Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China

An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19), however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until M...

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Autores:
Tipo de recurso:
Article of investigation
Fecha de publicación:
2020
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
eng
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/13804
Acceso en línea:
https://doi.org/10.1016/j.xinn.2020.100022
http://hdl.handle.net/20.500.12010/13804
Palabra clave:
COVID-19
Fatality
Risk factor
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
Rights
License
Abierto (Texto Completo)
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oai_identifier_str oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/13804
network_acronym_str UTADEO2
network_name_str Expeditio: repositorio UTadeo
repository_id_str
dc.title.spa.fl_str_mv Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China
title Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China
spellingShingle Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China
COVID-19
Fatality
Risk factor
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
title_short Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China
title_full Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China
title_fullStr Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China
title_full_unstemmed Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China
title_sort Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China
dc.subject.spa.fl_str_mv COVID-19
Fatality
Risk factor
topic COVID-19
Fatality
Risk factor
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
dc.subject.lemb.spa.fl_str_mv Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
description An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19), however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020. We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death probability under specific combinations of key predictors. Among the 21,392 patients, 1,020 (4.77%) died of COVID-19. Multivariable analyses showed that factors, including age (R60 versus <45 years, hazard ratio [HR] = 7.32; 95% confidence interval [CI], 5.42, 9.89), sex (male versus female, HR = 1.31; 95% CI, 1.15, 1.50), severity of the disease (critical versus mild, HR = 39.98; 95% CI, 29.52, 48.86), comorbidity (HR = 1.40; 95% CI, 1.23, 1.60), highest body temperature (>39 C versus <39 C, HR = 1.28; 95% CI, 1.09, 1.49), white blood cell counts (>10 3 109 /L versus (4–10) 3 109 /L, HR = 1.69; 95% CI, 1.35, 2.13), and lymphocyte counts (<0.8 3 109 /L versus (0.8–4) 3 109 /L, HR = 1.26; 95% CI, 1.06, 1.50) were significantly associated with case fatality of COVID-19 patients. Individuals of an older age, who were male, with comorbidities, and had a critical illness had the highest death probability, with 21%, 36%, 46%, and 54% within 1–4 weeks after the symptom onset. Risk factors, including demographic characteristics, clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19. Our predictive model can provide scientific evidence for a more rational, evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-09-25T16:40:27Z
dc.date.available.none.fl_str_mv 2020-09-25T16:40:27Z
dc.date.created.none.fl_str_mv 2020
dc.type.local.spa.fl_str_mv Artículo
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
format http://purl.org/coar/resource_type/c_2df8fbb1
dc.identifier.issn.spa.fl_str_mv 2666-6758
dc.identifier.other.spa.fl_str_mv https://doi.org/10.1016/j.xinn.2020.100022
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12010/13804
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.1016/j.xinn.2020.100022
identifier_str_mv 2666-6758
url https://doi.org/10.1016/j.xinn.2020.100022
http://hdl.handle.net/20.500.12010/13804
dc.language.iso.spa.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.extent.spa.fl_str_mv 9 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv The innovation
dc.source.spa.fl_str_mv reponame:Expeditio Repositorio Institucional UJTL
instname:Universidad de Bogotá Jorge Tadeo Lozano
instname_str Universidad de Bogotá Jorge Tadeo Lozano
institution Universidad de Bogotá Jorge Tadeo Lozano
reponame_str Expeditio Repositorio Institucional UJTL
collection Expeditio Repositorio Institucional UJTL
bitstream.url.fl_str_mv https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/13804/2/license.txt
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https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/13804/3/Predictive-Model-and-Risk-Factors-for-Case-Fatality-of-COVID-1_2020_The-Inno.pdf.jpg
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spelling 2020-09-25T16:40:27Z2020-09-25T16:40:27Z20202666-6758https://doi.org/10.1016/j.xinn.2020.100022http://hdl.handle.net/20.500.12010/13804https://doi.org/10.1016/j.xinn.2020.100022An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19), however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020. We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death probability under specific combinations of key predictors. Among the 21,392 patients, 1,020 (4.77%) died of COVID-19. Multivariable analyses showed that factors, including age (R60 versus <45 years, hazard ratio [HR] = 7.32; 95% confidence interval [CI], 5.42, 9.89), sex (male versus female, HR = 1.31; 95% CI, 1.15, 1.50), severity of the disease (critical versus mild, HR = 39.98; 95% CI, 29.52, 48.86), comorbidity (HR = 1.40; 95% CI, 1.23, 1.60), highest body temperature (>39 C versus <39 C, HR = 1.28; 95% CI, 1.09, 1.49), white blood cell counts (>10 3 109 /L versus (4–10) 3 109 /L, HR = 1.69; 95% CI, 1.35, 2.13), and lymphocyte counts (<0.8 3 109 /L versus (0.8–4) 3 109 /L, HR = 1.26; 95% CI, 1.06, 1.50) were significantly associated with case fatality of COVID-19 patients. Individuals of an older age, who were male, with comorbidities, and had a critical illness had the highest death probability, with 21%, 36%, 46%, and 54% within 1–4 weeks after the symptom onset. Risk factors, including demographic characteristics, clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19. Our predictive model can provide scientific evidence for a more rational, evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19.9 páginasapplication/pdfengThe innovationreponame:Expeditio Repositorio Institucional UJTLinstname:Universidad de Bogotá Jorge Tadeo LozanoCOVID-19FatalityRisk factorSíndrome respiratorio agudo graveCOVID-19SARS-CoV-2CoronavirusPredictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, ChinaArtículohttp://purl.org/coar/resource_type/c_2df8fbb1Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Wu, RanAi, SiqiCai, JingZhang, ShiyuQian, ZhengminZhang, YunquanWu, YinglinChen, LanTian, FeiLi, HuanLi, MingyanLin, HualiangLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/13804/2/license.txtabceeb1c943c50d3343516f9dbfc110fMD52open accessORIGINALPredictive-Model-and-Risk-Factors-for-Case-Fatality-of-COVID-1_2020_The-Inno.pdfPredictive-Model-and-Risk-Factors-for-Case-Fatality-of-COVID-1_2020_The-Inno.pdfVer artículoapplication/pdf1222559https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/13804/1/Predictive-Model-and-Risk-Factors-for-Case-Fatality-of-COVID-1_2020_The-Inno.pdfc088711b4a52854c530c334dba4d0f9fMD51open accessTHUMBNAILPredictive-Model-and-Risk-Factors-for-Case-Fatality-of-COVID-1_2020_The-Inno.pdf.jpgPredictive-Model-and-Risk-Factors-for-Case-Fatality-of-COVID-1_2020_The-Inno.pdf.jpgIM Thumbnailimage/jpeg19872https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/13804/3/Predictive-Model-and-Risk-Factors-for-Case-Fatality-of-COVID-1_2020_The-Inno.pdf.jpg201ddb880175b8e4c035d6f35631eb40MD53open access20.500.12010/13804oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/138042020-09-25 11:40:27.81open accessRepositorio Institucional - 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