Impact on disease mortality of clinical, biological, and virological characteristics at hospital admission and overtime in COVID‐19 patients
Little is known on the association between clinical factors and coronavirus disease 2019 (COVID‐19) more than 15 days after diagnosis. We conducted a multicentric prospective cohort of COVID‐19 hospitalized patients to describe clinical, biological, and virological characteristics at hospital admiss...
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| description | Little is known on the association between clinical factors and coronavirus disease 2019 (COVID‐19) more than 15 days after diagnosis. We conducted a multicentric prospective cohort of COVID‐19 hospitalized patients to describe clinical, biological, and virological characteristics at hospital admission and over time, according to mortality up to Day 60 after admission. For the analysis of risk factors of survival, analyses assessing associations between mortality and demographic characteristics or comorbidities were performed using a Cox regression model. Between January 24 and March 15, 2020, 246 patients with reverse‐transcriptase polymerase chain reactions virologically confirmed COVID‐19 were enrolled. In multivariate analysis, mortality at Day 60 (n = 42 patients, 17.1% [95% confidence interval, 12.6–22.4]) was associated with older age (adjusted hazard ratio [aHR] for age ≥ 65 years: 5.22 [2.56–10.63, p |
| doi_str_mv | 10.1002/jmv.26601 |
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Highlights
Older age, male gender, chronic pulmonary disease (not asthma), obesity, and diabetes were associated with mortality in COVID‐19 hospitalized patients.
Viral load at admission decreased with the time since symptom onset, with an association with mortality adjusted on clinical risk factors.</description><identifier>ISSN: 0146-6615</identifier><identifier>EISSN: 1096-9071</identifier><identifier>DOI: 10.1002/jmv.26601</identifier><identifier>PMID: 33058220</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Adolescent ; Adult ; Age ; Age Factors ; Aged ; Aged, 80 and over ; Asthma ; Cohort Studies ; Confidence intervals ; coronavirus disease 2019 ; Coronaviruses ; COVID-19 ; COVID-19 - diagnosis ; COVID-19 - mortality ; COVID-19 - virology ; Diabetes ; Diabetes mellitus ; emerging infection diseases ; Female ; France - epidemiology ; Gender ; Hospitalization - statistics & numerical data ; Human health and pathology ; Humans ; Life Sciences ; Lung diseases ; Male ; Middle Aged ; Mortality ; Multivariate analysis ; Obesity ; Patient Admission - statistics & numerical data ; Patients ; Polymerase chain reaction ; prospective cohort ; Prospective Studies ; Regression analysis ; Regression models ; Risk analysis ; Risk Factors ; Risk management ; SARS-CoV-2 - isolation & purification ; SARS‐CoV‐2 ; Signs and symptoms ; Statistical analysis ; Viral diseases ; Viral Load ; Virology ; Young Adult</subject><ispartof>Journal of medical virology, 2021-04, Vol.93 (4), p.2149-2159</ispartof><rights>2020 Wiley Periodicals LLC</rights><rights>2020 Wiley Periodicals LLC.</rights><rights>2021 Wiley Periodicals LLC</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4771-aa180909807757ab2b12ec2faaf74e1d1000c0757479f6e8651c1f67756cd1ef3</citedby><cites>FETCH-LOGICAL-c4771-aa180909807757ab2b12ec2faaf74e1d1000c0757479f6e8651c1f67756cd1ef3</cites><orcidid>0000-0001-9445-1117 ; 0000-0002-2177-4318 ; 0000-0002-8715-8323 ; 0000-0001-5942-2345 ; 0000-0002-8194-6126 ; 0000-0002-9998-8578 ; 0000-0002-6150-2376 ; 0000-0003-0699-8353 ; 0000-0001-6517-2901 ; 0000-0001-6861-236X ; 0000-0002-0892-2187 ; 0000-0001-7980-5650 ; 0000-0001-9393-7684 ; 0000-0003-0290-4532 ; 0000-0001-6468-2002 ; 0000-0003-2773-7750 ; 0000-0002-2603-8467 ; 0000-0002-8959-2123 ; 0000-0003-1878-9858 ; 0000-0002-3426-2936 ; 0000-0002-7559-9527 ; 0009-0002-7269-2328</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjmv.26601$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjmv.26601$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,776,780,881,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33058220$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://u-picardie.hal.science/hal-04121463$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Yazdanpanah, Yazdan</creatorcontrib><creatorcontrib>French COVID cohort investigators and study group</creatorcontrib><title>Impact on disease mortality of clinical, biological, and virological characteristics at hospital admission and overtime in COVID‐19 patients</title><title>Journal of medical virology</title><addtitle>J Med Virol</addtitle><description>Little is known on the association between clinical factors and coronavirus disease 2019 (COVID‐19) more than 15 days after diagnosis. We conducted a multicentric prospective cohort of COVID‐19 hospitalized patients to describe clinical, biological, and virological characteristics at hospital admission and over time, according to mortality up to Day 60 after admission. For the analysis of risk factors of survival, analyses assessing associations between mortality and demographic characteristics or comorbidities were performed using a Cox regression model. Between January 24 and March 15, 2020, 246 patients with reverse‐transcriptase polymerase chain reactions virologically confirmed COVID‐19 were enrolled. In multivariate analysis, mortality at Day 60 (n = 42 patients, 17.1% [95% confidence interval, 12.6–22.4]) was associated with older age (adjusted hazard ratio [aHR] for age ≥ 65 years: 5.22 [2.56–10.63, p < .001]), gender (aHR for male: 2.97 [1.47–5.99, p = .002]), chronic pulmonary disease (aHR: 4.84 [2.32–10.07, p < .001]), obesity (aHR: 3.32 [1.70–6.52, p < .001]), and diabetes (aHR: 1.98 [1.01–3.89, p = .048]). The median nasopharyngeal viral load at admission was 6.4 log10 copies/ml and was associated with mortality regardless of clinical risk factors. Viral load decreased with time elapsed since symptoms onset. Our study confirmed that mortality was associated with clinical characteristics at admission. The viral load at admission was significantly lower in patients admitted late after the onset of symptoms in both dead and alive patients. Our results could improve earlier identification of patients with increased risk of mortality and adapted management.
Highlights
Older age, male gender, chronic pulmonary disease (not asthma), obesity, and diabetes were associated with mortality in COVID‐19 hospitalized patients.
Viral load at admission decreased with the time since symptom onset, with an association with mortality adjusted on clinical risk factors.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Age</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Asthma</subject><subject>Cohort Studies</subject><subject>Confidence intervals</subject><subject>coronavirus disease 2019</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 - diagnosis</subject><subject>COVID-19 - mortality</subject><subject>COVID-19 - virology</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>emerging infection diseases</subject><subject>Female</subject><subject>France - epidemiology</subject><subject>Gender</subject><subject>Hospitalization - statistics & numerical data</subject><subject>Human health and pathology</subject><subject>Humans</subject><subject>Life Sciences</subject><subject>Lung diseases</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Multivariate analysis</subject><subject>Obesity</subject><subject>Patient Admission - statistics & numerical data</subject><subject>Patients</subject><subject>Polymerase chain reaction</subject><subject>prospective cohort</subject><subject>Prospective Studies</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Risk analysis</subject><subject>Risk Factors</subject><subject>Risk management</subject><subject>SARS-CoV-2 - isolation & purification</subject><subject>SARS‐CoV‐2</subject><subject>Signs and symptoms</subject><subject>Statistical analysis</subject><subject>Viral diseases</subject><subject>Viral Load</subject><subject>Virology</subject><subject>Young Adult</subject><issn>0146-6615</issn><issn>1096-9071</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1ks9u1DAQxi0EokvhwAsgS1xAIu2Mk9jxBala_nTRol6gV8vrOF2vknixs0F74wkQz8iT4CVtgUqcbM385hv700fIU4QTBGCnm248YZwD3iMzBMkzCQLvkxlgwTPOsTwij2LcAEAlGXtIjvIcyooxmJHvi26rzUB9T2sXrY6Wdj4MunXDnvqGmtb1zuj2FV053_qr6a77mo4u3BSoWeuQVGxwcXAmUj3QtY9bl3SorjsXo0sLDlN-tGFwnaWup_OLy8Wbn99-oKRbPTjbD_ExedDoNton1-cx-fzu7af5eba8eL-Yny0zUwiBmdZYgQRZgRCl0Cu2QmYNa7RuRGGxTq6AgdQqhGy4rXiJBhueYG5qtE1-TF5PutvdqrO1SbuDbtU2uE6HvfLaqX87vVurKz8qwUXJBEsCLyeB9Z2x87OlOtSgQJbsz0dM7IvrZcF_2dk4qOSIsW2re-t3UbGixKrMJS8S-vwOuvG70CcrEiUBmShk8We5CT7GYJvbFyCoQyJUSoT6nYjEPvv7p7fkTQQScDoBX11r9_9XUh8-Xk6SvwABfMHF</recordid><startdate>202104</startdate><enddate>202104</enddate><creator>Yazdanpanah, Yazdan</creator><general>Wiley Subscription Services, Inc</general><general>Wiley-Blackwell</general><general>John Wiley and Sons Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7TK</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>K9.</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>1XC</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-9445-1117</orcidid><orcidid>https://orcid.org/0000-0002-2177-4318</orcidid><orcidid>https://orcid.org/0000-0002-8715-8323</orcidid><orcidid>https://orcid.org/0000-0001-5942-2345</orcidid><orcidid>https://orcid.org/0000-0002-8194-6126</orcidid><orcidid>https://orcid.org/0000-0002-9998-8578</orcidid><orcidid>https://orcid.org/0000-0002-6150-2376</orcidid><orcidid>https://orcid.org/0000-0003-0699-8353</orcidid><orcidid>https://orcid.org/0000-0001-6517-2901</orcidid><orcidid>https://orcid.org/0000-0001-6861-236X</orcidid><orcidid>https://orcid.org/0000-0002-0892-2187</orcidid><orcidid>https://orcid.org/0000-0001-7980-5650</orcidid><orcidid>https://orcid.org/0000-0001-9393-7684</orcidid><orcidid>https://orcid.org/0000-0003-0290-4532</orcidid><orcidid>https://orcid.org/0000-0001-6468-2002</orcidid><orcidid>https://orcid.org/0000-0003-2773-7750</orcidid><orcidid>https://orcid.org/0000-0002-2603-8467</orcidid><orcidid>https://orcid.org/0000-0002-8959-2123</orcidid><orcidid>https://orcid.org/0000-0003-1878-9858</orcidid><orcidid>https://orcid.org/0000-0002-3426-2936</orcidid><orcidid>https://orcid.org/0000-0002-7559-9527</orcidid><orcidid>https://orcid.org/0009-0002-7269-2328</orcidid></search><sort><creationdate>202104</creationdate><title>Impact on disease mortality of clinical, biological, and virological characteristics at hospital admission and overtime in COVID‐19 patients</title><author>Yazdanpanah, Yazdan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4771-aa180909807757ab2b12ec2faaf74e1d1000c0757479f6e8651c1f67756cd1ef3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Age</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Asthma</topic><topic>Cohort Studies</topic><topic>Confidence intervals</topic><topic>coronavirus disease 2019</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>COVID-19 - diagnosis</topic><topic>COVID-19 - mortality</topic><topic>COVID-19 - virology</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>emerging infection diseases</topic><topic>Female</topic><topic>France - epidemiology</topic><topic>Gender</topic><topic>Hospitalization - statistics & numerical data</topic><topic>Human health and pathology</topic><topic>Humans</topic><topic>Life Sciences</topic><topic>Lung diseases</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Multivariate analysis</topic><topic>Obesity</topic><topic>Patient Admission - statistics & numerical data</topic><topic>Patients</topic><topic>Polymerase chain reaction</topic><topic>prospective cohort</topic><topic>Prospective Studies</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Risk analysis</topic><topic>Risk Factors</topic><topic>Risk management</topic><topic>SARS-CoV-2 - isolation & purification</topic><topic>SARS‐CoV‐2</topic><topic>Signs and symptoms</topic><topic>Statistical analysis</topic><topic>Viral diseases</topic><topic>Viral Load</topic><topic>Virology</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yazdanpanah, Yazdan</creatorcontrib><creatorcontrib>French COVID cohort investigators and study group</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of medical virology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yazdanpanah, Yazdan</au><aucorp>French COVID cohort investigators and study group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Impact on disease mortality of clinical, biological, and virological characteristics at hospital admission and overtime in COVID‐19 patients</atitle><jtitle>Journal of medical virology</jtitle><addtitle>J Med Virol</addtitle><date>2021-04</date><risdate>2021</risdate><volume>93</volume><issue>4</issue><spage>2149</spage><epage>2159</epage><pages>2149-2159</pages><issn>0146-6615</issn><eissn>1096-9071</eissn><abstract>Little is known on the association between clinical factors and coronavirus disease 2019 (COVID‐19) more than 15 days after diagnosis. We conducted a multicentric prospective cohort of COVID‐19 hospitalized patients to describe clinical, biological, and virological characteristics at hospital admission and over time, according to mortality up to Day 60 after admission. For the analysis of risk factors of survival, analyses assessing associations between mortality and demographic characteristics or comorbidities were performed using a Cox regression model. Between January 24 and March 15, 2020, 246 patients with reverse‐transcriptase polymerase chain reactions virologically confirmed COVID‐19 were enrolled. In multivariate analysis, mortality at Day 60 (n = 42 patients, 17.1% [95% confidence interval, 12.6–22.4]) was associated with older age (adjusted hazard ratio [aHR] for age ≥ 65 years: 5.22 [2.56–10.63, p < .001]), gender (aHR for male: 2.97 [1.47–5.99, p = .002]), chronic pulmonary disease (aHR: 4.84 [2.32–10.07, p < .001]), obesity (aHR: 3.32 [1.70–6.52, p < .001]), and diabetes (aHR: 1.98 [1.01–3.89, p = .048]). The median nasopharyngeal viral load at admission was 6.4 log10 copies/ml and was associated with mortality regardless of clinical risk factors. Viral load decreased with time elapsed since symptoms onset. Our study confirmed that mortality was associated with clinical characteristics at admission. The viral load at admission was significantly lower in patients admitted late after the onset of symptoms in both dead and alive patients. Our results could improve earlier identification of patients with increased risk of mortality and adapted management.
Highlights
Older age, male gender, chronic pulmonary disease (not asthma), obesity, and diabetes were associated with mortality in COVID‐19 hospitalized patients.
Viral load at admission decreased with the time since symptom onset, with an association with mortality adjusted on clinical risk factors.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>33058220</pmid><doi>10.1002/jmv.26601</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-9445-1117</orcidid><orcidid>https://orcid.org/0000-0002-2177-4318</orcidid><orcidid>https://orcid.org/0000-0002-8715-8323</orcidid><orcidid>https://orcid.org/0000-0001-5942-2345</orcidid><orcidid>https://orcid.org/0000-0002-8194-6126</orcidid><orcidid>https://orcid.org/0000-0002-9998-8578</orcidid><orcidid>https://orcid.org/0000-0002-6150-2376</orcidid><orcidid>https://orcid.org/0000-0003-0699-8353</orcidid><orcidid>https://orcid.org/0000-0001-6517-2901</orcidid><orcidid>https://orcid.org/0000-0001-6861-236X</orcidid><orcidid>https://orcid.org/0000-0002-0892-2187</orcidid><orcidid>https://orcid.org/0000-0001-7980-5650</orcidid><orcidid>https://orcid.org/0000-0001-9393-7684</orcidid><orcidid>https://orcid.org/0000-0003-0290-4532</orcidid><orcidid>https://orcid.org/0000-0001-6468-2002</orcidid><orcidid>https://orcid.org/0000-0003-2773-7750</orcidid><orcidid>https://orcid.org/0000-0002-2603-8467</orcidid><orcidid>https://orcid.org/0000-0002-8959-2123</orcidid><orcidid>https://orcid.org/0000-0003-1878-9858</orcidid><orcidid>https://orcid.org/0000-0002-3426-2936</orcidid><orcidid>https://orcid.org/0000-0002-7559-9527</orcidid><orcidid>https://orcid.org/0009-0002-7269-2328</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adolescent Adult Age Age Factors Aged Aged, 80 and over Asthma Cohort Studies Confidence intervals coronavirus disease 2019 Coronaviruses COVID-19 COVID-19 - diagnosis COVID-19 - mortality COVID-19 - virology Diabetes Diabetes mellitus emerging infection diseases Female France - epidemiology Gender Hospitalization - statistics & numerical data Human health and pathology Humans Life Sciences Lung diseases Male Middle Aged Mortality Multivariate analysis Obesity Patient Admission - statistics & numerical data Patients Polymerase chain reaction prospective cohort Prospective Studies Regression analysis Regression models Risk analysis Risk Factors Risk management SARS-CoV-2 - isolation & purification SARS‐CoV‐2 Signs and symptoms Statistical analysis Viral diseases Viral Load Virology Young Adult |
| title | Impact on disease mortality of clinical, biological, and virological characteristics at hospital admission and overtime in COVID‐19 patients |
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