Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study

Objective To examine age, gender, and temporal differences in baseline characteristics and clinical outcomes of adult patients hospitalised with COVID-19.Design A cohort study using deidentified electronic medical records from a Global Research Network.Setting/Participants 67 456 adult patients hosp...

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Main Authors: Jie Zhang, Peter Yu, Sudhakar Manne, Ying Bao, Cathy W Critchlow, Julia Zhu, Zhongyuan Wei, Manasi Suryavanshi, Xiu Chen, Qian Xia, Jenny Jiang, Olulade Ayodele, Brian D Bradbury, Corinne Brooks, Carolyn A Brown, Alvan Cheng, Giovanna Devercelli, Vivek Gandhi, Kathleen Gondek, Ajit A Londhe, Junjie Ma, Michele Jonsson-Funk, Hillary A Keenan, Kaili Ren, Lynn Sanders, Linyun Zhou
Format: Article
Language:English
Published: BMJ Publishing Group 2021-08-01
Series:BMJ Open
Online Access:https://bmjopen.bmj.com/content/11/8/e051588.full
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author Jie Zhang
Peter Yu
Sudhakar Manne
Ying Bao
Cathy W Critchlow
Julia Zhu
Zhongyuan Wei
Manasi Suryavanshi
Xiu Chen
Qian Xia
Jenny Jiang
Olulade Ayodele
Brian D Bradbury
Corinne Brooks
Carolyn A Brown
Alvan Cheng
Giovanna Devercelli
Vivek Gandhi
Kathleen Gondek
Ajit A Londhe
Junjie Ma
Michele Jonsson-Funk
Hillary A Keenan
Kaili Ren
Lynn Sanders
Linyun Zhou
author_facet Jie Zhang
Peter Yu
Sudhakar Manne
Ying Bao
Cathy W Critchlow
Julia Zhu
Zhongyuan Wei
Manasi Suryavanshi
Xiu Chen
Qian Xia
Jenny Jiang
Olulade Ayodele
Brian D Bradbury
Corinne Brooks
Carolyn A Brown
Alvan Cheng
Giovanna Devercelli
Vivek Gandhi
Kathleen Gondek
Ajit A Londhe
Junjie Ma
Michele Jonsson-Funk
Hillary A Keenan
Kaili Ren
Lynn Sanders
Linyun Zhou
author_sort Jie Zhang
collection DOAJ
description Objective To examine age, gender, and temporal differences in baseline characteristics and clinical outcomes of adult patients hospitalised with COVID-19.Design A cohort study using deidentified electronic medical records from a Global Research Network.Setting/Participants 67 456 adult patients hospitalised with COVID-19 from the USA; 7306 from Europe, Latin America and Asia-Pacific between February 2020 and January 2021.Results In the US cohort, compared with patients 18–34 years old, patients ≥65 had a greater risk of intensive care unit (ICU) admission (adjusted HR (aHR) 1.73, 95% CI 1.58 to 1.90), acute respiratory distress syndrome(ARDS)/respiratory failure (aHR 1.86, 95% CI 1.76 to 1.96), invasive mechanical ventilation (IMV, aHR 1.93, 95% CI, 1.73 to 2.15), and all-cause mortality (aHR 5.6, 95% CI 4.36 to 7.18). Men appeared to be at a greater risk for ICU admission (aHR 1.34, 95% CI 1.29 to 1.39), ARDS/respiratory failure (aHR 1.24, 95% CI1.21 to 1.27), IMV (aHR 1.38, 95% CI 1.32 to 1.45), and all-cause mortality (aHR 1.16, 95% CI 1.08 to 1.24) compared with women. Moreover, we observed a greater risk of adverse outcomes during the early pandemic (ie, February–April 2020) compared with later periods. In the ex-US cohort, the age and gender trends were similar; for the temporal trend, the highest proportion of patients with all-cause mortality were also in February–April 2020; however, the highest percentages of patients with IMV and ARDS/respiratory failure were in August–October 2020 followed by February–April 2020.Conclusions This study provided valuable information on the temporal trends of characteristics and outcomes of hospitalised adult COVID-19 patients in both USA and ex-USA. It also described the population at a potentially greater risk for worse clinical outcomes by identifying the age and gender differences. Together, the information could inform the prevention and treatment strategies of COVID-19. Furthermore, it can be used to raise public awareness of COVID-19’s impact on vulnerable populations.
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spelling doaj-art-0e3c644e58f9442c8c9f5cc25b1c48192024-12-08T03:40:12ZengBMJ Publishing GroupBMJ Open2044-60552021-08-0111810.1136/bmjopen-2021-051588Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort studyJie Zhang0Peter Yu1Sudhakar Manne2Ying Bao3Cathy W Critchlow4Julia Zhu5Zhongyuan Wei6Manasi Suryavanshi7Xiu Chen8Qian Xia9Jenny Jiang10Olulade Ayodele11Brian D Bradbury12Corinne Brooks13Carolyn A Brown14Alvan Cheng15Giovanna Devercelli16Vivek Gandhi17Kathleen Gondek18Ajit A Londhe19Junjie Ma20Michele Jonsson-Funk21Hillary A Keenan22Kaili Ren23Lynn Sanders24Linyun Zhou252 Guangdong Provincial Key Laboratory of Digestive Cancer Research, Sun Yat-sen University, Shenzhen, Guangdong, China2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA1Bristol-Myers Squibb, Princeton, United States of America4 Research & Development Strategy & Operations, Amgen, Inc, Thousand Oaks, California, USAOphthalmology, Mater Misericordiae University Hospital, Dublin, Ireland1 Center for Observational Research and Data Science, Bristol-Myers Squibb, Princeton, New Jersey, USA1 Center for Observational Research and Data Science, Bristol-Myers Squibb, Princeton, New Jersey, USA1 Center for Observational Research and Data Science, Bristol-Myers Squibb, Princeton, New Jersey, USA1 Center for Observational Research and Data Science, Bristol-Myers Squibb, Princeton, New Jersey, USA1 Center for Observational Research and Data Science, Bristol-Myers Squibb, Princeton, New Jersey, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA3 Center for Observational Research, Amgen, Inc, Thousand Oaks, California, USA3 Center for Observational Research, Amgen, Inc, Thousand Oaks, California, USA3 Center for Observational Research, Amgen, Inc, Thousand Oaks, California, USA3 Center for Observational Research, Amgen, Inc, Thousand Oaks, California, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA3 Center for Observational Research, Amgen, Inc, Thousand Oaks, California, USA3 Center for Observational Research, Amgen, Inc, Thousand Oaks, California, USA5 Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USA2 Data Sciences Institute, Takeda Pharmaceutical Company Limited, Cambridge, Massachusetts, USAObjective To examine age, gender, and temporal differences in baseline characteristics and clinical outcomes of adult patients hospitalised with COVID-19.Design A cohort study using deidentified electronic medical records from a Global Research Network.Setting/Participants 67 456 adult patients hospitalised with COVID-19 from the USA; 7306 from Europe, Latin America and Asia-Pacific between February 2020 and January 2021.Results In the US cohort, compared with patients 18–34 years old, patients ≥65 had a greater risk of intensive care unit (ICU) admission (adjusted HR (aHR) 1.73, 95% CI 1.58 to 1.90), acute respiratory distress syndrome(ARDS)/respiratory failure (aHR 1.86, 95% CI 1.76 to 1.96), invasive mechanical ventilation (IMV, aHR 1.93, 95% CI, 1.73 to 2.15), and all-cause mortality (aHR 5.6, 95% CI 4.36 to 7.18). Men appeared to be at a greater risk for ICU admission (aHR 1.34, 95% CI 1.29 to 1.39), ARDS/respiratory failure (aHR 1.24, 95% CI1.21 to 1.27), IMV (aHR 1.38, 95% CI 1.32 to 1.45), and all-cause mortality (aHR 1.16, 95% CI 1.08 to 1.24) compared with women. Moreover, we observed a greater risk of adverse outcomes during the early pandemic (ie, February–April 2020) compared with later periods. In the ex-US cohort, the age and gender trends were similar; for the temporal trend, the highest proportion of patients with all-cause mortality were also in February–April 2020; however, the highest percentages of patients with IMV and ARDS/respiratory failure were in August–October 2020 followed by February–April 2020.Conclusions This study provided valuable information on the temporal trends of characteristics and outcomes of hospitalised adult COVID-19 patients in both USA and ex-USA. It also described the population at a potentially greater risk for worse clinical outcomes by identifying the age and gender differences. Together, the information could inform the prevention and treatment strategies of COVID-19. Furthermore, it can be used to raise public awareness of COVID-19’s impact on vulnerable populations.https://bmjopen.bmj.com/content/11/8/e051588.full
spellingShingle Jie Zhang
Peter Yu
Sudhakar Manne
Ying Bao
Cathy W Critchlow
Julia Zhu
Zhongyuan Wei
Manasi Suryavanshi
Xiu Chen
Qian Xia
Jenny Jiang
Olulade Ayodele
Brian D Bradbury
Corinne Brooks
Carolyn A Brown
Alvan Cheng
Giovanna Devercelli
Vivek Gandhi
Kathleen Gondek
Ajit A Londhe
Junjie Ma
Michele Jonsson-Funk
Hillary A Keenan
Kaili Ren
Lynn Sanders
Linyun Zhou
Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study
BMJ Open
title Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study
title_full Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study
title_fullStr Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study
title_full_unstemmed Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study
title_short Characteristics and outcomes of hospitalised adults with COVID-19 in a Global Health Research Network: a cohort study
title_sort characteristics and outcomes of hospitalised adults with covid 19 in a global health research network a cohort study
url https://bmjopen.bmj.com/content/11/8/e051588.full
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