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.

Autor:	Hong C; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Zhang HG; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., L'Yi S; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Weber G; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Avillach P; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Tan BWQ; Department of Medicine, National University Hospital, Singapore., Gutiérrez-Sacristán A; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Bonzel CL; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Palmer NP; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Malovini A; Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy., Tibollo V; Laboratory of Informatics and Systems Engineering for Clinical Research, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy., Luo Y; Department of Preventive Medicine, Northwestern University, Evanston, Illinois, USA., Hutch MR; Department of Preventive Medicine, Northwestern University, Evanston, Illinois, USA., Liu M; Department of Biostatistics, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA., Bourgeois F; Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA., Bellazzi R; Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy., Chiovato L; Unit of Internal Medicine and Endocrinology, Istituti Clinici Scientifici Maugeri SpA SB IRCCS, Pavia, Lombardia, Italy., Sanz Vidorreta FJ; Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA., Le TT; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA., Wang X; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Yuan W; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Neuraz A; Department of Biomedical Informatics, Hopital Universitaire Necker-Enfants Malades, Paris, Île-de-France, France., Benoit V; IT department, Innovation & Data, APHP Greater Paris University Hospital, Paris, France., Moal B; IAM unit, Bordeaux University Hospital, Bordeaux, France., Morris M; Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA., Hanauer DA; Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan, USA., Maidlow S; MICHR Informatics, University of Michigan, Ann Arbor, Michigan, USA., Wagholikar K; Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA., Murphy S; Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA., Estiri H; Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA., Makoudjou A; Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany., Tippmann P; Institute of Medical Biometry and Statistics, Medical Center-University of Freiburg, Freiburg, Baden-Württemberg, Germany., Klann J; Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA., Follett RW; Department of Medicine, David Geffen School of Medicine, Los Angeles, California, USA., Gehlenborg N; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Omenn GS; Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA., Xia Z; Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA., Dagliati A; Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy., Visweswaran S; Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Kansas, USA., Patel LP; Department of Internal Medicine, Division of Medical Informatics, University of Kansas Medical Center, Kansas City, Kansas, USA., Mowery DL; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA., Schriver ER; Data Analytics Center, University of Pennsylvania Health System, Philadelphia, Pennsylvania, USA., Samayamuthu MJ; Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA., Kavuluru R; Institute for Biomedical Informatics, University of Kentucky, Lexington, Kentucky, USA., Lozano-Zahonero S; Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany., Zöller D; Institute of Medical Biometry and Statistics, University of Freiburg Faculty of Medicine, Freiburg, Baden-Württemberg, Germany., Tan ALM; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Tan BWL; Department of Medicine, National University Hospital, Singapore., Ngiam KY; Department of Surgery, National University Hospital, Singapore., Holmes JH; 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., Schubert P; Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA., Cho K; Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA., Ho YL; Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA., Beaulieu-Jones BK; Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Pedrera-Jiménez M; Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain., García-Barrio N; Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain., Serrano-Balazote P; Health Informatics, Hospital Universitario 12 de Octubre, Madrid, Comunidad de Madrid, Spain., Kohane I; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., South A; Department of Pediatrics, Section of Nephrology, Wake Forest University, Winston Salem, North Carolina, USA., Brat GA; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA., Cai T; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA tcai@hsph.harvard.edu.
Jazyk:	angličtina
Zdroj:	BMJ open [BMJ Open] 2022 Jun 23; Vol. 12 (6), pp. e057725. Date of Electronic Publication: 2022 Jun 23.
DOI:	10.1136/bmjopen-2021-057725
Abstrakt:	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. Competing Interests: Competing interests: None declared. (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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