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A risk scoring system to predict progression to severe pneumonia in patients with Covid-19

Rapid outbreak of coronavirus disease 2019 (Covid-19) raised major concern regarding medical resource constraints. We constructed and validated a scoring system for early prediction of progression to severe pneumonia in patients with Covid-19. A total of 561 patients from a Covid-19 designated hospi...

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Autores principales: Lee, Ji Yeon, Nam, Byung-Ho, Kim, Mhinjine, Hwang, Jongmin, Kim, Jin Young, Hyun, Miri, Kim, Hyun Ah, Cho, Chi-Heum
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8966605/
https://www.ncbi.nlm.nih.gov/pubmed/35354828
http://dx.doi.org/10.1038/s41598-022-07610-9
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author Lee, Ji Yeon
Nam, Byung-Ho
Kim, Mhinjine
Hwang, Jongmin
Kim, Jin Young
Hyun, Miri
Kim, Hyun Ah
Cho, Chi-Heum
author_facet Lee, Ji Yeon
Nam, Byung-Ho
Kim, Mhinjine
Hwang, Jongmin
Kim, Jin Young
Hyun, Miri
Kim, Hyun Ah
Cho, Chi-Heum
author_sort Lee, Ji Yeon
collection PubMed
description Rapid outbreak of coronavirus disease 2019 (Covid-19) raised major concern regarding medical resource constraints. We constructed and validated a scoring system for early prediction of progression to severe pneumonia in patients with Covid-19. A total of 561 patients from a Covid-19 designated hospital in Daegu, South Korea were randomly divided into two cohorts: development cohort (N = 421) and validation cohort (N = 140). We used multivariate logistic regression to identify four independent risk predictors for progression to severe pneumonia and constructed a risk scoring system by giving each factor a number of scores corresponding to its regression coefficient. We calculated risk scores for each patient and defined two groups: low risk (0 to 8 points) and high risk (9 to 20 points). In the development cohort, the sensitivity and specificity were 83.8% and 78.9%. In the validation cohort, the sensitivity and specificity were 70.8% and 79.3%, respectively. The C-statistics was 0.884 (95% CI 0.833–0.934) in the development cohort and 0.828 (95% CI 0.733–0.923) in the validation cohort. This risk scoring system is useful to identify high-risk group for progression to severe pneumonia in Covid-19 patients and can prevent unnecessary overuse of medical care in limited-resource settings.
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spelling pubmed-89666052022-03-31 A risk scoring system to predict progression to severe pneumonia in patients with Covid-19 Lee, Ji Yeon Nam, Byung-Ho Kim, Mhinjine Hwang, Jongmin Kim, Jin Young Hyun, Miri Kim, Hyun Ah Cho, Chi-Heum Sci Rep Article Rapid outbreak of coronavirus disease 2019 (Covid-19) raised major concern regarding medical resource constraints. We constructed and validated a scoring system for early prediction of progression to severe pneumonia in patients with Covid-19. A total of 561 patients from a Covid-19 designated hospital in Daegu, South Korea were randomly divided into two cohorts: development cohort (N = 421) and validation cohort (N = 140). We used multivariate logistic regression to identify four independent risk predictors for progression to severe pneumonia and constructed a risk scoring system by giving each factor a number of scores corresponding to its regression coefficient. We calculated risk scores for each patient and defined two groups: low risk (0 to 8 points) and high risk (9 to 20 points). In the development cohort, the sensitivity and specificity were 83.8% and 78.9%. In the validation cohort, the sensitivity and specificity were 70.8% and 79.3%, respectively. The C-statistics was 0.884 (95% CI 0.833–0.934) in the development cohort and 0.828 (95% CI 0.733–0.923) in the validation cohort. This risk scoring system is useful to identify high-risk group for progression to severe pneumonia in Covid-19 patients and can prevent unnecessary overuse of medical care in limited-resource settings. Nature Publishing Group UK 2022-03-30 /pmc/articles/PMC8966605/ /pubmed/35354828 http://dx.doi.org/10.1038/s41598-022-07610-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Lee, Ji Yeon
Nam, Byung-Ho
Kim, Mhinjine
Hwang, Jongmin
Kim, Jin Young
Hyun, Miri
Kim, Hyun Ah
Cho, Chi-Heum
A risk scoring system to predict progression to severe pneumonia in patients with Covid-19
title A risk scoring system to predict progression to severe pneumonia in patients with Covid-19
title_full A risk scoring system to predict progression to severe pneumonia in patients with Covid-19
title_fullStr A risk scoring system to predict progression to severe pneumonia in patients with Covid-19
title_full_unstemmed A risk scoring system to predict progression to severe pneumonia in patients with Covid-19
title_short A risk scoring system to predict progression to severe pneumonia in patients with Covid-19
title_sort risk scoring system to predict progression to severe pneumonia in patients with covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8966605/
https://www.ncbi.nlm.nih.gov/pubmed/35354828
http://dx.doi.org/10.1038/s41598-022-07610-9
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