Back to Search Start Over

International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study

Authors :
Weber, Griffin M
Zhang, Harrison G
L'Yi, Sehi
Bonzel, Clara-Lea
Hong, Chuan
Avillach, Paul
Gutiérrez-Sacristán, Alba
Palmer, Nathan P
Tan, Amelia Li Min
Wang, Xuan
Yuan, William
Gehlenborg, Nils
Alloni, Anna
Amendola, Danilo F
Bellasi, Antonio
Bellazzi, Riccardo
Beraghi, Michele
Bucalo, Mauro
Chiovato, Luca
Cho, Kelly
Dagliati, Arianna
Estiri, Hossein
Follett, Robert W
García Barrio, Noelia
Hanauer, David A
Henderson, Darren W
Ho, Yuk-Lam
Holmes, John H
Hutch, Meghan R
Kavuluru, Ramakanth
Kirchoff, Katie
Klann, Jeffrey G
Krishnamurthy, Ashok K
Le, Trang T
Liu, Molei
Loh, Ne Hooi Will
Lozano-Zahonero, Sara
Luo, Yuan
Maidlow, Sarah
Makoudjou, Adeline
Malovini, Alberto
Martins, Marcelo Roberto
Moal, Bertrand
Morris, Michele
Mowery, Danielle L
Murphy, Shawn N
Neuraz, Antoine
Ngiam, Kee Yuan
Okoshi, Marina P
Omenn, Gilbert S
Patel, Lav P
Pedrera Jiménez, Miguel
Prudente, Robson A
Samayamuthu, Malarkodi Jebathilagam
Sanz Vidorreta, Fernando J
Schriver, Emily R
Schubert, Petra
Serrano Balazote, Pablo
Tan, Byorn WL
Tanni, Suzana E
Tibollo, Valentina
Visweswaran, Shyam
Wagholikar, Kavishwar B
Xia, Zongqi
Zöller, Daniela
Kohane, Isaac S
Cai, Tianxi
South, Andrew M
Brat, Gabriel A
Harvard Medical School
BIOMERIS (BIOMedical Research Informatics Solutions)
Universidade Estadual Paulista (UNESP)
Ente Ospedaliero Cantonale
University of Pavia
Azienda Socio-Sanitaria Territoriale di Pavia
Istituti Clinici Scientifici Maugeri SpA SB IRCCS
Veterans Affairs Boston Healthcare System
Massachusetts General Hospital
Los Angeles
Hospital Universitario 12 de Octubre
University of Michigan Medical School
University of Kentucky
University of Pennsylvania Perelman School of Medicine
Northwestern University
Medical University of South Carolina
University of North Carolina at Chapel Hill
Harvard T.H. Chan School of Public Health
National University Health System
University of Freiburg
University of Michigan
Bordeaux University Hospital
University of Pittsburgh
University of Paris
University of Kansas Medical Center
University of Pennsylvania Health System
Wake Forest School of Medicine
Service d'informatique médicale et biostatistiques [CHU Necker]
CHU Necker - Enfants Malades [AP-HP]
Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)
Health data- and model- driven Knowledge Acquisition (HeKA)
Inria de Paris
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138))
École pratique des hautes études (EPHE)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université de Paris (UP)-École pratique des hautes études (EPHE)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université de Paris (UP)
Université de Paris - UFR Médecine Paris Centre [Santé] (UP Médecine Paris Centre)
Université de Paris (UP)
Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Necker - Enfants Malades [AP-HP]
Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPC)-École pratique des hautes études (EPHE)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPC)
Université Paris Cité - UFR Médecine Paris Centre [Santé] (UPC Médecine Paris Centre)
Université Paris Cité (UPC)
École Pratique des Hautes Études (EPHE)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)-École Pratique des Hautes Études (EPHE)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)
UFR Médecine [Santé] - Université Paris Cité (UFR Médecine UPCité)
Université Paris Cité (UPCité)
Source :
Journal of Medical Internet Research, Scopus, Repositório Institucional da UNESP, Universidade Estadual Paulista (UNESP), instacron:UNESP, Journal of Medical Internet Research, JMIR Publications, 2021, 23 (10), pp.e31400. ⟨10.2196/31400⟩, Journal of Medical Internet Research, 2021, 23 (10), pp.e31400. ⟨10.2196/31400⟩
Publication Year :
2021
Publisher :
JMIR Publications Inc., 2021.

Abstract

Made available in DSpace on 2022-04-29T08:35:26Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-10-01 National Human Genome Research Institute National Center for Advancing Translational Sciences National Heart, Lung, and Blood Institute National Institutes of Health U.S. National Library of Medicine National Institute of Neurological Disorders and Stroke Canadian Thoracic Society 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. Department of Biomedical Informatics Harvard Medical School BIOMERIS (BIOMedical Research Informatics Solutions) Clinical Research Unit Botucatu Medical School São Paulo State University Division of Nephrology Department of Medicine Ente Ospedaliero Cantonale Department of Electrical Computer and Biomedical Engineering University of Pavia Information Technology Department Azienda Socio-Sanitaria Territoriale di Pavia Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Massachusetts Veterans Epidemiology Research and Information Center Veterans Affairs Boston Healthcare System Department of Medicine Massachusetts General Hospital Department of Medicine David Geffen School of Medicine University of California Los Angeles Health Informatics Hospital Universitario 12 de Octubre Department of Learning Health Sciences University of Michigan Medical School Department of Biomedical Informatics University of Kentucky Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Institute for Biomedical Informatics University of Pennsylvania Perelman School of Medicine Department of Preventive Medicine Northwestern University Institute for Biomedical Informatics University of Kentucky Medical University of South Carolina Department of Computer Science Renaissance Computing Institute University of North Carolina at Chapel Hill Department of Biostatistics Harvard T.H. Chan School of Public Health Department of Anaesthesia National University Health System Institute of Medical Biometry and Statistics Faculty of Medicine and Medical Center University of Freiburg Michigan Institute for Clinical & Health Research Informatics University of Michigan Laboratory of Informatics and Systems Engineering for Clinical Research Istituti Clinici Scientifici Maugeri SpA SB IRCCS Clinical Hospital of Botucatu Medical School São Paulo State University Informatique et Archivistique Médicales Unit Bordeaux University Hospital Department of Biomedical Informatics University of Pittsburgh Department of Neurology Massachusetts General Hospital Department of Biomedical Informatics Hôpital Necker-Enfants Malade Assistance Publique Hôpitaux de Paris University of Paris Department of Biomedical Informatics Institute for Digital Medicine National University Health System Internal Medicine Department Botucatu Medical School São Paulo State University Department of Computational Medicine & Bioinformatics Internal Medicine Human Genetics and Public Health University of Michigan Division of Medical Informatics Department of Internal Medicine University of Kansas Medical Center Data Analytics Center University of Pennsylvania Health System Department of Medicine National University Health System Department of Neurology University of Pittsburgh Section of Nephrology Department of Pediatrics Brenner Children's Hospital Wake Forest School of Medicine Clinical Research Unit Botucatu Medical School São Paulo State University Clinical Hospital of Botucatu Medical School São Paulo State University Internal Medicine Department Botucatu Medical School São Paulo State University National Human Genome Research Institute: 3U01HG008685-05S2 National Human Genome Research Institute: 5R01HG009174-04 National Center for Advancing Translational Sciences: 5UL1TR001857-05 National Heart, Lung, and Blood Institute: K23HL148394 National Heart, Lung, and Blood Institute: L40HL148910 National Institutes of Health: P30ES017885 U.S. National Library of Medicine: R01LM012095 U.S. National Library of Medicine: R01LM013345 National Institute of Neurological Disorders and Stroke: R01NS098023 U.S. National Library of Medicine: T15LM007092 National Institutes of Health: U24CA210967 National Center for Advancing Translational Sciences: UL1TR000005 National Center for Advancing Translational Sciences: UL1TR001420 National Center for Advancing Translational Sciences: UL1TR001450 National Center for Advancing Translational Sciences: UL1TR001857 National Center for Advancing Translational Sciences: UL1TR001878 National Center for Advancing Translational Sciences: UL1TR001881 Canadian Thoracic Society: UL1TR001998 National Center for Advancing Translational Sciences: UL1TR002240 Canadian Thoracic Society: UL1TR002366 National Center for Advancing Translational Sciences: UL1TR002541

Details

ISSN :
14388871
Volume :
23
Database :
OpenAIRE
Journal :
Journal of Medical Internet Research
Accession number :
edsair.doi.dedup.....09845a07ae9436ffc5d9e676c0f9d31d
Full Text :
https://doi.org/10.2196/31400