TY - JOUR
T1 - International changes in COVID-19 clinical trajectories across 315 hospitals and 6 countries
T2 - Retrospective cohort study
AU - The Consortium For Clinical Characterization Of COVID-19 By EHR (4CE)
AU - Weber, Griffin M.
AU - Zhang, Harrison G.
AU - L'Yi, Sehi
AU - Bonzel, Clara Lea
AU - Hong, Chuan
AU - Avillach, Paul
AU - Gutiérrez-Sacristán, Alba
AU - Palmer, Nathan P.
AU - Tan, Amelia Li Min
AU - Wang, Xuan
AU - Yuan, William
AU - Gehlenborg, Nils
AU - Alloni, Anna
AU - Amendola, Danilo F.
AU - Bellasi, Antonio
AU - Bellazzi, Riccardo
AU - Beraghi, Michele
AU - Bucalo, Mauro
AU - Chiovato, Luca
AU - Cho, Kelly
AU - Dagliati, Arianna
AU - Estiri, Hossein
AU - Follett, Robert W.
AU - Barrio, Noelia García
AU - Hanauer, David A.
AU - Henderson, Darren W.
AU - Ho, Yuk Lam
AU - Holmes, John H.
AU - Hutch, Meghan R.
AU - Kavuluru, Ramakanth
AU - Kirchoff, Katie
AU - Klann, Jeffrey G.
AU - Krishnamurthy, Ashok K.
AU - Le, Trang T.
AU - Liu, Molei
AU - Loh, Ne Hooi Will
AU - Lozano-Zahonero, Sara
AU - Luo, Yuan
AU - Maidlow, Sarah
AU - Makoudjou, Adeline
AU - Malovini, Alberto
AU - Martins, Marcelo Roberto
AU - Moal, Bertrand
AU - Morris, Michele
AU - Mowery, Danielle L.
AU - Murphy, Shawn N.
AU - Neuraz, Antoine
AU - Ngiam, Kee Yuan
AU - Okoshi, Marina P.
AU - Omenn, Gilbert S.
N1 - Funding Information:
GMW is supported by National Institutes of Health (NIH)/National Center for Advancing Translational Sciences (NCATS) UL1TR002541 and UL1TR000005, NIH/National Library of Medicine (NLM) R01LM013345, and NIH/National Human Genome Research Institute (NHGRI) 3U01HG008685-05S2. NG is supported by NIH/NLM T15LM007092. DAH is supported by NCATS UL1TR002240. RK is supported by Clinical and Translational Science Awards (CTSA) Award UL1TR001998. KK is supported by NIH/NCATS UL1TR001450. DLM is supported by NIH/NCATS UL1TR001878. SNM is supported by NIH/NCATS 5UL1TR001857-05 and NIH/NHGRI 5R01HG009174-04. GSO is supported by NIH P30ES017885 and U24CA210967. LPP is supported by CTSA Award UL1TR002366. JS is supported by NIH/NCATS UL1TR001881. SV is supported by NIH/NLM R01LM012095 and NIH/NCATS UL1TR001857. ZX is supported by National Institute of Neurological Disorders and Stroke (NINDS) R01NS098023. AMS is supported by NIH/National Heart, Lung, and Blood Institute (NHLBI) K23HL148394, L40HL148910, and NIH/NCATS UL1TR001420.
Publisher Copyright:
© 2021 Journal of Medical Internet Research. All rights reserved.
PY - 2021/10
Y1 - 2021/10
N2 - 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.
AB - 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.
KW - COVID-19
KW - Electronic health records
KW - Federated study
KW - Laboratory trajectory
KW - Meta-analysis
KW - Retrospective cohort study
KW - SARS-CoV-2
KW - Severe COVID-19
UR - http://www.scopus.com/inward/record.url?scp=85117168924&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85117168924&partnerID=8YFLogxK
U2 - 10.2196/31400
DO - 10.2196/31400
M3 - Article
C2 - 34533459
AN - SCOPUS:85117168924
VL - 23
JO - Journal of Medical Internet Research
JF - Journal of Medical Internet Research
SN - 1439-4456
IS - 10
M1 - e31400
ER -