A novel severity score to predict inpatient mortality in COVID‑19 patients

COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifcally for...

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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:20.500.12010/14380
Acceso en línea:
https://doi.org/10.1038/s41598-020-73962-9
http://hdl.handle.net/20.500.12010/14380
Palabra clave:
COVID‑19
Predict inpatient mortality
Patients
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:20.500.12010/14380
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network_name_str Expeditio: repositorio UTadeo
repository_id_str
dc.title.spa.fl_str_mv A novel severity score to predict inpatient mortality in COVID‑19 patients
title A novel severity score to predict inpatient mortality in COVID‑19 patients
spellingShingle A novel severity score to predict inpatient mortality in COVID‑19 patients
COVID‑19
Predict inpatient mortality
Patients
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
title_short A novel severity score to predict inpatient mortality in COVID‑19 patients
title_full A novel severity score to predict inpatient mortality in COVID‑19 patients
title_fullStr A novel severity score to predict inpatient mortality in COVID‑19 patients
title_full_unstemmed A novel severity score to predict inpatient mortality in COVID‑19 patients
title_sort A novel severity score to predict inpatient mortality in COVID‑19 patients
dc.subject.spa.fl_str_mv COVID‑19
Predict inpatient mortality
Patients
topic COVID‑19
Predict inpatient mortality
Patients
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 COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifcally for COVID-19 to help predict disease severity and mortality. 4711 patients with confrmed SARS-CoV-2 infection were included. We derived a risk model using the frst half of the cohort (n= 2355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2356 patients. Mortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814–0.851) and an AUC of 0.798 (95% CI 0.789–0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0–3), moderate (4–6) and high (7–10) COVID-19 severity score. This developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-10-13T15:57:51Z
dc.date.available.none.fl_str_mv 2020-10-13T15:57:51Z
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 2045-2322
dc.identifier.other.spa.fl_str_mv https://doi.org/10.1038/s41598-020-73962-9
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12010/14380
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.1038/s41598-020-73962-9
identifier_str_mv 2045-2322
url https://doi.org/10.1038/s41598-020-73962-9
http://hdl.handle.net/20.500.12010/14380
dc.language.iso.spa.fl_str_mv eng
language eng
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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 8 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Scientific reports
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/20.500.12010/14380/2/license.txt
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spelling 2020-10-13T15:57:51Z2020-10-13T15:57:51Z20202045-2322https://doi.org/10.1038/s41598-020-73962-9http://hdl.handle.net/20.500.12010/14380https://doi.org/10.1038/s41598-020-73962-9COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifcally for COVID-19 to help predict disease severity and mortality. 4711 patients with confrmed SARS-CoV-2 infection were included. We derived a risk model using the frst half of the cohort (n= 2355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2356 patients. Mortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814–0.851) and an AUC of 0.798 (95% CI 0.789–0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0–3), moderate (4–6) and high (7–10) COVID-19 severity score. This developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.8 páginasapplication/pdfengScientific reportsreponame:Expeditio Repositorio Institucional UJTLinstname:Universidad de Bogotá Jorge Tadeo LozanoCOVID‑19Predict inpatient mortalityPatientsSíndrome respiratorio agudo graveCOVID-19SARS-CoV-2CoronavirusA novel severity score to predict inpatient mortality in COVID‑19 patientsArtículohttp://purl.org/coar/resource_type/c_2df8fbb1Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Altschul, David J.Unda, Santiago R.Benton, JoshuaGarza Ramos, Rafael de laCezayirli, PhillipMehler, MarkEskandar, Emad N.LICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/14380/2/license.txtabceeb1c943c50d3343516f9dbfc110fMD52open accessTHUMBNAILs41598-020-73962-9.pdf.jpgs41598-020-73962-9.pdf.jpgIM Thumbnailimage/jpeg15174https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/14380/3/s41598-020-73962-9.pdf.jpgf96c5393af4681f451546975e1009bf7MD53open access20.500.12010/14380oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/143802021-03-17 17:17:36.787metadata only accessRepositorio Institucional - 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