Association of pre-existing comorbidities with mortality and disease severity among 167,500 individuals with COVID-19 in Canada: A population-based cohort study
The novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that ca...
Gespeichert in:
Veröffentlicht in: | PloS one 2021-10, Vol.16 (10), p.e0258154-e0258154 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | e0258154 |
---|---|
container_issue | 10 |
container_start_page | e0258154 |
container_title | PloS one |
container_volume | 16 |
creator | Ge, Erjia Li, Yanhong Wu, Shishi Candido, Elisa Wei, Xiaolin |
description | The novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada. We conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35-3.34; p |
doi_str_mv | 10.1371/journal.pone.0258154 |
format | Article |
fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2579349322</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A677999435</galeid><doaj_id>oai_doaj_org_article_b3bc1877ef744281b3cb038b5fe78ab3</doaj_id><sourcerecordid>A677999435</sourcerecordid><originalsourceid>FETCH-LOGICAL-c669t-f45fb31133d18e7e227d770e5cd34d449da376b0cc28ff9572afa5ff08c468c13</originalsourceid><addsrcrecordid>eNqNk12L1DAUhoso7rr6DwQDgijYMWnSpPFCGMavgYUBP_Y2pPmYydJpapOOO__Gn2pmpspW9kJ6kXLyvO-bHHKy7CmCM4QZenPth76VzazzrZnBoqxQSe5l54jjIqcFxPdv_Z9lj0K4hrDEFaUPszNMKIKQsPPs1zwEr5yMzrfAW9D1Jjc3LkTXroHyW9_XTrvoTAA_XdyAVIiycXEPZKuBdsHIYEAwO9Mfi1ufdIiy1yWEwLXa7ZweZDOqF6ur5fsc8bQDFrKVWr4Fc9D5bmiOJ8jr5KZT7ibFgBAHvX-cPbBJb56M60X2_eOHb4vP-eXq03Ixv8wVpTzmlpS2xghhrFFlmCkKphmDplQaE00I1xIzWkOlispaXrJCWllaCytFaKUQvsienXy7xgcxNjeIomQck9THIhHLE6G9vBZd77ay3wsvnTgWfL8Wso9ONUbUuFaoYsxYRkhRoRqrGuKqLq1hlaxx8no3pg311mhl2tjLZmI63WndRqz9TlSEI07KZPByNOj9j8GEKLYuKNM0sjV-OJ2bFpQXNKHP_0Hvvt1IrWW6gGutT7nqYCrmlDHOOcGH2NkdVPq02TqVXqJ1qT4RvJoIEhPNTVzLIQSx_Prl_9nV1ZR9cYvdGNnETfDNcHhFYQqSE6h6H0Jv7N8mIygOg_SnG-IwSGIcJPwb9N0QKg</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2579349322</pqid></control><display><type>article</type><title>Association of pre-existing comorbidities with mortality and disease severity among 167,500 individuals with COVID-19 in Canada: A population-based cohort study</title><source>Public Library of Science (PLoS) Journals Open Access</source><source>DOAJ Directory of Open Access Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Ge, Erjia ; Li, Yanhong ; Wu, Shishi ; Candido, Elisa ; Wei, Xiaolin</creator><contributor>Augusto, Orvalho</contributor><creatorcontrib>Ge, Erjia ; Li, Yanhong ; Wu, Shishi ; Candido, Elisa ; Wei, Xiaolin ; Augusto, Orvalho</creatorcontrib><description><![CDATA[The novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada. We conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35-3.34; p<0.001), and the risk substantially was elevated from 2.14 (95%CI 1.76-2.60) to 4.81 (95%CI 3.95-5.85) times as the number of comorbidities increased from one to five or more. Significant predictors for mortality included comorbidities such as solid organ transplant (HR = 3.06, 95%CI 2.03-4.63; p<0.001), dementia (HR = 1.46, 95%CI 1.35-1.58; p<0.001), chronic kidney disease (HR = 1.45, 95%CI 1.34-1.57; p<0.001), severe mental illness (HR = 1.42, 95%CI%, 1.12-1.80; p<0.001), cardiovascular disease (CVD) (HR = 1.22, 95%CI, 1.15-1.30), diabetes (HR = 1.19, 95%, 1.12-1.26; p<0.001), chronic obstructive pulmonary disease (COPD) (HR = 1.19, 95%CI 1.12-1.26; p<0.001), cancer (HR = 1.17, 95%CI, 1.09-1.27; p<0.001), hypertension (HR = 1.16, 95%CI, 1.07-1.26; p<0.001). Compared to their effect in older age groups, comorbidities were associated with higher risk of mortality and severity in individuals under 50 years old. Individuals with five or more comorbidities in the below 50 years age group had 395.44 (95%CI, 57.93-2699.44, p<0.001) times higher risk of mortality compared to those without. Limitations include that data were collected during 2020 when the new variants of concern were not predominant, and that the ICES databases do not contain detailed individual-level socioeconomic and racial variables. We found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.]]></description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0258154</identifier><identifier>PMID: 34610047</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Age ; Arthritis ; Asthma ; Biology and Life Sciences ; Cancer ; Cardiovascular diseases ; Chronic illnesses ; Chronic obstructive pulmonary disease ; Cohort analysis ; Comorbidity ; Complications and side effects ; Coronaviruses ; COVID-19 ; Dementia disorders ; Demographic variables ; Diabetes ; Diabetes mellitus ; Economic models ; Health insurance ; Health risks ; Heart diseases ; HIV ; Human immunodeficiency virus ; Hypertension ; Illnesses ; Kidney diseases ; Kidney transplantation ; Kidneys ; Lung diseases ; Medicine and Health Sciences ; Mental disorders ; Mortality ; Mortality risk ; Obstructive lung disease ; Patient outcomes ; People and places ; Population studies ; Population-based studies ; Prognosis ; Public health ; Regression analysis ; Regression models ; Rheumatoid arthritis ; Risk analysis ; Risk factors ; Social factors ; Socio-economic aspects ; Socioeconomics ; Vaccination ; Viral diseases ; World population</subject><ispartof>PloS one, 2021-10, Vol.16 (10), p.e0258154-e0258154</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Ge et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Ge et al 2021 Ge et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c669t-f45fb31133d18e7e227d770e5cd34d449da376b0cc28ff9572afa5ff08c468c13</citedby><cites>FETCH-LOGICAL-c669t-f45fb31133d18e7e227d770e5cd34d449da376b0cc28ff9572afa5ff08c468c13</cites><orcidid>0000-0002-3076-2650</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8491945/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8491945/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids></links><search><contributor>Augusto, Orvalho</contributor><creatorcontrib>Ge, Erjia</creatorcontrib><creatorcontrib>Li, Yanhong</creatorcontrib><creatorcontrib>Wu, Shishi</creatorcontrib><creatorcontrib>Candido, Elisa</creatorcontrib><creatorcontrib>Wei, Xiaolin</creatorcontrib><title>Association of pre-existing comorbidities with mortality and disease severity among 167,500 individuals with COVID-19 in Canada: A population-based cohort study</title><title>PloS one</title><description><![CDATA[The novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada. We conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35-3.34; p<0.001), and the risk substantially was elevated from 2.14 (95%CI 1.76-2.60) to 4.81 (95%CI 3.95-5.85) times as the number of comorbidities increased from one to five or more. Significant predictors for mortality included comorbidities such as solid organ transplant (HR = 3.06, 95%CI 2.03-4.63; p<0.001), dementia (HR = 1.46, 95%CI 1.35-1.58; p<0.001), chronic kidney disease (HR = 1.45, 95%CI 1.34-1.57; p<0.001), severe mental illness (HR = 1.42, 95%CI%, 1.12-1.80; p<0.001), cardiovascular disease (CVD) (HR = 1.22, 95%CI, 1.15-1.30), diabetes (HR = 1.19, 95%, 1.12-1.26; p<0.001), chronic obstructive pulmonary disease (COPD) (HR = 1.19, 95%CI 1.12-1.26; p<0.001), cancer (HR = 1.17, 95%CI, 1.09-1.27; p<0.001), hypertension (HR = 1.16, 95%CI, 1.07-1.26; p<0.001). Compared to their effect in older age groups, comorbidities were associated with higher risk of mortality and severity in individuals under 50 years old. Individuals with five or more comorbidities in the below 50 years age group had 395.44 (95%CI, 57.93-2699.44, p<0.001) times higher risk of mortality compared to those without. Limitations include that data were collected during 2020 when the new variants of concern were not predominant, and that the ICES databases do not contain detailed individual-level socioeconomic and racial variables. We found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.]]></description><subject>Age</subject><subject>Arthritis</subject><subject>Asthma</subject><subject>Biology and Life Sciences</subject><subject>Cancer</subject><subject>Cardiovascular diseases</subject><subject>Chronic illnesses</subject><subject>Chronic obstructive pulmonary disease</subject><subject>Cohort analysis</subject><subject>Comorbidity</subject><subject>Complications and side effects</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Dementia disorders</subject><subject>Demographic variables</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Economic models</subject><subject>Health insurance</subject><subject>Health risks</subject><subject>Heart diseases</subject><subject>HIV</subject><subject>Human immunodeficiency virus</subject><subject>Hypertension</subject><subject>Illnesses</subject><subject>Kidney diseases</subject><subject>Kidney transplantation</subject><subject>Kidneys</subject><subject>Lung diseases</subject><subject>Medicine and Health Sciences</subject><subject>Mental disorders</subject><subject>Mortality</subject><subject>Mortality risk</subject><subject>Obstructive lung disease</subject><subject>Patient outcomes</subject><subject>People and places</subject><subject>Population studies</subject><subject>Population-based studies</subject><subject>Prognosis</subject><subject>Public health</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Rheumatoid arthritis</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Social factors</subject><subject>Socio-economic aspects</subject><subject>Socioeconomics</subject><subject>Vaccination</subject><subject>Viral diseases</subject><subject>World population</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk12L1DAUhoso7rr6DwQDgijYMWnSpPFCGMavgYUBP_Y2pPmYydJpapOOO__Gn2pmpspW9kJ6kXLyvO-bHHKy7CmCM4QZenPth76VzazzrZnBoqxQSe5l54jjIqcFxPdv_Z9lj0K4hrDEFaUPszNMKIKQsPPs1zwEr5yMzrfAW9D1Jjc3LkTXroHyW9_XTrvoTAA_XdyAVIiycXEPZKuBdsHIYEAwO9Mfi1ufdIiy1yWEwLXa7ZweZDOqF6ur5fsc8bQDFrKVWr4Fc9D5bmiOJ8jr5KZT7ibFgBAHvX-cPbBJb56M60X2_eOHb4vP-eXq03Ixv8wVpTzmlpS2xghhrFFlmCkKphmDplQaE00I1xIzWkOlispaXrJCWllaCytFaKUQvsienXy7xgcxNjeIomQck9THIhHLE6G9vBZd77ay3wsvnTgWfL8Wso9ONUbUuFaoYsxYRkhRoRqrGuKqLq1hlaxx8no3pg311mhl2tjLZmI63WndRqz9TlSEI07KZPByNOj9j8GEKLYuKNM0sjV-OJ2bFpQXNKHP_0Hvvt1IrWW6gGutT7nqYCrmlDHOOcGH2NkdVPq02TqVXqJ1qT4RvJoIEhPNTVzLIQSx_Prl_9nV1ZR9cYvdGNnETfDNcHhFYQqSE6h6H0Jv7N8mIygOg_SnG-IwSGIcJPwb9N0QKg</recordid><startdate>20211005</startdate><enddate>20211005</enddate><creator>Ge, Erjia</creator><creator>Li, Yanhong</creator><creator>Wu, Shishi</creator><creator>Candido, Elisa</creator><creator>Wei, Xiaolin</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-3076-2650</orcidid></search><sort><creationdate>20211005</creationdate><title>Association of pre-existing comorbidities with mortality and disease severity among 167,500 individuals with COVID-19 in Canada: A population-based cohort study</title><author>Ge, Erjia ; Li, Yanhong ; Wu, Shishi ; Candido, Elisa ; Wei, Xiaolin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c669t-f45fb31133d18e7e227d770e5cd34d449da376b0cc28ff9572afa5ff08c468c13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Age</topic><topic>Arthritis</topic><topic>Asthma</topic><topic>Biology and Life Sciences</topic><topic>Cancer</topic><topic>Cardiovascular diseases</topic><topic>Chronic illnesses</topic><topic>Chronic obstructive pulmonary disease</topic><topic>Cohort analysis</topic><topic>Comorbidity</topic><topic>Complications and side effects</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Dementia disorders</topic><topic>Demographic variables</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Economic models</topic><topic>Health insurance</topic><topic>Health risks</topic><topic>Heart diseases</topic><topic>HIV</topic><topic>Human immunodeficiency virus</topic><topic>Hypertension</topic><topic>Illnesses</topic><topic>Kidney diseases</topic><topic>Kidney transplantation</topic><topic>Kidneys</topic><topic>Lung diseases</topic><topic>Medicine and Health Sciences</topic><topic>Mental disorders</topic><topic>Mortality</topic><topic>Mortality risk</topic><topic>Obstructive lung disease</topic><topic>Patient outcomes</topic><topic>People and places</topic><topic>Population studies</topic><topic>Population-based studies</topic><topic>Prognosis</topic><topic>Public health</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Rheumatoid arthritis</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Social factors</topic><topic>Socio-economic aspects</topic><topic>Socioeconomics</topic><topic>Vaccination</topic><topic>Viral diseases</topic><topic>World population</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ge, Erjia</creatorcontrib><creatorcontrib>Li, Yanhong</creatorcontrib><creatorcontrib>Wu, Shishi</creatorcontrib><creatorcontrib>Candido, Elisa</creatorcontrib><creatorcontrib>Wei, Xiaolin</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database (ProQuest)</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database (Proquest)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>Biological Sciences</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials science collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ge, Erjia</au><au>Li, Yanhong</au><au>Wu, Shishi</au><au>Candido, Elisa</au><au>Wei, Xiaolin</au><au>Augusto, Orvalho</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Association of pre-existing comorbidities with mortality and disease severity among 167,500 individuals with COVID-19 in Canada: A population-based cohort study</atitle><jtitle>PloS one</jtitle><date>2021-10-05</date><risdate>2021</risdate><volume>16</volume><issue>10</issue><spage>e0258154</spage><epage>e0258154</epage><pages>e0258154-e0258154</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract><![CDATA[The novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada. We conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35-3.34; p<0.001), and the risk substantially was elevated from 2.14 (95%CI 1.76-2.60) to 4.81 (95%CI 3.95-5.85) times as the number of comorbidities increased from one to five or more. Significant predictors for mortality included comorbidities such as solid organ transplant (HR = 3.06, 95%CI 2.03-4.63; p<0.001), dementia (HR = 1.46, 95%CI 1.35-1.58; p<0.001), chronic kidney disease (HR = 1.45, 95%CI 1.34-1.57; p<0.001), severe mental illness (HR = 1.42, 95%CI%, 1.12-1.80; p<0.001), cardiovascular disease (CVD) (HR = 1.22, 95%CI, 1.15-1.30), diabetes (HR = 1.19, 95%, 1.12-1.26; p<0.001), chronic obstructive pulmonary disease (COPD) (HR = 1.19, 95%CI 1.12-1.26; p<0.001), cancer (HR = 1.17, 95%CI, 1.09-1.27; p<0.001), hypertension (HR = 1.16, 95%CI, 1.07-1.26; p<0.001). Compared to their effect in older age groups, comorbidities were associated with higher risk of mortality and severity in individuals under 50 years old. Individuals with five or more comorbidities in the below 50 years age group had 395.44 (95%CI, 57.93-2699.44, p<0.001) times higher risk of mortality compared to those without. Limitations include that data were collected during 2020 when the new variants of concern were not predominant, and that the ICES databases do not contain detailed individual-level socioeconomic and racial variables. We found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.]]></abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>34610047</pmid><doi>10.1371/journal.pone.0258154</doi><tpages>e0258154</tpages><orcidid>https://orcid.org/0000-0002-3076-2650</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2021-10, Vol.16 (10), p.e0258154-e0258154 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_2579349322 |
source | Public Library of Science (PLoS) Journals Open Access; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Age Arthritis Asthma Biology and Life Sciences Cancer Cardiovascular diseases Chronic illnesses Chronic obstructive pulmonary disease Cohort analysis Comorbidity Complications and side effects Coronaviruses COVID-19 Dementia disorders Demographic variables Diabetes Diabetes mellitus Economic models Health insurance Health risks Heart diseases HIV Human immunodeficiency virus Hypertension Illnesses Kidney diseases Kidney transplantation Kidneys Lung diseases Medicine and Health Sciences Mental disorders Mortality Mortality risk Obstructive lung disease Patient outcomes People and places Population studies Population-based studies Prognosis Public health Regression analysis Regression models Rheumatoid arthritis Risk analysis Risk factors Social factors Socio-economic aspects Socioeconomics Vaccination Viral diseases World population |
title | Association of pre-existing comorbidities with mortality and disease severity among 167,500 individuals with COVID-19 in Canada: A population-based cohort study |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T07%3A03%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Association%20of%20pre-existing%20comorbidities%20with%20mortality%20and%20disease%20severity%20among%20167,500%20individuals%20with%20COVID-19%20in%20Canada:%20A%20population-based%20cohort%20study&rft.jtitle=PloS%20one&rft.au=Ge,%20Erjia&rft.date=2021-10-05&rft.volume=16&rft.issue=10&rft.spage=e0258154&rft.epage=e0258154&rft.pages=e0258154-e0258154&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0258154&rft_dat=%3Cgale_plos_%3EA677999435%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2579349322&rft_id=info:pmid/34610047&rft_galeid=A677999435&rft_doaj_id=oai_doaj_org_article_b3bc1877ef744281b3cb038b5fe78ab3&rfr_iscdi=true |