Tech (UPC), Barcelona, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Sergio Romero
- Biomedical Engineering Research Center (CREB), Automatic Control Department (ESAII), Universitat Politècnica de Catalunya-Barcelona Tech (UPC), Barcelona, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Manuel Rubio-Rivas
- Department of Internal Medicine, Bellvitge University Hospital, Hospitalet de Llobregat, Barcelona, Spain
| | - Martin Wolkewitz
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
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South AM, Rigdon J, Voruganti S, Stafford JM, Dabelea D, Marcovina S, Mottl AK, Pihoker C, Urbina EM, Jensen ET. Uric Acid Is Not Associated With Cardiovascular Health in Youth With Type 1 Diabetes: SEARCH for Diabetes in Youth Study. J Clin Endocrinol Metab 2024; 109:e726-e734. [PMID: 37690117 PMCID: PMC10795892 DOI: 10.1210/clinem/dgad534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/17/2023] [Accepted: 09/05/2023] [Indexed: 09/12/2023]
Abstract
CONTEXT Uric acid's role in cardiovascular health in youth with type 1 diabetes is unknown. OBJECTIVE Investigate whether higher uric acid is associated with increased blood pressure (BP) and arterial stiffness over time in adolescents and young adults with type 1 diabetes and if overweight/obesity modifies this relationship. METHODS Longitudinal analysis of data from adolescents and young adults with type 1 diabetes from 2 visits (mean follow up 4.6 years) in the SEARCH for Diabetes in Youth multicenter prospective cohort study from 2007 to 2018. Our exposure was uric acid at the first visit and our outcome measures were the change in BP, pulse wave velocity (PWV), and augmentation index between visits. We used multivariable linear mixed-effects models and assessed for effect modification by overweight/obesity. RESULTS Of 1744 participants, mean age was 17.6 years, 49.4% were female, 75.9% non-Hispanic White, and 45.4% had a follow-up visit. Mean uric acid was 3.7 mg/dL (SD 1.0). Uric acid was not associated with increased BP, PWV-trunk, or augmentation index over time. Uric acid was marginally associated with PWV-upper extremity (β = .02 m/s/year, 95% CI 0.002 to 0.04). The magnitude of this association did not differ by overweight/obesity status. CONCLUSION Among adolescents and young adults with type 1 diabetes, uric acid was not consistently associated with increased BP or arterial stiffness over time. These results support findings from clinical trials in older adults with diabetes showing that lowering uric acid levels does not improve cardiovascular outcomes.
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Affiliation(s)
- Andrew M South
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27101, USA
- Section of Nephrology, Department of Pediatrics, Brenner Children's, Wake Forest University School of Medicine, Winston Salem, NC 27157, USA
- Cardiovascular Sciences Center, Wake Forest University School of Medicine, Winston Salem, NC 27101, USA
- Center on Diabetes, Obesity and Metabolism, Wake Forest University School of Medicine, Winston Salem, NC 27101, USA
| | - Joseph Rigdon
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27101, USA
| | - Saroja Voruganti
- Department of Nutrition, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC 27599, USA
| | - Jeanette M Stafford
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27101, USA
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Santica Marcovina
- Northwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Seattle, WA 98109, USA
| | - Amy K Mottl
- Division of Nephrology and Hypertension, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | - Cate Pihoker
- Department of Pediatrics, University of Washington School of Medicine and Division of Endocrinology, Seattle Children's Hospital, University of Washington, Seattle, WA 98105, USA
| | - Elaine M Urbina
- The Heart Institute, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH 45229, USA
| | - Elizabeth T Jensen
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC 27101, USA
- Department of Medicine, Section of Gastroenterology, Wake Forest University School of Medicine, Winston Salem, NC 27101, USA
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Schiff AF, Deines D, Jensen ET, O'Connell N, Perry CJ, Shaltout HA, Washburn LK, South AM. Duration of Simultaneous Exposure to High-Risk and Lower-Risk Nephrotoxic Antimicrobials in the Neonatal Intensive Care Unit (NICU) and Future Adolescent Kidney Health. J Pediatr 2024; 264:113730. [PMID: 37722552 PMCID: PMC10873056 DOI: 10.1016/j.jpeds.2023.113730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/30/2023] [Accepted: 09/13/2023] [Indexed: 09/20/2023]
Abstract
OBJECTIVE To determine whether greater duration of simultaneous exposure to antimicrobials with high nephrotoxicity risk combined with lower-risk antimicrobials (simultaneous exposure) in the neonatal intensive care unit (NICU) is associated with worse later kidney health in adolescents born preterm with very low birth weight (VLBW). STUDY DESIGN Prospective cohort study of participants born preterm with VLBW (<1500 g) as singletons between January 1, 1992, and June 30, 1996. We defined simultaneous exposure as a high-risk antimicrobial, such as vancomycin, administered with a lower-risk antimicrobial on the same date in the NICU. Outcomes were serum creatinine, estimated glomerular filtration rate (eGFR), and first-morning urine albumin-creatinine ratio (ACR) at age 14 years. We fit multivariable linear regression models with days of simultaneous exposure and days of nonsimultaneous exposure as main effects, adjusting for gestational age, birth weight, and birth weight z-score. RESULTS Of the 147 out of 177 participants who had exposure data, 97% received simultaneous antimicrobials for mean duration 7.2 days (SD 5.6). No participant had eGFR <90 ml/min/1.73 m2. The mean ACR was 15.2 mg/g (SD 38.7) and 7% had albuminuria (ACR >30 mg/g). Each day of simultaneous exposure was associated only with a 1.04-mg/g higher ACR (95% CI 1.01 to 1.06). CONCLUSIONS Despite frequent simultaneous exposure to high-risk combined with lower-risk nephrotoxic antimicrobials in the NICU, there were no clinically relevant associations with worse kidney health identified in adolescence. Although future studies are needed, these findings may provide reassurance in a population thought to be at increased risk of chronic kidney disease.
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Affiliation(s)
- Andrew F Schiff
- Department of Pediatrics, Section of Neonatology, Wake Forest University School of Medicine, Winston Salem, NC
| | - Danielle Deines
- University of Otago School of Medicine, Dunedin, New Zealand
| | - Elizabeth T Jensen
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston Salem, NC
| | - Nathaniel O'Connell
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston Salem, NC
| | - Courtney J Perry
- Department of Physician Assistant Studies, Wake Forest University School of Medicine, Winston Salem, NC
| | - Hossam A Shaltout
- Department of Obstetrics and Gynecology, Wake Forest University School of Medicine, Winston Salem, NC; Department of Pharmacology and Toxicology, School of Pharmacy, University of Alexandria, Alexandria, Egypt
| | - Lisa K Washburn
- Department of Pediatrics, Section of Neonatology, Wake Forest University School of Medicine, Winston Salem, NC
| | - Andrew M South
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston Salem, NC; Department of Pediatrics, Section of Nephrology, Wake Forest University School of Medicine, Winston Salem, NC.
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9
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Perrin EC, Ravi HL, Borra GS, South AM. Prevalence and risk factors of disordered eating behavior in youth with hypertension disorders. Pediatr Nephrol 2023; 38:3779-3789. [PMID: 37195544 PMCID: PMC10189692 DOI: 10.1007/s00467-023-05921-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/08/2023] [Accepted: 02/13/2023] [Indexed: 05/18/2023]
Abstract
BACKGROUND Adolescents with certain health conditions requiring lifestyle management, such as diabetes mellitus, have higher disordered eating behavior (DEB) risk than the general adolescent population, but DEB is underdiagnosed and can lead to adverse health consequences. In youth with other conditions requiring lifestyle counseling such as hypertension (HTN), DEB prevalence and associated risk factors are unknown. We hypothesized that youth with HTN disorders would have higher DEB prevalence than the general adolescent population, and that obesity, chronic kidney disease (CKD), and less specialized lifestyle counseling would be associated with higher DEB risk. METHODS Prospective cross-sectional study of youth aged 11-18 years with HTN disorders. We excluded patients with diabetes mellitus, kidney failure or transplantation, or gastrostomy tube dependence. We collected data via surveys and electronic health record abstraction. We administered the validated SCOFF DEB screening questionnaire. We compared DEB prevalence using a one-sample z-test of proportions (p0 = 0.1) and estimated DEB risk by obesity, CKD, and lifestyle counseling source using multivariable generalized linear models. RESULTS Of 74 participants, 59% identified as male, 22% as Black or African American, and 36% as Hispanic or Latino; 58% had obesity and 26% had CKD. DEB prevalence was 28% (95% CI 18-39%, p < 0.001). CKD was associated with higher DEB prevalence (adjusted RR 2.17, 95% CL 1.09 to 4.32), but obesity and lifestyle counseling source were not. CONCLUSIONS DEB prevalence is higher in youth with HTN disorders and comparable to other conditions requiring lifestyle counseling. Youth with HTN disorders may benefit from DEB screening. A higher resolution version of the Graphical abstract is available as Supplementary information.
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Affiliation(s)
- Ella C Perrin
- Department of Pediatrics, Section of Nephrology, Brenner Children's, Wake Forest University School of Medicine, One Medical Center Boulevard, Winston Salem, NC, 27157, USA
| | - Hanna L Ravi
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Gagana S Borra
- Department of Pediatrics, Section of Nephrology, Brenner Children's, Wake Forest University School of Medicine, One Medical Center Boulevard, Winston Salem, NC, 27157, USA
| | - Andrew M South
- Department of Pediatrics, Section of Nephrology, Brenner Children's, Wake Forest University School of Medicine, One Medical Center Boulevard, Winston Salem, NC, 27157, USA.
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston Salem, NC, USA.
- Cardiovascular Sciences Center, Wake Forest University School of Medicine, Winston Salem, NC, USA.
- Center for Biomedical Informatics, Wake Forest University School of Medicine, Winston Salem, NC, USA.
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10
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Floyd WN, Beavers DP, Jensen ET, Washburn LK, South AM. Association of antenatal corticosteroids with kidney function in adolescents born preterm with very low birth weight. J Perinatol 2023; 43:1038-1044. [PMID: 37160975 PMCID: PMC10524661 DOI: 10.1038/s41372-023-01688-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 03/15/2023] [Accepted: 04/26/2023] [Indexed: 05/11/2023]
Abstract
OBJECTIVE Investigate if antenatal corticosteroids (ANCS) are associated with worse kidney function in adolescence and if greater adiposity magnifies this association. STUDY DESIGN Prospective cohort of 162 14-year-olds born preterm with very low birth weight (<1500 g). Outcomes were estimated glomerular filtration rate (eGFR) and first-morning urine albumin-to-creatinine ratio (UACR). We used adjusted generalized linear models, stratified by waist-to-height ratio (WHR) ≥ 0.5. RESULTS Fifty-five percent had ANCS exposure and 31.3% had WHR ≥ 0.5. In adjusted analyses of the entire cohort, ANCS was not significantly associated with eGFR or UACR. However, the ANCS-eGFR association was greater in those with WHR ≥ 0.5 (β -16.8 ml/min/1.73 m2, 95% CL -31.5 to -2.1) vs. WHR < 0.5: (β 13.9 ml/min/1.73 m2, 95% CL -0.4 to 28.1), interaction term p = 0.02. CONCLUSION ANCS exposure was not associated with worse kidney function in adolescence, though ANCS may be associated with lower eGFR if children develop obesity by adolescence.
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Affiliation(s)
- Whitney N Floyd
- Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA
| | - Daniel P Beavers
- Department of Statistical Sciences, Wake Forest University, Winston-Salem, NC, 27101, USA
| | - Elizabeth T Jensen
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA
| | - Lisa K Washburn
- Department of Pediatrics, Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA
| | - Andrew M South
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA.
- Department of Pediatrics, Section of Nephrology, Brenner Children's, Wake Forest University School of Medicine, Winston Salem, NC, USA.
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11
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Rastmanesh R, Krishnia L, Kashyap MK. The Influence of COVID-19 in Endocrine Research: Critical Overview, Methodological Implications and a Guideline for Future Designs. Clin Med Insights Endocrinol Diabetes 2023; 16:11795514231189073. [PMID: 37529301 PMCID: PMC10387761 DOI: 10.1177/11795514231189073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 06/14/2023] [Indexed: 08/03/2023] Open
Abstract
The COVID-19 pandemic has changed many aspects of people's lives, including not only individual social behavior, healthcare procedures, and altered physiological and pathophysiological responses. As a result, some medical studies may be influenced by one or more hidden factors brought about by the COVID-19 pandemic. Using the literature review method, we are briefly discussing the studies that are confounded by COVID-19 and facemask-induced partiality and how these factors can be further complicated with other confounding variables. Facemask wearing has been reported to produce partiality in studies of ophthalmology (particularly dry eye and related ocular diseases), sleep studies, cognitive studies (such as emotion-recognition accuracy research, etc.), and gender-influenced studies, to mention a few. There is a possibility that some other COVID-19 related influences remain unrecognized in medical research. To account for heterogeneity, current and future studies need to consider the severity of the initial illness (such as diabetes, other endocrine disorders), and COVID-19 infection, the timing of analysis, or the presence of a control group. Face mask-induced influences may confound the results of diabetes studies in many ways.
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Affiliation(s)
| | - Lucky Krishnia
- Amity Centre of Nanotechnology, Amity University Haryana, Panchgaon, Haryana, India
| | - Manoj Kumar Kashyap
- Amity Medical School, Amity Stem Cell Institute, Amity University Haryana, Panchgaon, Haryana, India
- Clinical Biosamples & Research Services (CBRS), Noida, Uttar Pradesh, India
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12
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Alexander BT, South AM, August P, Bertagnolli M, Ferranti EP, Grobe JL, Jones EJ, Loria AS, Safdar B, Sequeira-Lopez MLS. Appraising the Preclinical Evidence of the Role of the Renin-Angiotensin-Aldosterone System in Antenatal Programming of Maternal and Offspring Cardiovascular Health Across the Life Course: Moving the Field Forward: A Scientific Statement From the American Heart Association. Hypertension 2023; 80:e75-e89. [PMID: 36951054 PMCID: PMC10242542 DOI: 10.1161/hyp.0000000000000227] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
There is increasing interest in the long-term cardiovascular health of women with complicated pregnancies and their affected offspring. Emerging antenatal risk factors such as preeclampsia appear to increase the risk of hypertension and cardiovascular disease across the life course in both the offspring and women after pregnancy. However, the antenatal programming mechanisms responsible are complex and incompletely understood, with roots in alterations in the development, structure, and function of the kidney, heart, vasculature, and brain. The renin-angiotensin-aldosterone system is a major regulator of maternal-fetal health through the placental interface, as well as kidney and cardiovascular tissue development and function. Renin-angiotensin-aldosterone system dysregulation plays a critical role in the development of pregnancy complications such as preeclampsia and programming of long-term adverse cardiovascular health in both the mother and the offspring. An improved understanding of antenatal renin-angiotensin-aldosterone system programming is crucial to identify at-risk individuals and to facilitate development of novel therapies to prevent and treat disease across the life course. Given the inherent complexities of the renin-angiotensin-aldosterone system, it is imperative that preclinical and translational research studies adhere to best practices to accurately and rigorously measure components of the renin-angiotensin-aldosterone system. This comprehensive synthesis of preclinical and translational scientific evidence of the mechanistic role of the renin-angiotensin-aldosterone system in antenatal programming of hypertension and cardiovascular disease will help (1) to ensure that future research uses best research practices, (2) to identify pressing needs, and (3) to guide future investigations to maximize potential outcomes. This will facilitate more rapid and efficient translation to clinical care and improve health outcomes.
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13
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Giammattei VC, Weaver DJ, South AM. Management of acute severe hypertension in youth: from the philosophical to the practical. Curr Opin Pediatr 2023; 35:251-258. [PMID: 36437756 PMCID: PMC9992153 DOI: 10.1097/mop.0000000000001209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
PURPOSE OF REVIEW Acute severe hypertension remains an uncommon but important source of morbidity and mortality in youth. However, there has been very little progress made in our understanding of how to best manage youth with acute severe hypertension to improve patient outcomes. RECENT FINDINGS Our understanding of what is acute severe hypertension is undergoing a philosophical change. Management of patients with acute severe hypertension is evolving towards more of a risk and outcomes-based approach. SUMMARY We should be intentional when we consider whether a patient has acute severe hypertension and if they are truly at an increased risk for life-threatening target organ injury. We should consider their specific risk factors to best interpret the risks and benefits of how best to treat a patient with acute severe hypertension, rather than relying on traditional approaches and conventional wisdom. We should always ask 'why' when we are pursuing a given management course. Future studies should clearly define the research questions they are investigating to best advance the field to ultimately improve patient outcomes.
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Affiliation(s)
| | - Donald J. Weaver
- Division of Nephrology and Hypertension, Department of Pediatrics, Atrium Health Levine Children's, Charlotte, NC, USA
| | - Andrew M. South
- Section of Nephrology, Department of Pediatrics, Brenner Children’s, Wake Forest University School of Medicine, Winston Salem, NC, USA
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston Salem, NC, USA
- Cardiovascular Sciences Center, Wake Forest University School of Medicine, Winston Salem, NC, USA
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14
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Martinuka O, von Cube M, Hazard D, Marateb HR, Mansourian M, Sami R, Hajian MR, Ebrahimi S, Wolkewitz M. Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19. Life (Basel) 2023; 13:777. [PMID: 36983933 PMCID: PMC10053871 DOI: 10.3390/life13030777] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 03/02/2023] [Accepted: 03/08/2023] [Indexed: 03/17/2023] Open
Abstract
Methodological biases are common in observational studies evaluating treatment effectiveness. The objective of this study is to emulate a target trial in a competing risks setting using hospital-based observational data. We extend established methodology accounting for immortal time bias and time-fixed confounding biases to a setting where no survival information beyond hospital discharge is available: a condition common to coronavirus disease 2019 (COVID-19) research data. This exemplary study includes a cohort of 618 hospitalized patients with COVID-19. We describe methodological opportunities and challenges that cannot be overcome applying traditional statistical methods. We demonstrate the practical implementation of this trial emulation approach via clone-censor-weight techniques. We undertake a competing risk analysis, reporting the cause-specific cumulative hazards and cumulative incidence probabilities. Our analysis demonstrates that a target trial emulation framework can be extended to account for competing risks in COVID-19 hospital studies. In our analysis, we avoid immortal time bias, time-fixed confounding bias, and competing risks bias simultaneously. Choosing the length of the grace period is justified from a clinical perspective and has an important advantage in ensuring reliable results. This extended trial emulation with the competing risk analysis enables an unbiased estimation of treatment effects, along with the ability to interpret the effectiveness of treatment on all clinically important outcomes.
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Affiliation(s)
- Oksana Martinuka
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Centre, University of Freiburg, 79104 Freiburg, Germany
| | - Maja von Cube
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Centre, University of Freiburg, 79104 Freiburg, Germany
| | - Derek Hazard
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Centre, University of Freiburg, 79104 Freiburg, Germany
| | - Hamid Reza Marateb
- Biomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan 81746-73441, Iran
- Biomedical Engineering Research Centre (CREB), Automatic Control Department (ESAII), Universitat Politècnica de Catalunya-Barcelona Tech (UPC) Building H, Floor 4, Av. Diagonal 647, 08028 Barcelona, Spain
| | - Marjan Mansourian
- Biomedical Engineering Research Centre (CREB), Automatic Control Department (ESAII), Universitat Politècnica de Catalunya-Barcelona Tech (UPC) Building H, Floor 4, Av. Diagonal 647, 08028 Barcelona, Spain
- Department of Epidemiology and Biostatistics, School of Health, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
| | - Ramin Sami
- Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
| | - Mohammad Reza Hajian
- Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
| | - Sara Ebrahimi
- Alzahra Research Institute, Alzahra University Hospital, Isfahan University of Medical Sciences, Isfahan 81746-75731, Iran
| | - Martin Wolkewitz
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Centre, University of Freiburg, 79104 Freiburg, Germany
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15
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Paguio JA, Casipit BA, John TA, Balu A, Lo KB. Angiotensin converting enzyme inhibitors and angiotensin II receptor blockers and outcomes in hospitalized patients with COVID-19: an updated systematic review and meta-analysis of randomized clinical trials. Expert Rev Cardiovasc Ther 2023; 21:219-226. [PMID: 36821251 DOI: 10.1080/14779072.2023.2184351] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
BACKGROUND Our prior analysis demonstrated no significant difference in risk of mortality or disease progression among patients with COVID-19. With the availability of findings from randomized controlled trials (RCTs), we provide an updated review of RCTs which explored the outcomes among hospitalized patients with COVID-19 treated with Angiotensin Converting Enzyme inhibitor (ACEis)/Angiotensin Receptor Blockers (ARBs) versus control. RESEARCH DESIGN AND METHODS This systematic review and meta-analysis covers RCTs exploring mortality, intensive care unit admission, and mechanical ventilation outcomes among hospitalized COVID-19 patients treated with ACEi/ARBs. RESULTS Ten studies were included in this meta-analysis. For mortality with ACEi/ARB utilization among hospitalized COVID-19 patients, the pooled risk ratio (RR) was 0.97 (95% CI 0.64-1.47, p = 0.89) with heterogeneity of 26%. Further, the pooled RR for ACEi/ARB use on ICU admission and mechanical ventilation were 0.55 (0.55-1.08, p = 0.13) with a heterogeneity of 0% and 1.02 (0.78-1.32, p = 0.91) with a heterogeneity of 0%, respectively. CONCLUSION Among hospitalized patients with COVID-19, the use of ACEi/ARB was not associated with increased risk of mortality, ICU admission, or mechanical ventilation compared to control. These findings support continuation of ACEi/ARB for whom baseline clinical indications for these agents exist.
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Affiliation(s)
- Joseph Alexander Paguio
- Department of Medicine, Albert Einstein Medical Center, Philadelphia, Pennsylvania, USA.,Sidney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Bruce Adrian Casipit
- Department of Medicine, Albert Einstein Medical Center, Philadelphia, Pennsylvania, USA.,Sidney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Tara A John
- Department of Medicine, Albert Einstein Medical Center, Philadelphia, Pennsylvania, USA.,Sidney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Aniruddh Balu
- Longfellow Middle School, Fairfax, Pennsylvania, USA
| | - Kevin Bryan Lo
- Department of Medicine, Albert Einstein Medical Center, Philadelphia, Pennsylvania, USA.,Sidney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
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16
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Tan BW, Tan BW, Tan AL, Schriver ER, Gutiérrez-Sacristán A, Das P, Yuan W, Hutch MR, García Barrio N, Pedrera Jimenez M, Abu-el-rub N, Morris M, Moal B, Verdy G, Cho K, Ho YL, Patel LP, Dagliati A, Neuraz A, Klann JG, South AM, Visweswaran S, Hanauer DA, Maidlow SE, Liu M, Mowery DL, Batugo A, Makoudjou A, Tippmann P, Zöller D, Brat GA, Luo Y, Avillach P, Bellazzi R, Chiovato L, Malovini A, Tibollo V, Samayamuthu MJ, Serrano Balazote P, Xia Z, Loh NHW, Chiudinelli L, Bonzel CL, Hong C, Zhang HG, Weber GM, Kohane IS, Cai T, Omenn GS, Holmes JH, Ngiam KY. Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study. EClinicalMedicine 2023; 55:101724. [PMID: 36381999 PMCID: PMC9640184 DOI: 10.1016/j.eclinm.2022.101724] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/12/2022] [Accepted: 10/12/2022] [Indexed: 11/09/2022] Open
Abstract
Background While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1-365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings Advanced age (HR 2.77, 95%CI 2.53-3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03-4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55-5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14-1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37-0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17-1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20-1.58, p < 0.0001), male sex (HR 1.67, 95%CI 1.45-1.93, p < 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80-13.91, p < 0.0001), and hypertension (HR 1.22, 95%CI 1.10-1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32-1.67) and 365 days (RR 1.54, 95%CI 1.21-1.96) compared to COVID-19 patients with no AKI. Interpretation COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery. Funding Authors are supported by various funders, with full details stated in the acknowledgement section.
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Affiliation(s)
- Byorn W.L. Tan
- Department of Medicine, National University Hospital, 1E Kent Ridge Road, NUHS Tower Block Level 10, Singapore 119228
| | - Bryce W.Q. Tan
- Department of Medicine, National University Hospital, 1E Kent Ridge Road, NUHS Tower Block Level 10, Singapore 119228
| | - Amelia L.M. Tan
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Emily R. Schriver
- Data Analytics Center, University of Pennsylvania Health System, 3600 Civic Center Boulevard, Philadelphia, PA 19104, USA
| | - Alba Gutiérrez-Sacristán
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Priyam Das
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - William Yuan
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Meghan R. Hutch
- Department of Preventive Medicine, Northwestern University, 750 North Lake Shore Drive, Chicago, IL 60611, USA
| | - Noelia García Barrio
- Department of Health Informatics, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n 28041 Madrid, Spain
| | - Miguel Pedrera Jimenez
- Department of Health Informatics, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n 28041 Madrid, Spain
| | - Noor Abu-el-rub
- Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS 66160, USA
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, 5607 Baum Blvd, Pittsburgh, PA 15206, USA
| | - Bertrand Moal
- IAM Unit, Bordeaux University Hospital, Place Amélie Rabat Léon, 33076 Bordeaux, France
| | - Guillaume Verdy
- IAM Unit, Bordeaux University Hospital, Place Amélie Rabat Léon, 33076 Bordeaux, France
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, 2 Avenue De Lafayette, Boston, MA 02130, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, 2 Avenue De Lafayette, Boston, MA 02130, USA
| | - Lav P. Patel
- Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS 66160, USA
| | - Arianna Dagliati
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy, Via Ferrata 5, 27100 Pavia, Italy
| | - Antoine Neuraz
- Department of Biomedical Informatics, Hôpital Necker-Enfants Malade, Assistance Publique Hôpitaux de Paris, University of Paris, 149 Rue de Sèvres, 75015 Paris, France
| | - Jeffrey G. Klann
- Department of Medicine, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Andrew M. South
- Department of Pediatrics-Section of Nephrology, Brenner Children's Hospital, Wake Forest School of Medicine, Medical Center Boulevard, Winston Salem, NC 27157, USA
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, 5607 Baum Blvd, Pittsburgh, PA 15206, USA
| | - David A. Hanauer
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan, USA, 100-107 NCRC, 2800 Plymouth Road, Ann Arbor, MI 48109, USA
| | - Sarah E. Maidlow
- Michigan Institute for Clinical and Health Research (MICHR) Informatics, University of Michigan, NCRC Bldg 400, 2800 Plymouth Road, Ann Arbor, MI, United States
| | - Mei Liu
- Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS 66160, USA
| | - Danielle L. Mowery
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk, Richards Hall, A202, Philadelphia, PA 19104, USA
| | - Ashley Batugo
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, 401 Blockley Hall 423 Guardian Drive Philadelphia, PA 19104, USA
| | - Adeline Makoudjou
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Zinkmattenstraße 6a, DE79108 Freiburg, Germany
| | - Patric Tippmann
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Zinkmattenstraße 6a, DE79108 Freiburg, Germany
| | - Daniela Zöller
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Zinkmattenstraße 6a, DE79108 Freiburg, Germany
| | - Gabriel A. Brat
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, 750 North Lake Shore Drive, Chicago, IL 60611, USA
| | - Paul Avillach
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy, Via Ferrata 5, 27100 Pavia, Italy
| | - Luca Chiovato
- Unit of Internal Medicine and Endocrinology, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Via Maugeri 4, 27100 Pavia, Italy
| | - Alberto Malovini
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy., Via Maugeri 4, 27100 Pavia, Italy
| | - Valentina Tibollo
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy., Via Maugeri 4, 27100 Pavia, Italy
| | | | - Pablo Serrano Balazote
- Department of Health Informatics, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n 28041 Madrid, Spain
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, 3501 5th Avenue, BST-3 Suite 7014, Pittsburgh, PA 15260, USA
| | - Ne Hooi Will Loh
- Department of Anaesthesia, National University Health System, 5 Lower Kent Ridge Road, Singapore 119074
| | - Lorenzo Chiudinelli
- UOC Ricerca, Innovazione e Brand reputation, ASST Papa Giovanni XXIII, Bergamo, P.zza OMS 1 - 24127 Bergamo, Italy
| | - Clara-Lea Bonzel
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Chuan Hong
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
- Department of Biostatistics and Bioinformatics, Duke University, 2424 Erwin Road, Durham, NC, United States
| | - Harrison G. Zhang
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Griffin M. Weber
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Isaac S. Kohane
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA
| | - Gilbert S. Omenn
- Department of Computational Medicine & Bioinformatics, University of Michigan, 2017B Palmer Commons, 100 Washtenaw, Ann Arbor, MI 48109-2218
| | - John H. Holmes
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, 3700 Hamilton Walk, Richards Hall, A202, Philadelphia, PA 19104, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, 401 Blockley Hall 423 Guardian Drive Philadelphia, PA 19104, USA
| | - Kee Yuan Ngiam
- Department of Biomedical Informatics, WiSDM, National University Health Systems Singapore, 1E Kent Ridge Road, NUHS Tower Block Level 8, Singapore 119228
- Corresponding author. Department of Biomedical Informatics, WiSDM, National University Health Systems Singapore, 1E Kent Ridge Road, NUHS Tower Block Level 8, Singapore 119228.
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17
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O'Shea TM, Register HM, Yi JX, Jensen ET, Joseph RM, Kuban KCK, Frazier JA, Washburn L, Belfort M, South AM, Santos HP, Shenberger J, Perrin EM, Thompson AL, Singh R, Rollins J, Gogcu S, Sanderson K, Wood C, Fry RC. Growth During Infancy After Extremely Preterm Birth: Associations with Later Neurodevelopmental and Health Outcomes. J Pediatr 2023; 252:40-47.e5. [PMID: 35987367 PMCID: PMC10242541 DOI: 10.1016/j.jpeds.2022.08.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 07/12/2022] [Accepted: 08/11/2022] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate associations between changes in weight, length, and weight/length ratio during infancy and outcomes later in life among individuals born extremely preterm. STUDY DESIGN Among participants in the Extremely Low Gestational Age Newborn (ELGAN) study, we measured weight and length at discharge from the neonatal intensive care unit (NICU) and at age 2 years and evaluated neurocognitive, psychiatric, and health outcomes at age 10 years and 15 years. Using multivariable logistic regression, we estimated associations between gains in weight, length, and weight/length ratio z-scores between discharge and 2 years and outcomes at 10 and 15 years. High gain was defined as the top quintile of change; low gain, as the bottom quintile of change. RESULTS High gains in weight and weight/length were associated with greater odds of obesity at 10 years, but not at 15 years. These associations were found only for females. High gain in length z-score was associated with lower odds of obesity at 15 years. The only association found between high gains in growth measures and more favorable neurocognitive or psychiatric outcomes was between high gain in weight/length and lower odds of cognitive impairment at age 10 years. CONCLUSIONS During the 2 years after NICU discharge, females born extremely preterm with high gains in weight/length or weight have greater odds of obesity at 10 years, but not at 15 years. Infants with high growth gains in the 2 years after NICU discharge have neurocognitive and psychiatric outcomes in middle childhood and adolescence similar to those of infants with lower gains in weight and weight/length.
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Affiliation(s)
- T Michael O'Shea
- Department of Pediatrics, The University of North Carolina, Chapel Hill, NC
| | - Hannah M Register
- Department of Pediatrics, The University of North Carolina, Chapel Hill, NC
| | - Joe X Yi
- Frank Porter Graham Child Development Institute, The University of North Carolina, Chapel Hill, NC
| | - Elizabeth T Jensen
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA
| | - Karl C K Kuban
- Department of Pediatrics and Neurology, Boston Medical Center, Boston, MA
| | - Jean A Frazier
- Eunice Kennedy Shriver Center and Department of Psychiatry, University of Massachusetts Chan Medical Center, Worcester, MA
| | - Lisa Washburn
- Department of Pediatrics, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Mandy Belfort
- Department of Pediatric Newborn Medicine, Harvard Medical School, Boston, MA
| | - Andrew M South
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC; Department of Pediatrics, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Hudson P Santos
- School of Nursing & Health Studies, University of Miami, Coral Gables, FL
| | - Jeffrey Shenberger
- Department of Pediatrics, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Eliana M Perrin
- Department of Pediatrics, Johns Hopkins University School of Medicine and Nursing, Baltimore, MD
| | - Amanda L Thompson
- Department of Anthropology, The University of North Carolina, Chapel Hill, NC
| | - Rachana Singh
- Department of Pediatrics, Tufts Children's Hospital, Tufts University School of Medicine, Boston, MA
| | - Julie Rollins
- Department of Pediatrics, The University of North Carolina, Chapel Hill, NC
| | - Semsa Gogcu
- Department of Pediatrics, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Keia Sanderson
- Department of Internal Medicine, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Charles Wood
- Department of Pediatrics, Duke University School of Medicine, Durham, NC
| | - Rebecca C Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina, Chapel Hill, NC
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18
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South AM, Allen NB. Antenatal Programming of Hypertension: Paradigms, Paradoxes, and How We Move Forward. Curr Hypertens Rep 2022; 24:655-667. [PMID: 36227517 PMCID: PMC9712278 DOI: 10.1007/s11906-022-01227-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/28/2022] [Indexed: 01/31/2023]
Abstract
PURPOSE OF REVIEW Synthesize the clinical, epidemiological, and preclinical evidence for antenatal programming of hypertension and critically appraise paradigms and paradoxes to improve translation. RECENT FINDINGS Clinical and epidemiological studies persistently demonstrate that antenatal factors contribute to programmed hypertension under the developmental origins of health and disease framework, including lower birth weight, preterm birth, and fetal growth restriction. Preclinical mechanisms include preeclampsia, maternal diabetes, maternal undernutrition, and antenatal corticosteroid exposure. However, clinical and epidemiological studies to date have largely failed to adequately identify, discuss, and mitigate many sources and types of bias in part due to heterogeneous study designs and incomplete adherence to scientific rigor. These limitations have led to incomplete and biased paradigms as well as persistent paradoxes that have significantly limited translation into clinical and population health interventions. Improved understanding of these paradigms and paradoxes will allow us to substantially move the field forward.
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Affiliation(s)
- Andrew M South
- Department of Pediatrics, Section of Nephrology, Brenner Children's, Wake Forest University School of Medicine, One Medical Center Boulevard, Winston-Salem, NC, 27157, USA.
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
- Department of Surgery-Hypertension and Vascular Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
- Cardiovascular Sciences Center, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
| | - Norrina B Allen
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
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19
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Yu YH, Oh IS, Jeong HE, Platt RW, Douros A, Shin JY, Filion KB. Challenges in evaluating treatments for COVID-19: The case of in-hospital anticoagulant use and the risk of adverse outcomes. Front Pharmacol 2022; 13:1034636. [PMID: 36506517 PMCID: PMC9729259 DOI: 10.3389/fphar.2022.1034636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 11/10/2022] [Indexed: 11/25/2022] Open
Abstract
Anticoagulants are a potential treatment for the thrombotic complications resulting from COVID-19. We aimed to determine the association between anticoagulant use and adverse outcomes among hospitalized patients with COVID-19. We used data from the COVID-19 International Collaborative Research Project in South Korea from January to June 2020. We defined exposure using an intention-to-treat approach, with person-time classified as use or non-use of anticoagulants at cohort entry, and a time-varying approach. The primary outcome was all-cause, in-hospital mortality; the secondary outcome was a composite including respiratory outcomes, cardiovascular outcomes, venous thromboembolism, major bleeding, and intensive care unit admission. Cox proportional hazards models estimated adjusted hazard ratios (HRs) of the outcomes comparing use versus non-use of anticoagulants. Our cohort included 2,677 hospitalized COVID-19 patients, of whom 24 received anticoagulants at cohort entry. Users were older and had more comorbidities. The crude incidence rate (per 1,000 person-days) of mortality was 5.83 (95% CI: 2.80, 10.72) among anticoagulant users and 1.36 (95% CI: 1.14, 1.59) for non-users. Crude rates of the composite outcome were 3.20 (95% CI: 1.04, 7.47) and 1.80 (95% CI: 1.54, 2.08), respectively. Adjusted HRs for mortality (HR: 1.12, 95% CI: 0.48, 2.64) and the composite outcome (HR: 0.79, 95% CI: 0.28, 2.18) were inconclusive. Although our study was not able to draw conclusions on anticoagulant effectiveness for COVID-19 outcomes, these results can contribute to future knowledge syntheses of this important question. Our study demonstrated that the dynamic pandemic environment may have important implications for observational studies of COVID-19 treatment effectiveness.
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Affiliation(s)
- Ya-Hui Yu
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada,Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada
| | - In-Sun Oh
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada,Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada,School of Pharmacy Science, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea,Department of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, Gyeonggi-do, South Kore
| | - Han Eol Jeong
- School of Pharmacy Science, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea,Department of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, Gyeonggi-do, South Kore
| | - Robert W. Platt
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada,Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada,Department of Pediatrics, McGill University, Montreal, QC, Canada
| | - Antonios Douros
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada,Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada,Department of Medicine, McGill University, Montreal, QC, Canada,Institute of Clinical Pharmacology and Toxicology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ju-Young Shin
- School of Pharmacy Science, Sungkyunkwan University, Suwon, Gyeonggi-do, South Korea,Department of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, Gyeonggi-do, South Kore,Department of Clinical Research Design and Evaluation, Samsung Advanced Institute for Health Sciences and Technology, Seoul, South Korea
| | - Kristian B. Filion
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada,Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, Montreal, QC, Canada,Department of Medicine, McGill University, Montreal, QC, Canada,*Correspondence: Kristian B. Filion,
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20
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Chmielewski J, Chaudhry PM, Harer MW, Menon S, South AM, Chappell A, Griffin R, Askenazi D, Jetton J, Starr MC, Selewski DT, Sarkar S, Kent A, Fletcher J, Abitbol CL, DeFreitas M, Duara S, Charlton JR, Swanson JR, Guillet R, D’Angio C, Mian A, Rademacher E, Mhanna MJ, Raina R, Kumar D, Jetton JG, Brophy PD, Colaizy TT, Klein JM, Arikan AA, Rhee CJ, Goldstein SL, Nathan AT, Kupferman JC, Bhutada A, Rastogi S, Bonachea E, Ingraham S, Mahan J, Nada A, Cole FS, Davis TK, Dower J, Milner L, Smith A, Fuloria M, Reidy K, Kaskel FJ, Soranno DE, Gien J, Gist KM, Chishti AS, Hanna MH, Hingorani S, Juul S, Wong CS, Joseph C, DuPont T, Ohls R, Staples A, Rohatgi S, Sethi SK, Wazir S, Khokhar S, Perazzo S, Ray PE, Revenis M, Mammen C, Synnes A, Wintermark P, Zappitelli M, Woroniecki R, Sridhar S. Documentation of acute kidney injury at discharge from the neonatal intensive care unit and role of nephrology consultation. J Perinatol 2022; 42:930-936. [PMID: 35676535 PMCID: PMC9280854 DOI: 10.1038/s41372-022-01424-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 04/29/2022] [Accepted: 05/27/2022] [Indexed: 11/09/2022]
Abstract
OBJECTIVE To investigate whether NICU discharge summaries documented neonatal AKI and estimate if nephrology consultation mediated this association. STUDY DESIGN Secondary analysis of AWAKEN multicenter retrospective cohort. EXPOSURES AKI severity and diagnostic criteria. OUTCOME AKI documentation on NICU discharge summaries using multivariable logistic regression to estimate associations and test for causal mediation. RESULTS Among 605 neonates with AKI, 13% had documented AKI. Those with documented AKI were more likely to have severe AKI (70.5% vs. 51%, p < 0.001) and SCr-only AKI (76.9% vs. 50.1%, p = 0.04). Nephrology consultation mediated 78.0% (95% CL 46.5-109.4%) of the total effect of AKI severity and 82.8% (95% CL 70.3-95.3%) of the total effect of AKI diagnostic criteria on documentation. CONCLUSION We report a low prevalence of AKI documentation at NICU discharge. AKI severity and SCr-only AKI increased odds of AKI documentation. Nephrology consultation mediated the associations of AKI severity and diagnostic criteria with documentation.
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Affiliation(s)
- Jennifer Chmielewski
- Department of Pediatrics, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Paulomi M. Chaudhry
- Department of Pediatrics, Division of Neonatology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Matthew W. Harer
- Department of Pediatrics, Division of Neonatology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Shina Menon
- Division of Nephrology, University of Washington and Seattle Children’s Hospital, Seattle, WA, USA
| | - Andrew M. South
- Department of Pediatrics, Section of Nephrology, Brenner Children’s, Wake Forest School of Medicine, Winston Salem, NC, USA.,Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Ashley Chappell
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Russell Griffin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - David Askenazi
- Department of Pediatrics, Division of Nephrology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jennifer Jetton
- Division of Nephrology, Dialysis and Transplantation, Stead Family Department of Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Michelle C. Starr
- Department of Pediatrics, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA.,Pediatric and Adolescent Comparative Effectiveness Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA.,Correspondence and requests for materials should be addressed to Michelle C. Starr.
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21
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Hong C, Zhang HG, L'Yi S, Weber G, Avillach P, Tan BWQ, Gutiérrez-Sacristán A, Bonzel CL, Palmer NP, Malovini A, Tibollo V, Luo Y, Hutch MR, Liu M, Bourgeois F, Bellazzi R, Chiovato L, Sanz Vidorreta FJ, Le TT, Wang X, Yuan W, Neuraz A, Benoit V, Moal B, Morris M, Hanauer DA, Maidlow S, Wagholikar K, Murphy S, Estiri H, Makoudjou A, Tippmann P, Klann J, Follett RW, Gehlenborg N, Omenn GS, Xia Z, Dagliati A, Visweswaran S, Patel LP, Mowery DL, Schriver ER, Samayamuthu MJ, Kavuluru R, Lozano-Zahonero S, Zöller D, Tan ALM, Tan BWL, Ngiam KY, Holmes JH, Schubert P, Cho K, Ho YL, Beaulieu-Jones BK, Pedrera-Jiménez M, García-Barrio N, Serrano-Balazote P, Kohane I, South A, Brat GA, Cai T. Changes in laboratory value improvement and mortality rates over the course of the pandemic: an international retrospective cohort study of hospitalised patients infected with SARS-CoV-2. BMJ Open 2022; 12:e057725. [PMID: 35738646 PMCID: PMC9226470 DOI: 10.1136/bmjopen-2021-057725] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 06/12/2022] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVE To assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic. DESIGN, SETTING AND PARTICIPANTS This is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic. PRIMARY AND SECONDARY OUTCOME MEASURES The primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the average rate of change in laboratory values during the first week of hospitalisation. RESULTS Baseline Charlson Comorbidity Index and laboratory values at admission were not significantly different between the first and second waves. The improvement in laboratory values over time was faster in the second wave compared with the first. The average C reactive protein rate of change was -4.72 mg/dL vs -4.14 mg/dL per day (p=0.05). The mortality rates within each risk category significantly decreased over time, with the most substantial decrease in the high-risk group (42.3% in March-April 2020 vs 30.8% in November 2020 to January 2021, p<0.001) and a moderate decrease in the intermediate-risk group (21.5% in March-April 2020 vs 14.3% in November 2020 to January 2021, p<0.001). CONCLUSIONS Admission profiles of patients hospitalised with SARS-CoV-2 infection did not differ greatly between the first and second waves of the pandemic, but there were notable differences in laboratory improvement rates during hospitalisation. Mortality risks among patients with similar risk profiles decreased over the course of the pandemic. The improvement in laboratory values and mortality risk was consistent across multiple countries.
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Affiliation(s)
- Chuan Hong
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Harrison G Zhang
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Sehi L'Yi
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Griffin Weber
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Paul Avillach
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Bryce W Q Tan
- Department of Medicine, National University Hospital, Singapore
| | | | - Clara-Lea Bonzel
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Nathan P Palmer
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Alberto Malovini
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy
| | - Valentina Tibollo
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, Evanston, Illinois, USA
| | - Meghan R Hutch
- Department of Preventive Medicine, Northwestern University, Evanston, Illinois, USA
| | - Molei Liu
- Department of Biostatistics, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Florence Bourgeois
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Luca Chiovato
- Unit of Internal Medicine and Endocrinology, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy
| | | | - Trang T Le
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - William Yuan
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Antoine Neuraz
- Department of Biomedical Informatics, Hopital Universitaire Necker-Enfants Malades, Paris, Île-de-France, France
| | - Vincent Benoit
- IT department, Innovation & Data, APHP Greater Paris University Hospital, Paris, France
| | - Bertrand Moal
- IAM unit, Bordeaux University Hospital, Bordeaux, France
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - David A Hanauer
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Sarah Maidlow
- MICHR Informatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Kavishwar Wagholikar
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Shawn Murphy
- Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Hossein Estiri
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Adeline Makoudjou
- Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany
| | - Patric Tippmann
- Institute of Medical Biometry and Statistics, Medical Center-University of Freiburg, Freiburg, Baden-Württemberg, Germany
| | - Jeffery Klann
- Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Robert W Follett
- Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA
| | - Nils Gehlenborg
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Gilbert S Omenn
- Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Arianna Dagliati
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Kansas, USA
| | - Lav P Patel
- Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Danielle L Mowery
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Emily R Schriver
- Data Analytics Center, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA
| | | | - Ramakanth Kavuluru
- Institute for Biomedical Informatics, University of Kentucky, Lexington, Kentucky, USA
| | - Sara Lozano-Zahonero
- Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany
| | - Daniela Zöller
- Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany
| | - Amelia L M Tan
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Byorn W L Tan
- Department of Medicine, National University Hospital, Singapore
| | - Kee Yuan Ngiam
- Department of Surgery, National University Hospital, Singapore
| | - John H Holmes
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Petra Schubert
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | | | - Miguel Pedrera-Jiménez
- Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain
| | - Noelia García-Barrio
- Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain
| | - Pablo Serrano-Balazote
- Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain
| | - Isaac Kohane
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Andrew South
- Department of Pediatrics, Section of Nephrology, Wake Forest University, Winston Salem, North Carolina, USA
| | - Gabriel A Brat
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - T Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
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22
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Klann JG, Strasser ZH, Hutch MR, Kennedy CJ, Marwaha JS, Morris M, Samayamuthu MJ, Pfaff AC, Estiri H, South AM, Weber GM, Yuan W, Avillach P, Wagholikar KB, Luo Y, Omenn GS, Visweswaran S, Holmes JH, Xia Z, Brat GA, Murphy SN. Distinguishing Admissions Specifically for COVID-19 From Incidental SARS-CoV-2 Admissions: National Retrospective Electronic Health Record Study. J Med Internet Res 2022; 24:e37931. [PMID: 35476727 PMCID: PMC9119395 DOI: 10.2196/37931] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/22/2022] [Accepted: 04/22/2022] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Admissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. Electronic health record (EHR)-based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. Although the need to improve classification of COVID-19 versus incidental SARS-CoV-2 is well understood, the magnitude of the problems has only been characterized in small, single-center studies. Furthermore, there have been no peer-reviewed studies evaluating methods for improving classification. OBJECTIVE The aims of this study are to, first, quantify the frequency of incidental hospitalizations over the first 15 months of the pandemic in multiple hospital systems in the United States and, second, to apply electronic phenotyping techniques to automatically improve COVID-19 hospitalization classification. METHODS From a retrospective EHR-based cohort in 4 US health care systems in Massachusetts, Pennsylvania, and Illinois, a random sample of 1123 SARS-CoV-2 PCR-positive patients hospitalized from March 2020 to August 2021 was manually chart-reviewed and classified as "admitted with COVID-19" (incidental) versus specifically admitted for COVID-19 ("for COVID-19"). EHR-based phenotyping was used to find feature sets to filter out incidental admissions. RESULTS EHR-based phenotyped feature sets filtered out incidental admissions, which occurred in an average of 26% of hospitalizations (although this varied widely over time, from 0% to 75%). The top site-specific feature sets had 79%-99% specificity with 62%-75% sensitivity, while the best-performing across-site feature sets had 71%-94% specificity with 69%-81% sensitivity. CONCLUSIONS A large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.
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Affiliation(s)
- Jeffrey G Klann
- Laboratory of Computer Science, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Zachary H Strasser
- Laboratory of Computer Science, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Meghan R Hutch
- Department of Preventive Medicine, Northwestern University, Chicago, IL, United States
| | - Chris J Kennedy
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, United States
| | - Jayson S Marwaha
- Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States
| | | | - Ashley C Pfaff
- Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States
| | - Hossein Estiri
- Laboratory of Computer Science, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Andrew M South
- Section of Nephrology, Department of Pediatrics, Brenner Children's, Wake Forest School of Medicine, Winston Salem, NC, United States
| | | | | | | | - Kavishwar B Wagholikar
- Laboratory of Computer Science, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, Chicago, IL, United States
| | - Gilbert S Omenn
- Center for Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, United States
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States
| | - John H Holmes
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | | | - Shawn N Murphy
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
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23
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Perrin EC, South AM. Correlation between kidney sodium and potassium handling and the renin-angiotensin-aldosterone system in children with hypertensive disorders. Pediatr Nephrol 2022; 37:633-641. [PMID: 34499251 PMCID: PMC8904647 DOI: 10.1007/s00467-021-05204-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 06/11/2021] [Accepted: 06/22/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Urine sodium and potassium are used as surrogate markers for dietary consumption in adults with hypertension, but their role in youth with hypertension and their association with components of the renin-angiotensin-aldosterone system (RAAS) are incompletely characterized. Some individuals with hypertension may have an abnormal RAAS response to dietary sodium and potassium intake, though this is incompletely described. Our objective was to investigate if plasma renin activity and serum aldosterone are associated with urine sodium and potassium in youth referred for hypertensive disorders. METHODS This pilot study was a cross-sectional analysis of baseline data from 44 youth evaluated for hypertensive disorders in a Hypertension Clinic. We recorded urine sodium and potassium concentrations normalized to urine creatinine, plasma renin activity, and serum aldosterone and calculated the sodium/potassium (UNaK) and aldosterone/renin ratios. We used multivariable generalized linear models to estimate the associations of renin and aldosterone with urine sodium and potassium. RESULTS Our cohort was diverse (37% non-Hispanic Black, 14% Hispanic), 66% were male, and median age was 15.3 years; 77% had obesity and 9% had a secondary etiology. Aldosterone was associated inversely with urine sodium/creatinine (β: -0.34, 95% CI -0.62 to -0.06) and UNaK (β: -0.09, 95% CI -0.16 to -0.03), and adjusted for estimated glomerular filtration rate and serum potassium. CONCLUSIONS Higher serum aldosterone levels, but not plasma renin activity, were associated with lower urine sodium/creatinine and UNaK at baseline in youth referred for hypertensive disorders. Further characterization of the RAAS could help define hypertension phenotypes and guide management. A higher resolution version of the Graphical abstract is available as supplementary information.
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Affiliation(s)
- Ella C Perrin
- Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Andrew M South
- Department of Pediatrics, Section of Nephrology, Brenner Children's Hospital, Wake Forest School of Medicine, One Medical Center Boulevard, Winston Salem, NC, 27157, USA. .,Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston Salem, NC, USA. .,Department of Surgery-Hypertension and Vascular Research, Wake Forest School of Medicine, Winston Salem, NC, USA. .,Center for Biomedical Informatics, Wake Forest School of Medicine, Winston Salem, NC, USA.
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24
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Puskarich MA, Ingraham NE, Merck LH, Driver BE, Wacker DA, Black LP, Jones AE, Fletcher CV, South AM, Murray TA, Lewandowski C, Farhat J, Benoit JL, Biros MH, Cherabuddi K, Chipman JG, Schacker TW, Guirgis FW, Voelker HT, Koopmeiners JS, Tignanelli CJ. Efficacy of Losartan in Hospitalized Patients With COVID-19-Induced Lung Injury: A Randomized Clinical Trial. JAMA Netw Open 2022; 5:e222735. [PMID: 35294537 PMCID: PMC8928006 DOI: 10.1001/jamanetworkopen.2022.2735] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 01/23/2022] [Indexed: 12/14/2022] Open
Abstract
Importance SARS-CoV-2 viral entry may disrupt angiotensin II (AII) homeostasis, contributing to COVID-19 induced lung injury. AII type 1 receptor blockade mitigates lung injury in preclinical models, although data in humans with COVID-19 remain mixed. Objective To test the efficacy of losartan to reduce lung injury in hospitalized patients with COVID-19. Design, Setting, and Participants This blinded, placebo-controlled randomized clinical trial was conducted in 13 hospitals in the United States from April 2020 to February 2021. Hospitalized patients with COVID-19 and a respiratory sequential organ failure assessment score of at least 1 and not already using a renin-angiotensin-aldosterone system (RAAS) inhibitor were eligible for participation. Data were analyzed from April 19 to August 24, 2021. Interventions Losartan 50 mg orally twice daily vs equivalent placebo for 10 days or until hospital discharge. Main Outcomes and Measures The primary outcome was the imputed arterial partial pressure of oxygen to fraction of inspired oxygen (Pao2:Fio2) ratio at 7 days. Secondary outcomes included ordinal COVID-19 severity; days without supplemental o2, ventilation, or vasopressors; and mortality. Losartan pharmacokinetics and RAAS components (AII, angiotensin-[1-7] and angiotensin-converting enzymes 1 and 2)] were measured in a subgroup of participants. Results A total of 205 participants (mean [SD] age, 55.2 [15.7] years; 123 [60.0%] men) were randomized, with 101 participants assigned to losartan and 104 participants assigned to placebo. Compared with placebo, losartan did not significantly affect Pao2:Fio2 ratio at 7 days (difference, -24.8 [95%, -55.6 to 6.1]; P = .12). Compared with placebo, losartan did not improve any secondary clinical outcomes and led to fewer vasopressor-free days than placebo (median [IQR], 9.4 [9.1-9.8] vasopressor-free days vs 8.7 [8.2-9.3] vasopressor-free days). Conclusions and Relevance This randomized clinical trial found that initiation of orally administered losartan to hospitalized patients with COVID-19 and acute lung injury did not improve Pao2:Fio2 ratio at 7 days. These data may have implications for ongoing clinical trials. Trial Registration ClinicalTrials.gov Identifier: NCT04312009.
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Affiliation(s)
- Michael A. Puskarich
- Department of Emergency Medicine, University of Minnesota, Minneapolis
- Department of Emergency Medicine, Hennepin County Medical Center, Minneapolis, Minnesota
| | - Nicholas E. Ingraham
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, University of Minnesota, Minneapolis
| | - Lisa H. Merck
- Department of Emergency Medicine, University of Florida College of Medicine, Gainesville
| | - Brian E. Driver
- Department of Emergency Medicine, Hennepin County Medical Center, Minneapolis, Minnesota
| | - David A. Wacker
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, University of Minnesota, Minneapolis
| | - Lauren Page Black
- Department of Emergency Medicine, University of Florida College of Medicine, Jacksonville
| | - Alan E. Jones
- Department of Emergency Medicine, University of Mississippi Medical Center, Jackson
| | | | - Andrew M. South
- Section of Nephrology, Department of Pediatrics, Wake Forest School of Medicine and Brenner Children's Hospital, Winston Salem, North Carolina
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston Salem, North Carolina
- Department of Surgery-Hypertension and Vascular Research, Wake Forest School of Medicine, Winston Salem, North Carolina
| | - Thomas A. Murray
- Department of Biostatistics, School of Public Health, University of Minnesota, Minneapolis
| | - Christopher Lewandowski
- Department of Emergency Medicine, Henry Ford Hospital, Wayne State University, Detroit, Michigan
| | - Joseph Farhat
- Department of Surgery, North Memorial Medical Center, Minneapolis, Minnesota
| | - Justin L. Benoit
- Department of Emergency Medicine, University of Cincinnati, Cincinnati, Ohio
| | - Michelle H. Biros
- Department of Emergency Medicine, University of Minnesota, Minneapolis
| | - Kartik Cherabuddi
- Department of Emergency Medicine, University of Florida College of Medicine, Gainesville
| | | | - Timothy W. Schacker
- Division of Infectious Disease, Department of Medicine, University of Minnesota, Minneapolis
| | - Faheem W. Guirgis
- Department of Emergency Medicine, University of Florida College of Medicine, Jacksonville
| | - Helen T. Voelker
- Department of Biostatistics, School of Public Health, University of Minnesota, Minneapolis
| | - Joseph S. Koopmeiners
- Department of Biostatistics, School of Public Health, University of Minnesota, Minneapolis
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25
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Labandeira-Garcia JL, Labandeira CM, Valenzuela R, Pedrosa MA, Quijano A, Rodriguez-Perez AI. Drugs Modulating Renin-Angiotensin System in COVID-19 Treatment. Biomedicines 2022; 10:502. [PMID: 35203711 PMCID: PMC8962306 DOI: 10.3390/biomedicines10020502] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 02/07/2023] Open
Abstract
A massive worldwide vaccination campaign constitutes the main tool against the COVID-19 pandemic. However, drug treatments are also necessary. Antivirals are the most frequently considered treatments. However, strategies targeting mechanisms involved in disease aggravation may also be effective. A major role of the tissue renin-angiotensin system (RAS) in the pathophysiology and severity of COVID-19 has been suggested. The main link between RAS and COVID-19 is angiotensin-converting enzyme 2 (ACE2), a central RAS component and the primary binding site for SARS-CoV-2 that facilitates the virus entry into host cells. An initial suggestion that the susceptibility to infection and disease severity may be enhanced by angiotensin type-1 receptor blockers (ARBs) and ACE inhibitors (ACEIs) because they increase ACE2 levels, led to the consideration of discontinuing treatments in thousands of patients. More recent experimental and clinical data indicate that ACEIs and, particularly, ARBs can be beneficial for COVID-19 outcome, both by reducing inflammatory responses and by triggering mechanisms (such as ADAM17 inhibition) counteracting viral entry. Strategies directly activating RAS anti-inflammatory components such as soluble ACE2, Angiotensin 1-7 analogues, and Mas or AT2 receptor agonists may also be beneficial. However, while ACEIs and ARBs are cheap and widely used, the second type of strategies are currently under study.
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Affiliation(s)
- Jose L. Labandeira-Garcia
- Research Center for Molecular Medicine and Chronic Diseases (CIMUS), IDIS, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; (C.M.L.); (R.V.); (M.A.P.); (A.Q.)
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), 28031 Madrid, Spain
| | - Carmen M. Labandeira
- Research Center for Molecular Medicine and Chronic Diseases (CIMUS), IDIS, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; (C.M.L.); (R.V.); (M.A.P.); (A.Q.)
- Neurology Service, Hospital Alvaro Cunqueiro, University Hospital Complex, 36213 Vigo, Spain
| | - Rita Valenzuela
- Research Center for Molecular Medicine and Chronic Diseases (CIMUS), IDIS, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; (C.M.L.); (R.V.); (M.A.P.); (A.Q.)
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), 28031 Madrid, Spain
| | - Maria A. Pedrosa
- Research Center for Molecular Medicine and Chronic Diseases (CIMUS), IDIS, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; (C.M.L.); (R.V.); (M.A.P.); (A.Q.)
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), 28031 Madrid, Spain
| | - Aloia Quijano
- Research Center for Molecular Medicine and Chronic Diseases (CIMUS), IDIS, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; (C.M.L.); (R.V.); (M.A.P.); (A.Q.)
| | - Ana I. Rodriguez-Perez
- Research Center for Molecular Medicine and Chronic Diseases (CIMUS), IDIS, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; (C.M.L.); (R.V.); (M.A.P.); (A.Q.)
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), 28031 Madrid, Spain
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26
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Klann JG, Strasser ZH, Hutch MR, Kennedy CJ, Marwaha JS, Morris M, Samayamuthu MJ, Pfaff AC, Estiri H, South AM, Weber GM, Yuan W, Avillach P, Wagholikar KB, Luo Y, Omenn GS, Visweswaran S, Holmes JH, Xia Z, Brat GA, Murphy SN. Distinguishing Admissions Specifically for COVID-19 from Incidental SARS-CoV-2 Admissions: A National EHR Research Consortium Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.02.10.22270728. [PMID: 35350202 PMCID: PMC8963684 DOI: 10.1101/2022.02.10.22270728] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Admissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. EHR-based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. From a retrospective EHR-based cohort in four US healthcare systems, a random sample of 1,123 SARS-CoV-2 PCR-positive patients hospitalized between 3/2020â€"8/2021 was manually chart-reviewed and classified as admitted-with-COVID-19 (incidental) vs. specifically admitted for COVID-19 (for-COVID-19). EHR-based phenotyped feature sets filtered out incidental admissions, which occurred in 26%. The top site-specific feature sets had 79-99% specificity with 62-75% sensitivity, while the best performing across-site feature set had 71-94% specificity with 69-81% sensitivity. A large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.
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27
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Smith SM, Desai RA, Walsh MG, Nilles EK, Shaw K, Smith M, Chamberlain AM, Derington CG, Bress AP, Chuang CH, Ford DE, Taylor BW, Chandaka S, Patel LP, McClay J, Priest E, Fuloria J, Doshi K, Ahmad FS, Viera AJ, Faulkner M, O'Brien EC, Pletcher MJ, Cooper-DeHoff RM. Angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and COVID-19-related outcomes: A patient-level analysis of the PCORnet blood pressure control lab. AMERICAN HEART JOURNAL PLUS : CARDIOLOGY RESEARCH AND PRACTICE 2022; 13:100112. [PMID: 35252907 PMCID: PMC8889730 DOI: 10.1016/j.ahjo.2022.100112] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/21/2022] [Accepted: 02/11/2022] [Indexed: 12/20/2022]
Abstract
SARS-CoV-2 accesses host cells via angiotensin-converting enzyme-2, which is also affected by commonly used angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), raising concerns that ACEI or ARB exposure may portend differential COVID-19 outcomes. In parallel cohort studies of outpatient and inpatient COVID-19-diagnosed adults with hypertension, we assessed associations between antihypertensive exposure (ACEI/ARB vs. non-ACEI/ARB antihypertensives, as well as between ACEI- vs. ARB) at the time of COVID-19 diagnosis, using electronic health record data from PCORnet health systems. The primary outcomes were all-cause hospitalization or death (outpatient cohort) or all-cause death (inpatient), analyzed via Cox regression weighted by inverse probability of treatment weights. From February 2020 through December 9, 2020, 11,246 patients (3477 person-years) and 2200 patients (777 person-years) were included from 17 health systems in outpatient and inpatient cohorts, respectively. There were 1015 all-cause hospitalization or deaths in the outpatient cohort (incidence, 29.2 events per 100 person-years), with no significant difference by ACEI/ARB use (adjusted HR 1.01; 95% CI 0.88, 1.15). In the inpatient cohort, there were 218 all-cause deaths (incidence, 28.1 per 100 person-years) and ACEI/ARB exposure was associated with reduced death (adjusted HR, 0.76; 95% CI, 0.57, 0.99). ACEI, versus ARB exposure, was associated with higher risk of hospitalization in the outpatient cohort, but no difference in all-cause death in either cohort. There was no evidence of effect modification across pre-specified baseline characteristics. Our results suggest ACEI and ARB exposure have no detrimental effect on hospitalizations and may reduce death among hypertensive patients diagnosed with COVID-19.
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Affiliation(s)
- Steven M Smith
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
| | - Raj A Desai
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
| | - Marta G Walsh
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
| | - Ester Kim Nilles
- Duke Clinical Research Institute, Duke University, Durham, NC, United States of America
| | - Katie Shaw
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States of America
| | - Myra Smith
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States of America
| | - Alanna M Chamberlain
- Departments of Quantitative Health Sciences and Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States of America
| | - Catherine G Derington
- Department of Population Health Sciences, School of Medicine, University of Utah, Salt Lake City, UT, United States of America
| | - Adam P Bress
- Department of Population Health Sciences, School of Medicine, University of Utah, Salt Lake City, UT, United States of America
| | | | - Daniel E Ford
- Johns Hopkins University, Baltimore, MD, United States of America
| | - Bradley W Taylor
- Medical College of Wisconsin, Milwaukee, WI, United States of America
| | - Sravani Chandaka
- University of Kansas Medical Center, Kansas City, KS, United States of America
| | | | - James McClay
- University of Nebraska, Omaha, NE, United States of America
| | - Elisa Priest
- Baylor Scott & White Health, Dallas, TX, United States of America
| | - Jyotsna Fuloria
- School of Medicine, Louisiana State University, New Orleans, LA, United States of America
| | - Kruti Doshi
- Cook County Health, Chicago, IL, United States of America
| | - Faraz S Ahmad
- Departments of Medicine and Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America
| | - Anthony J Viera
- Department of Family Medicine and Community Health, School of Medicine, Duke University, Durham, NC, United States of America
| | - Madelaine Faulkner
- Department of Epidemiology & Biostatistics, School of Medicine, University of California San Francisco, San Francisco, CA, United States of America
| | - Emily C O'Brien
- Duke Clinical Research Institute, Duke University, Durham, NC, United States of America
| | - Mark J Pletcher
- Department of Epidemiology & Biostatistics, School of Medicine, University of California San Francisco, San Francisco, CA, United States of America
| | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
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28
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Weber GM, Zhang HG, L'Yi S, Bonzel CL, Hong C, Avillach P, Gutiérrez-Sacristán A, Palmer NP, Tan ALM, Wang X, Yuan W, Gehlenborg N, Alloni A, Amendola DF, Bellasi A, Bellazzi R, Beraghi M, Bucalo M, Chiovato L, Cho K, Dagliati A, Estiri H, Follett RW, García Barrio N, Hanauer DA, Henderson DW, Ho YL, Holmes JH, Hutch MR, Kavuluru R, Kirchoff K, Klann JG, Krishnamurthy AK, Le TT, Liu M, Loh NHW, Lozano-Zahonero S, Luo Y, Maidlow S, Makoudjou A, Malovini A, Martins MR, Moal B, Morris M, Mowery DL, Murphy SN, Neuraz A, Ngiam KY, Okoshi MP, Omenn GS, Patel LP, Pedrera Jiménez M, Prudente RA, Samayamuthu MJ, Sanz Vidorreta FJ, Schriver ER, Schubert P, Serrano Balazote P, Tan BW, Tanni SE, Tibollo V, Visweswaran S, Wagholikar KB, Xia Z, Zöller D, Kohane IS, Cai T, South AM, Brat GA. International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study. J Med Internet Res 2021; 23:e31400. [PMID: 34533459 PMCID: PMC8510151 DOI: 10.2196/31400] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/02/2021] [Accepted: 09/02/2021] [Indexed: 02/06/2023] Open
Abstract
Background Many countries have experienced 2 predominant waves of COVID-19–related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic. Objective In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic. Methods Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19. Results Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain. Conclusions Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.
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Affiliation(s)
- Griffin M Weber
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Harrison G Zhang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Sehi L'Yi
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Clara-Lea Bonzel
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Chuan Hong
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Paul Avillach
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | | | - Nathan P Palmer
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Amelia Li Min Tan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Xuan Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - William Yuan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Nils Gehlenborg
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Anna Alloni
- BIOMERIS (BIOMedical Research Informatics Solutions), Pavia, Italy
| | - Danilo F Amendola
- Clinical Research Unit, Botucatu Medical School, São Paulo State University, Botucatu, Brazil
| | - Antonio Bellasi
- Division of Nephrology, Department of Medicine, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Michele Beraghi
- Information Technology Department, Azienda Socio-Sanitaria Territoriale di Pavia, Pavia, Italy
| | - Mauro Bucalo
- BIOMERIS (BIOMedical Research Informatics Solutions), Pavia, Italy
| | - Luca Chiovato
- Unit of Internal Medicine and Endocrinology, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - Arianna Dagliati
- Department of Electrical Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Hossein Estiri
- Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Robert W Follett
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | | | - David A Hanauer
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Darren W Henderson
- Department of Biomedical Informatics, University of Kentucky, Lexington, KY, United States
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | - John H Holmes
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.,Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Meghan R Hutch
- Department of Preventive Medicine, Northwestern University, Chicago, IL, United States
| | - Ramakanth Kavuluru
- Institute for Biomedical Informatics, University of Kentucky, Lexington, KY, United States
| | - Katie Kirchoff
- Medical University of South Carolina, Charleston, SC, United States
| | - Jeffrey G Klann
- Department of Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Ashok K Krishnamurthy
- Department of Computer Science, Renaissance Computing Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Trang T Le
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Molei Liu
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Ne Hooi Will Loh
- Department of Anaesthesia, National University Health System, Singapore, Singapore
| | - Sara Lozano-Zahonero
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, Chicago, IL, United States
| | - Sarah Maidlow
- Michigan Institute for Clinical & Health Research Informatics, University of Michigan, Ann Arbor, MI, United States
| | - Adeline Makoudjou
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Alberto Malovini
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy
| | | | - Bertrand Moal
- Informatique et archivistique médicales unit, Bordeaux University Hospital, Bordeaux, France
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Danielle L Mowery
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Shawn N Murphy
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Antoine Neuraz
- Department of Biomedical Informatics, Hôpital Necker-Enfants Malade, Assistance Publique Hôpitaux de Paris, University of Paris, Paris, France
| | - Kee Yuan Ngiam
- Department of Biomedical Informatics, Institute for Digital Medicine, National University Health System, Singapore, Singapore
| | - Marina P Okoshi
- Internal Medicine Department, Botucatu Medical School, São Paulo State University, Botucatu, Brazil
| | - Gilbert S Omenn
- Department of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, and Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Lav P Patel
- Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
| | | | - Robson A Prudente
- Internal Medicine Department, Botucatu Medical School, São Paulo State University, Botucatu, Brazil
| | | | - Fernando J Sanz Vidorreta
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Emily R Schriver
- Data Analytics Center, University of Pennsylvania Health System, Philadelphia, PA, United States
| | - Petra Schubert
- Massachusetts Veterans Epidemiology Research and Information Center, Veterans Affairs Boston Healthcare System, Boston, MA, United States
| | | | - Byorn Wl Tan
- Department of Medicine, National University Health System, Singapore, Singapore
| | - Suzana E Tanni
- Internal Medicine Department, Botucatu Medical School, São Paulo State University, Botucatu, Brazil
| | - Valentina Tibollo
- Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Italy
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States
| | | | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Daniela Zöller
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
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- see Authors' Contributions,
| | - Isaac S Kohane
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
| | - Andrew M South
- Section of Nephrology, Department of Pediatrics, Brenner Children's Hospital, Wake Forest School of Medicine, Winston Salem, NC, United States
| | - Gabriel A Brat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
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Peñalvo JL, Genbrugge E, Mertens E, Sagastume D, van der Sande MAB, Widdowson MA, Van Beckhoven D. Insights into the association of ACEIs/ARBs use and COVID-19 prognosis: a multistate modelling study of nationwide hospital surveillance data from Belgium. BMJ Open 2021; 11:e053393. [PMID: 34531225 PMCID: PMC8449849 DOI: 10.1136/bmjopen-2021-053393] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVES The widespread use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) by patients with chronic conditions raised early concerns on the potential exacerbation of COVID-19 severity and fatality. Previous studies addressing this question have used standard methods that may lead to biased estimates when analysing hospital data because of the presence of competing events and event-related dependency. We investigated the association of ACEIs/ARBs' use with COVID-19 disease outcomes using time-to-event data in a multistate setting to account for competing events and minimise bias. SETTING Nationwide surveillance data from 119 Belgian hospitals. PARTICIPANTS Medical records of 10 866 patients hospitalised from 14 March 2020to 14 June 2020 with a confirmed SARS-CoV-19 infection and information about ACEIs/ARBs' use. PRIMARY OUTCOME MEASURE Multistate, multivariate Cox-Markov models were used to estimate the hazards of patients transitioning through health states from admission to discharge or death, along with transition probabilities calculated by combining the baseline cumulative hazard and regression coefficients. RESULTS After accounting for potential confounders, there was no discernable association between ACEIs/ARBs' use and transfer to intensive care unit (ICU). Contrastingly, for patients without ICU transfer, ACEIs/ARBs' use was associated with a modest increase in recovery (HR 1.07, 95% CI 1.01 to 1.13, p=0.027) and reduction in fatality (HR 0.83, 95% CI 0.75 to 0.93, p=0.001) transitions. For patients transferred to ICU admission, no evidence of an association between ACEIs/ARBs' use and recovery (HR 1.16, 95% CI 0.97 to 1.38, p=0.098) or in-hospital death (HR 0.91, 95% CI 0.73 to 1.12, p=0.381) was observed. Male gender and older age were significantly associated with higher risk of ICU admission or death. Chronic cardiometabolic comorbidities were also associated with less recovery. CONCLUSIONS For the first time, a multistate model was used to address magnitude and direction of the association of ACEIs/ARBs' use on COVID-19 progression. By minimising bias, this study provided a robust indication of a protective, although modest, association with recovery and survival.
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Affiliation(s)
- José L Peñalvo
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerpen, Belgium
| | - Els Genbrugge
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerpen, Belgium
| | - Elly Mertens
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerpen, Belgium
| | - Diana Sagastume
- Unit of Non-Communicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerpen, Belgium
| | - Marianne A B van der Sande
- Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
- Global Health Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands
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Soler MJ, Ribera A, Marsal JR, Mendez AB, Andres M, Azancot MA, Oristrell G, Méndez-Boo L, Cohen J, Barrabés JA, Ferreira-González I. Association of renin–angiotensin system blockers with COVID-19 diagnosis and prognosis in patients with hypertension: a population-based study. Clin Kidney J 2021; 15:79-94. [PMID: 35035939 PMCID: PMC8499934 DOI: 10.1093/ckj/sfab161] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Indexed: 12/13/2022] Open
Abstract
Abstract
Background
The effect of renin–angiotensin system (RAS) blockade either by angiotensin-converting enzyme inhibitors (ACEis) or angiotensin-receptor blockers (ARBs) on coronavirus disease 2019 (COVID-19) susceptibility, mortality and severity is inadequately described. We examined the association between RAS blockade and COVID-19 diagnosis and prognosis in a large population-based cohort of patients with hypertension (HTN).
Methods
This is a cohort study using regional health records. We identified all individuals aged 18–95 years from 87 healthcare reference areas of the main health provider in Catalonia (Spain), with a history of HTN from primary care records. Data were linked to COVID-19 test results, hospital, pharmacy and mortality records from 1 March 2020 to 14 August 2020. We defined exposure to RAS blockers as the dispensation of ACEi/ARBs during the 3 months before COVID-19 diagnosis or 1 March 2020. Primary outcomes were: COVID-19 infection and severe progression in hospitalized patients with COVID-19 (the composite of need for invasive respiratory support or death). For both outcomes and for each exposure of interest (RAS blockade, ACEi or ARB) we estimated associations in age-, sex-, healthcare area- and propensity score-matched samples.
Results
From a cohort of 1 365 215 inhabitants we identified 305 972 patients with HTN history. Recent use of ACEi/ARBs in patients with HTN was associated with a lower 6-month cumulative incidence of COVID-19 diagnosis {3.78% [95% confidence interval (CI) 3.69–3.86%] versus 4.53% (95% CI 4.40–4.65%); P < 0.001}. In the 12 344 patients with COVID-19 infection, the use of ACEi/ARBs was not associated with a higher risk of hospitalization with need for invasive respiratory support or death [OR = 0.91 (0.71–1.15); P = 0.426].
Conclusions
RAS blockade in patients with HTN is not associated with higher risk of COVID-19 infection or with a worse progression of the disease.
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Affiliation(s)
- María José Soler
- Department of Nephrology, Vall d’Hebron University Hospital, Universitat Autònoma de Barcelona, Nephrology Research Group, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
| | - Aida Ribera
- Department of Cardiology, Cardiovascular Epidemiology Unit, Vall d’Hebron University Hospital Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Josep R Marsal
- Department of Cardiology, Cardiovascular Epidemiology Unit, Vall d’Hebron University Hospital Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Ana Belen Mendez
- Department of Cardiology, Vall d’Hebron University Hospital, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
| | - Mireia Andres
- Department of Cardiology, Vall d’Hebron University Hospital, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Maria Antonia Azancot
- Department of Nephrology, Vall d’Hebron University Hospital, Universitat Autònoma de Barcelona, Nephrology Research Group, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
| | - Gerard Oristrell
- Department of Cardiology, Vall d’Hebron University Hospital, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
| | - Leonardo Méndez-Boo
- Departament de Salut, SISAP: Sistema d′Informació dels Serveis d′Atenció Primària, Direcció de Sistemes d′Informació, Institut Català de la Salut, Generalitat de Catalunya, Barcelona, Spain
| | - Jordana Cohen
- Division of Renal-Electrolyte and Hypertension, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, USA
| | - Jose A Barrabés
- Department of Cardiology, Vall d’Hebron University Hospital, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Ignacio Ferreira-González
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Cardiology, Vall d’Hebron University Hospital, Vall d’Hebron Research Institute (VHIR), Barcelona, Spain
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Campitelli MA, Bronskill SE, Maclagan LC, Harris DA, Cotton CA, Tadrous M, Gruneir A, Hogan DB, Maxwell CJ. Comparison of Medication Prescribing Before and After the COVID-19 Pandemic Among Nursing Home Residents in Ontario, Canada. JAMA Netw Open 2021; 4:e2118441. [PMID: 34338794 PMCID: PMC8329744 DOI: 10.1001/jamanetworkopen.2021.18441] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 05/21/2021] [Indexed: 12/24/2022] Open
Abstract
Importance COVID-19 has had devastating effects on the health and well-being of older adult residents and health care professionals in nursing homes. Uncertainty about the associated consequences of these adverse effects on the use of medications common to this care setting remains. Objective To examine the association between the COVID-19 pandemic and prescription medication changes among nursing home residents. Design, Setting, and Participants This population-based cohort study with an interrupted time-series analysis used linked health administrative data bases for residents of all nursing homes (N = 630) in Ontario, Canada. During the observation period, residents were divided into consecutive weekly cohorts. The first observation week was March 5 to 11, 2017; the last observation week was September 20 to 26, 2020. Exposures Onset of the COVID-19 pandemic on March 1, 2020. Main Outcomes and Measures Weekly proportion of residents dispensed antipsychotics, benzodiazepines, antidepressants, anticonvulsants, opioids, antibiotics, angiotensin receptor blockers (ARBs), and angiotensin-converting enzyme (ACE) inhibitors. Autoregressive integrated moving average models with step and ramp intervention functions tested for level and slope changes in weekly medication use after the onset of the pandemic and were fit on prepandemic data for projected trends. Results Across study years, the annual cohort size ranged from 75 850 to 76 549 residents (mean [SD] age, 83.4 [10.8] years; mean proportion of women, 68.9%). A significant increased slope change in the weekly proportion of residents who were dispensed antipsychotics (parameter estimate [β] = 0.051; standard error [SE] = 0.010; P < .001), benzodiazepines (β = 0.026; SE = 0.003; P < .001), antidepressants (β = 0.046; SE = 0.013; P < .001), trazodone hydrochloride (β = 0.033; SE = 0.010; P < .001), anticonvulsants (β = 0.014; SE = 0.006; P = .03), and opioids (β = 0.038; SE = 0.007; P < .001) was observed. The absolute difference in observed vs estimated use in the last week of the pandemic period ranged from 0.48% (for anticonvulsants) to 1.52% (for antipsychotics). No significant level or slope changes were found for antibiotics, ARBs, or ACE inhibitors. Conclusions and Relevance In this population-based cohort study, statistically significant increases in the use of antipsychotics, benzodiazepines, antidepressants, anticonvulsants, and opioids followed the onset of the COVID-19 pandemic, although absolute differences were small. There were no significant changes for antibiotics, ARBs, or ACE inhibitors. Studies are needed to monitor whether changes in pharmacotherapy persist, regress, or accelerate during the course of the pandemic and how these changes affect resident-level outcomes.
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Affiliation(s)
- Michael A. Campitelli
- ICES (formerly Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada
| | - Susan E. Bronskill
- ICES (formerly Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
- Women’s College Research Institute, Women’s College Hospital, Toronto, Ontario, Canada
| | - Laura C. Maclagan
- ICES (formerly Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada
| | - Daniel A. Harris
- ICES (formerly Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Cecilia A. Cotton
- Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada
| | - Mina Tadrous
- ICES (formerly Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada
- Women’s College Research Institute, Women’s College Hospital, Toronto, Ontario, Canada
- Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada
| | - Andrea Gruneir
- ICES (formerly Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada
- Women’s College Research Institute, Women’s College Hospital, Toronto, Ontario, Canada
- Department of Family Medicine, University of Alberta, Edmonton, Canada
| | - David B. Hogan
- Division of Geriatric Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Colleen J. Maxwell
- ICES (formerly Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada
- School of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada
- Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
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Saeed S, Tadic M, Larsen TH, Grassi G, Mancia G. Coronavirus disease 2019 and cardiovascular complications: focused clinical review. J Hypertens 2021; 39:1282-1292. [PMID: 33687179 PMCID: PMC9904438 DOI: 10.1097/hjh.0000000000002819] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 01/06/2021] [Accepted: 01/17/2021] [Indexed: 02/06/2023]
Abstract
The coronavirus disease 2019 (COVID-19) may cause not only an acute respiratory distress syndrome (ARDS) but also multiple organ damage and failure requiring intensive care and leading to death. Male sex, advanced age, chronic lung disease, chronic kidney disease and cardiovascular disease, such as hypertension, diabetes and obesity have been identified as risk factors for the COVID-19 severity. Presumably, as these three cardiovascular risk factors are associated with a high prevalence of multiorgan damage. In the present focused clinical review, we will discuss the cardiovascular complications of COVID-19 including acute cardiovascular syndrome (acute cardiac injury/COVID cardiomyopathy, thromboembolic complications and arrhythmias) and post-COVID-19 sequelae. Preliminary data shows that the cause of acute cardiovascular syndrome may be multifactorial and involve direct viral invasion of the heart and vascular system, as well as through the immune and inflammation-mediated systemic cytokine storm. COVID-19 survivors may also show persistently elevated blood pressure and sinus tachycardia at rest. Furthermore, poor diabetic control, persistent renal damage and cerebral sequelae, such as persistent cognitive and neuropsychiatric alterations are also frequently reported. A particular attention should be paid towards cardiovascular protection in COVID-19 patients who develop acute cardiovascular syndromes during hospitalization, and/or permanent/semipermanent sequelae after recovery from COVID-19. These conditions may require careful clinical assessment, treatment and close follow-up to avoid short-term and long-term complications.
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Affiliation(s)
- Sahrai Saeed
- Department of Heart Disease, Haukeland University Hospital, Bergen, Norway
| | - Marijana Tadic
- Department of Cardiology, University Hospital ‘Dr Dragisa Misovic-Dedinje’, Belgrade, Serbia
| | - Terje H. Larsen
- Department of Heart Disease, Haukeland University Hospital, Bergen, Norway
| | - Guido Grassi
- Department of Medicine and Surgery, University of Milano-Bicocca, Milan
| | - Giuseppe Mancia
- University of Milano-Bicocca, Milano and Policlinico di Monza, Monza, Italy
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Jaberi-Douraki M, Meyer E, Riviere J, Gedara NIM, Kawakami J, Wyckoff GJ, Xu X. Pulmonary adverse drug event data in hypertension with implications on COVID-19 morbidity. Sci Rep 2021; 11:13349. [PMID: 34172790 PMCID: PMC8233397 DOI: 10.1038/s41598-021-92734-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 06/15/2021] [Indexed: 12/15/2022] Open
Abstract
Hypertension is a recognized comorbidity for COVID-19. The association of antihypertensive medications with outcomes in patients with hypertension is not fully described. However, angiotensin-converting enzyme 2 (ACE2), responsible for host entry of the novel coronavirus (SARS-CoV-2) leading to COVID-19, is postulated to be upregulated in patients taking angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs). Here, we evaluated the occurrence of pulmonary adverse drug events (ADEs) in patients with hypertension receiving ACEIs/ARBs to determine if disparities exist between individual drugs within the respective classes using data from the FDA Spontaneous Reporting Systems. For this purpose, we proposed the proportional reporting ratio to provide a statistical summary for the commonality of an ADE for a specific drug as compared to the entire database for drugs in the same or other classes. In addition, a statistical procedure, multiple logistic regression analysis, was employed to correct hidden confounders when causative covariates are underreported or untrusted to correct analyses of drug-ADE combinations. To date, analyses have been focused on drug classes rather than individual drugs which may have different ADE profiles depending on the underlying diseases present. A retrospective analysis of thirteen pulmonary ADEs showed significant differences associated with quinapril and trandolapril, compared to other ACEIs and ARBs. Specifically, quinapril and trandolapril were found to have a statistically significantly higher incidence of pulmonary ADEs compared with other ACEIs as well as ARBs (P < 0.0001) for group comparison (i.e., ACEIs vs. ARBs vs. quinapril vs. trandolapril) and (P ≤ 0.0007) for pairwise comparison (i.e., ACEIs vs. quinapril, ACEIs vs. trandolapril, ARBs vs. quinapril, or ARBs vs. trandolapril). This study suggests that specific members of the ACEI antihypertensive class (quinapril and trandolapril) have a significantly higher cluster of pulmonary ADEs.
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Affiliation(s)
- Majid Jaberi-Douraki
- 1DATA Consortium, Manhattan, USA.
- Kansas State University Olathe, Olathe, KS, 66061-1304, USA.
- Department of Mathematics, Kansas State University, Manhattan, USA.
| | - Emma Meyer
- 1DATA Consortium, Manhattan, USA
- Division of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, USA
| | - Jim Riviere
- 1DATA Consortium, Manhattan, USA
- Kansas State University, Manhattan, USA
- North Carolina State University, Raleigh, USA
| | - Nuwan Indika Millagaha Gedara
- 1DATA Consortium, Manhattan, USA
- Kansas State University Olathe, Olathe, KS, 66061-1304, USA
- Department of Business Economics, University of Colombo, Colombo, Sri Lanka
| | - Jessica Kawakami
- 1DATA Consortium, Manhattan, USA
- Division of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, USA
- Molecular Biology and Biochemistry, School of Biological and Chemical Sciences, University of Missouri-Kansas City, Kansas City, USA
| | - Gerald J Wyckoff
- 1DATA Consortium, Manhattan, USA
- Division of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Missouri-Kansas City, Kansas City, USA
- Molecular Biology and Biochemistry, School of Biological and Chemical Sciences, University of Missouri-Kansas City, Kansas City, USA
| | - Xuan Xu
- 1DATA Consortium, Manhattan, USA
- Kansas State University Olathe, Olathe, KS, 66061-1304, USA
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Affiliation(s)
- Emmanuelle Vidal-Petiot
- Assistance Publique-Hôpitaux de Paris, Physiology department, Bichat-Claude Bernard University Hospital, 46 rue Henri Huchard, Paris, France. .,Université de Paris, Inserm U1149, 75018, Paris, France.
| | - Nathalie Gault
- INSERM CIC-EC 1425, hôpital Bichat Claude Bernard, 75018, Paris, France.,APHP.Nord, Département Epidémiologie Biostatistiques et Recherche Clinique, Hôpital Bichat, 75018, Paris, France
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Bourgeois FT, Gutiérrez-Sacristán A, Keller MS, Liu M, Hong C, Bonzel CL, Tan ALM, Aronow BJ, Boeker M, Booth J, Cruz Rojo J, Devkota B, García Barrio N, Gehlenborg N, Geva A, Hanauer DA, Hutch MR, Issitt RW, Klann JG, Luo Y, Mandl KD, Mao C, Moal B, Moshal KL, Murphy SN, Neuraz A, Ngiam KY, Omenn GS, Patel LP, Jiménez MP, Sebire NJ, Balazote PS, Serret-Larmande A, South AM, Spiridou A, Taylor DM, Tippmann P, Visweswaran S, Weber GM, Kohane IS, Cai T, Avillach P. International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries. JAMA Netw Open 2021; 4:e2112596. [PMID: 34115127 PMCID: PMC8196345 DOI: 10.1001/jamanetworkopen.2021.12596] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
IMPORTANCE Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients. OBJECTIVE To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study. MAIN OUTCOMES AND MEASURES Patient characteristics, clinical features, and medication use. RESULTS There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study's cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0- to 2-year (199 patients [30%]) and 12- to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19-directed medications. CONCLUSIONS AND RELEVANCE This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and identified common complications and laboratory abnormalities in children and youth with COVID-19 infection. Large-scale informatics-based approaches to integrate and analyze data across health care systems complement methods of disease surveillance and advance understanding of epidemiological and clinical features associated with COVID-19 in children and youth.
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Affiliation(s)
- Florence T. Bourgeois
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
- Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
| | | | - Mark S. Keller
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Molei Liu
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Chuan Hong
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Clara-Lea Bonzel
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Amelia L. M. Tan
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Bruce J. Aronow
- Departments of Biomedical Informatics, Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Ohio
| | - Martin Boeker
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Germany
| | - John Booth
- Digital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, London, United Kingdom
| | - Jaime Cruz Rojo
- Department of Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Spain
| | - Batsal Devkota
- Department of Biomedical Health Informatics and the Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Noelia García Barrio
- Department of Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Spain
| | - Nils Gehlenborg
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Alon Geva
- Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
- Department of Anesthesiology, Critical Care, and Pain Medicine, Boston Children’s Hospital, Boston, Massachusetts
| | - David A. Hanauer
- Department of Learning Health Sciences, University of Michigan, Ann Arbor
| | - Meghan R. Hutch
- Department of Preventive Medicine, Northwestern University, Evanston, Illinois
| | - Richard W. Issitt
- Digital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, London, United Kingdom
| | | | - Yuan Luo
- Department of Preventive Medicine, Northwestern University, Evanston, Illinois
| | - Kenneth D. Mandl
- Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
| | - Chengsheng Mao
- Department of Preventive Medicine, Northwestern University, Evanston, Illinois
| | - Bertrand Moal
- IAM Unit, Bordeaux University Hospital, Bordeaux, France
| | - Karyn L. Moshal
- Department of Infectious Diseases, Great Ormond Street Hospital for Children, London, United Kingdom
| | - Shawn N. Murphy
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Antoine Neuraz
- Department of Biomedical Informatics, Hôpital Necker-Enfants Malade, Assistance Publique Hôpitaux de Paris, University of Paris, Paris, France
| | - Kee Yuan Ngiam
- Department of Biomedical informatics, WiSDM, National University Health Systems Singapore, Singapore
| | - Gilbert S Omenn
- Department of Computational Medicine & Bioinformatics, Internal Medicine, Human Genetics, & School of Public Health, University of Michigan, Ann Arbor
| | - Lav P. Patel
- Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, Kansas City
| | | | - Neil J. Sebire
- Digital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, London, United Kingdom
| | | | | | - Andrew M. South
- Department of Pediatrics-Section of Nephrology, Brenner Children's Hospital, Wake Forest School of Medicine, Winston Salem, North Carolina
| | - Anastasia Spiridou
- Digital Research, Informatics and Virtual Environments (DRIVE), Great Ormond Street Hospital for Children, London, United Kingdom
| | - Deanne M. Taylor
- Department of Biomedical Health Informatics and the Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Pediatrics, Perelman Medical School at the University of Pennsylvania, Philadelphia
| | - Patric Tippmann
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Germany
| | - Shyam Visweswaran
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Griffin M. Weber
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Isaac S. Kohane
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Paul Avillach
- Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
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Derington CG, Cohen JB, Mohanty AF, Greene TH, Cook J, Ying J, Wei G, Herrick JS, Stevens VW, Jones BE, Wang L, Zheutlin AR, South AM, Hanff TC, Smith SM, Cooper-DeHoff RM, King JB, Alexander GC, Berlowitz DR, Ahmad FS, Penrod MJ, Hess R, Conroy MB, Fang JC, Rubin MA, Beddhu S, Cheung AK, Xian W, Weintraub WS, Bress AP. Angiotensin II receptor blocker or angiotensin-converting enzyme inhibitor use and COVID-19-related outcomes among US Veterans. PLoS One 2021; 16:e0248080. [PMID: 33891615 PMCID: PMC8064574 DOI: 10.1371/journal.pone.0248080] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 02/19/2021] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Angiotensin II receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACEIs) may positively or negatively impact outcomes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association of ARB or ACEI use with coronavirus disease 2019 (COVID-19)-related outcomes in US Veterans with treated hypertension using an active comparator design, appropriate covariate adjustment, and negative control analyses. METHODS AND FINDINGS In this retrospective cohort study of Veterans with treated hypertension in the Veterans Health Administration (01/19/2020-08/28/2020), we compared users of (A) ARB/ACEI vs. non-ARB/ACEI (excluding Veterans with compelling indications to reduce confounding by indication) and (B) ARB vs. ACEI among (1) SARS-CoV-2+ outpatients and (2) COVID-19 hospitalized inpatients. The primary outcome was all-cause hospitalization or mortality (outpatients) and all-cause mortality (inpatients). We estimated hazard ratios (HR) using propensity score-weighted Cox regression. Baseline characteristics were well-balanced between exposure groups after weighting. Among outpatients, there were 5.0 and 6.0 primary outcomes per 100 person-months for ARB/ACEI (n = 2,482) vs. non-ARB/ACEI (n = 2,487) users (HR 0.85, 95% confidence interval [CI] 0.73-0.99, median follow-up 87 days). Among outpatients who were ARB (n = 4,877) vs. ACEI (n = 8,704) users, there were 13.2 and 14.8 primary outcomes per 100 person-months (HR 0.91, 95%CI 0.86-0.97, median follow-up 85 days). Among inpatients who were ARB/ACEI (n = 210) vs. non-ARB/ACEI (n = 275) users, there were 3.4 and 2.0 all-cause deaths per 100 person months (HR 1.25, 95%CI 0.30-5.13, median follow-up 30 days). Among inpatients, ARB (n = 1,164) and ACEI (n = 2,014) users had 21.0 vs. 17.7 all-cause deaths, per 100 person-months (HR 1.13, 95%CI 0.93-1.38, median follow-up 30 days). CONCLUSIONS This observational analysis supports continued ARB or ACEI use for patients already using these medications before SARS-CoV-2 infection. The novel beneficial association observed among outpatients between users of ARBs vs. ACEIs on hospitalization or mortality should be confirmed with randomized trials.
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Affiliation(s)
- Catherine G. Derington
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Jordana B. Cohen
- Department of Medicine, Renal-Electrolyte and Hypertension Division, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States of America
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - April F. Mohanty
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Tom H. Greene
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - James Cook
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Jian Ying
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
| | - Guo Wei
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
| | - Jennifer S. Herrick
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
| | - Vanessa W. Stevens
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
| | - Barbara E. Jones
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Libo Wang
- Department of Medicine, Division of Cardiology, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Alexander R. Zheutlin
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Andrew M. South
- Department of Pediatrics, Section of Nephrology, Brenner Children’s Hospital, Wake Forest School of Medicine, Winston Salem, NC, United States of America
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston Salem, NC, United States of America
| | - Thomas C. Hanff
- Department of Medicine, Division of Cardiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Steven M. Smith
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States of America
| | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States of America
- Department of Medicine, University of Florida, College of Medicine, Gainesville, FL, United States of America
| | - Jordan B. King
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, United States of America
| | - G. Caleb Alexander
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Dan R. Berlowitz
- Department of Public Health; University of Massachusetts Lowell, Lowell, MA, United States of America
- Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States of America
| | - Faraz S. Ahmad
- Department of Medicine, Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
| | - M. Jason Penrod
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Rachel Hess
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Molly B. Conroy
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - James C. Fang
- Department of Medicine, Division of Cardiology, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Michael A. Rubin
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Srinivasan Beddhu
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Alfred K. Cheung
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Weiming Xian
- Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, United States of America
- Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine, Boston, MA, United States of America
| | | | - Adam P. Bress
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, United States of America
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, United States of America
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38
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Gault N, Esposito-Farèse M, Revest M, Inamo J, Cabié A, Polard É, Hulot JS, Ghosn J, Chirouze C, Deconinck L, Diehl JL, Poissy J, Epaulard O, Lefèvre B, Piroth L, De Montmollin E, Oziol E, Etienne M, Laouénan C, Rossignol P, Costagliola D, Vidal-Petiot E. Chronic use of renin-angiotensin-aldosterone system blockers and mortality in COVID-19: A multicenter prospective cohort and literature review. Fundam Clin Pharmacol 2021; 35:1141-1158. [PMID: 33876439 PMCID: PMC8250758 DOI: 10.1111/fcp.12683] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 03/22/2021] [Accepted: 04/14/2021] [Indexed: 01/09/2023]
Abstract
Aims The role of renin‐angiotensin‐aldosterone system (RAAS) blockers on the course of coronavirus disease 2019 (COVID‐19) is debated. We assessed the association between chronic use of RAAS blockers and mortality among inpatients with COVID‐19 and explored reasons for discrepancies in the literature. Methods and results We included adult hypertensive patients from a prospective nationwide cohort of 3512 inpatients with COVID‐19 up to June 30, 2020. Cox proportional hazard models with various adjustment or propensity weighting methods were used to estimate the hazard ratios (HR) of 30‐day mortality for chronic users versus non‐users of RAAS blockers. We analyzed data of 1160 hypertensive patients: 719 (62%) were male and 777 (67%) were older than 65 years. The main comorbidities were diabetes (n = 416, 36%), chronic cardiac disease (n = 401, 35%), and obesity (n = 340, 29%); 705 (61%) received oxygen therapy. We recorded 135 (11.6%) deaths within 30 days of diagnosis. We found no association between chronic use of RAAS blockers and mortality (unadjusted HR = 1.13, 95% CI [0.8–1.6]; propensity inverse probability treatment weighted HR = 1.09 [0.86‐1.39]; propensity standardized mortality ratio weighted HR = 1.08 [0.79–1.47]). Our comprehensive review of previous studies highlighted that significant associations were mostly found in unrestricted populations with inappropriate adjustment, or with biased in‐hospital exposure measurement. Conclusion Our results do not support previous concerns regarding these drugs, nor a potential protective effect as reported in previous poorly designed studies and meta‐analyses. RAAS blockers should not be discontinued during the pandemic, while in‐hospital management of these drugs will be clarified by randomized trials. NCT04262921.
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Affiliation(s)
- Nathalie Gault
- Centre d'Investigations cliniques-Epidémiologie Clinique 1425, INSERM, Hôpital Bichat, Paris, 75018, France.,Département Epidémiologie Biostatistiques et Recherche Clinique, AP-HP, Hôpital Bichat, Paris, 75018, France
| | - Marina Esposito-Farèse
- Centre d'Investigations cliniques-Epidémiologie Clinique 1425, INSERM, Hôpital Bichat, Paris, 75018, France.,URC Paris Nord, AP-HP DRCI, Hôpital Bichat, Paris, 75018, France
| | - Matthieu Revest
- Service des Maladies Infectieuses et Réanimation Médicale, Univ Rennes, INSERM UMR 1230, Bacterial Regulatory RNA and Medicine, CHU Rennes, Rennes, France
| | - Jocelyn Inamo
- Département de Cardiologie, EA7525, CHU Martinique, Fort-de-France, France
| | - André Cabié
- Inserm CIC 1424, Université des Antilles EA 7524, Service de maladies infectieuses et tropicales, CHU de Martinique, Fort-de-France, France
| | - Élisabeth Polard
- Department of Clinical Pharmacology, Pharmacovigilance, Pharmacoepidemiology and Drug Information Centre, Rennes University Hospital, Rennes, France
| | - Jean-Sébastien Hulot
- PARCC, INSERM, Université de Paris, Paris, 75015, France.,INSERM Centre d'Investigations cliniques-plurithématique 1418 and DMU CARTE, F-CRIN INI-CRCT network, AP-HP, Hôpital Européen Georges-Pompidou, Paris, 751015, France
| | - Jade Ghosn
- Service de Maladie Infectieuses et Tropicales, AP-HP, Hôpital Bichat, Paris, France
| | - Catherine Chirouze
- Service de Maladie Infectieuses et Tropicales, CHU Besançon, Besançon, France
| | - Laurène Deconinck
- Service de Maladie Infectieuses et Tropicales, AP-HP, Hôpital Bichat, Paris, France
| | - Jean-Luc Diehl
- Service de Médecine Intensive Réanimation, Laboratoire de Recherche Biochirurgicale (Fondation Carpentier), AP-HP, Hôpital Européen Georges-Pompidou, Paris, France.,UMR_S 1140, Innovations thérapeutiques en Hémostase, Université de Paris, INSERM, Paris, France
| | - Julien Poissy
- Inserm U1285, CHU Lille, Pôle de réanimation, UMR 8576 - UGSF - Unité de Glycobiologie Structurale et Fonctionnelle, Université de Lille, CNRS, Lille, France
| | - Olivier Epaulard
- Service de Maladies Infectieuses et Médecine Tropicale, CHU Grenoble Rhône Alpes, Grenoble, France
| | - Benjamin Lefèvre
- Service des Maladies Infectieuses et Tropicales, CHRU Nancy, Université de Lorraine, Nancy, France.,APEMAC, Université de Lorraine, Nancy, France
| | - Lionel Piroth
- Département d'infectiologie, Université de Bourgogne, CHU Dijon Bourgogne, Dijon, France
| | - Etienne De Montmollin
- Service de réanimation médicale et des maladies infectieuses, AP-HP, Hôpital Bichat, Paris, France.,IAME UMR 1137, INSERM, Université de Paris, Paris, France
| | - Eric Oziol
- Service de Médecine Hospitalière, CHU Beziers, Beziers, France
| | - Manuel Etienne
- Service des Maladies Infectieuses et Tropicales, CHU Rouen, Rouen, France
| | - Cédric Laouénan
- Centre d'Investigations cliniques-Epidémiologie Clinique 1425, INSERM, Hôpital Bichat, Paris, 75018, France.,Département Epidémiologie Biostatistiques et Recherche Clinique, AP-HP, Hôpital Bichat, Paris, 75018, France.,IAME UMR 1137, INSERM, Université de Paris, Paris, France
| | - Patrick Rossignol
- Centre d'Investigations cliniques-plurithématique 1433, INSERM U1116, CHRU Nancy, Université de Lorraine, INSERM, Nancy, France.,F-CRIN INI-CRCT network, Nancy, France
| | - Dominique Costagliola
- Institut Pierre Louis d'Épidémiologie et de Santé Publique (IPLESP), Sorbonne Université, INSERM, Paris, France
| | - Emmanuelle Vidal-Petiot
- Service de Physiologie rénale, AP-HP, Hôpital Bichat, Paris, France.,U1149, INSERM, Université de Paris, Paris, France
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39
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Gressens SB, Leftheriotis G, Dussaule JC, Flamant M, Levy BI, Vidal-Petiot E. Controversial Roles of the Renin Angiotensin System and Its Modulators During the COVID-19 Pandemic. Front Physiol 2021; 12:624052. [PMID: 33692701 PMCID: PMC7937723 DOI: 10.3389/fphys.2021.624052] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/12/2021] [Indexed: 12/15/2022] Open
Abstract
Since December 2019, the coronavirus 2019 (COVID-19) pandemic has rapidly spread and overwhelmed healthcare systems worldwide, urging physicians to understand how to manage this novel infection. Early in the pandemic, more severe forms of COVID-19 have been observed in patients with cardiovascular comorbidities, who are often treated with renin-angiotensin aldosterone system (RAAS)-blockers, such as angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs), but whether these are indeed independent risk factors is unknown. The cellular receptor for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the membrane-bound angiotensin converting enzyme 2 (ACE2), as for SARS-CoV(-1). Experimental data suggest that expression of ACE2 may be increased by RAAS-blockers, raising concerns that these drugs may facilitate viral cell entry. On the other hand, ACE2 is a key counter-regulator of the RAAS, by degrading angiotensin II into angiotensin (1-7), and may thereby mediate beneficial effects in COVID-19. These considerations have raised concerns about the management of these drugs, and early comments shed vivid controversy among physicians. This review will describe the homeostatic balance between ACE-angiotensin II and ACE2-angiotensin (1-7) and summarize the pathophysiological rationale underlying the debated role of the RAAS and its modulators in the context of the pandemic. In addition, we will review available evidence investigating the impact of RAAS blockers on the course and prognosis of COVID-19 and discuss why retrospective observational studies should be interpreted with caution. These considerations highlight the importance of solid evidence-based data in order to guide physicians in the management of RAAS-interfering drugs in the general population as well as in patients with more or less severe forms of SARS-CoV-2 infection.
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Affiliation(s)
- Simon B Gressens
- Department of Infectious and Tropical Diseases, Assistance Publique-Hôpitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France
| | - Georges Leftheriotis
- Laboratory of Molecular Physiology and Medicine, Université Cote d'Azur, Nice, France
| | - Jean-Claude Dussaule
- Sorbonne Université, INSERM, Unité des Maladies Rénales Fréquentes et Rares: des Mécanismes Moléculaires à la Médecine Personnalisée, AP-HP, Hôpital Tenon, Paris, France.,Faculty of Medicine, Sorbonne University, Paris, France
| | - Martin Flamant
- Department of Physiology, Assistance Publique-Hôpitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France.,Inserm U1149, Centre for Research on Inflammation, Université de Paris, Paris, France
| | | | - Emmanuelle Vidal-Petiot
- Department of Physiology, Assistance Publique-Hôpitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France.,Inserm U1149, Centre for Research on Inflammation, Université de Paris, Paris, France
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40
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Cohen JB, South AM, Shaltout HA, Sinclair MR, Sparks MA. Renin-angiotensin system blockade in the COVID-19 pandemic. Clin Kidney J 2021; 14:i48-i59. [PMID: 33796285 PMCID: PMC7929063 DOI: 10.1093/ckj/sfab026] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 01/19/2021] [Indexed: 01/08/2023] Open
Abstract
In the early months of the coronavirus disease 2019 (COVID-19) pandemic, a hypothesis emerged suggesting that pharmacologic inhibitors of the renin–angiotensin system (RAS) may increase COVID-19 severity. This hypothesis was based on the role of angiotensin-converting enzyme 2 (ACE2), a counterregulatory component of the RAS, as the binding site for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), allowing viral entry into host cells. Extrapolations from prior evidence led to speculation that upregulation of ACE2 by RAS blockade may increase the risk of adverse outcomes from COVID-19. However, counterarguments pointed to evidence of potential protective effects of ACE2 and RAS blockade with regard to acute lung injury, as well as substantial risks from discontinuing these commonly used and important medications. Here we provide an overview of classic RAS physiology and the crucial role of ACE2 in systemic pathways affected by COVID-19. Additionally, we critically review the physiologic and epidemiologic evidence surrounding the interactions between RAS blockade and COVID-19. We review recently published trial evidence and propose important future directions to improve upon our understanding of these relationships.
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Affiliation(s)
- Jordana B Cohen
- Renal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew M South
- Section of Nephrology, Department of Pediatrics, Brenner Children's Hospital, Wake Forest School of Medicine, Winston Salem, NC, USA.,Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston Salem, NC, USA.,Department of Surgery, Hypertension and Vascular Research, Wake Forest School of Medicine, Winston Salem, NC, USA.,Cardiovascular Sciences Center, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Hossam A Shaltout
- Department of Surgery, Hypertension and Vascular Research, Wake Forest School of Medicine, Winston Salem, NC, USA.,Cardiovascular Sciences Center, Wake Forest School of Medicine, Winston Salem, NC, USA.,Department of Obstetrics and Gynecology, Wake Forest School of Medicine, Winston Salem, NC, USA.,Department of Pharmacology and Toxicology, School of Pharmacy, University of Alexandria, Alexandria, Egypt
| | - Matthew R Sinclair
- Division of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.,Duke Clinical Research Institute, Durham, NC, USA
| | - Matthew A Sparks
- Division of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA.,Renal Section, Durham VA Health Care System, Durham, NC, USA
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