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...
- 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 |
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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 https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/13804/1/Predictive-Model-and-Risk-Factors-for-Case-Fatality-of-COVID-1_2020_The-Inno.pdf 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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repository.name.fl_str_mv |
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repository.mail.fl_str_mv |
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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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