Cargando…
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...
Autores principales: | , , , , , , , |
---|---|
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 |
_version_ | 1784678676415119360 |
---|---|
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. |
format | Online Article Text |
id | pubmed-8966605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT leejiyeon ariskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT nambyungho ariskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT kimmhinjine ariskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT hwangjongmin ariskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT kimjinyoung ariskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT hyunmiri ariskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT kimhyunah ariskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT chochiheum ariskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT leejiyeon riskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT nambyungho riskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT kimmhinjine riskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT hwangjongmin riskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT kimjinyoung riskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT hyunmiri riskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT kimhyunah riskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 AT chochiheum riskscoringsystemtopredictprogressiontoseverepneumoniainpatientswithcovid19 |