Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study

Objectives: To develop and internally validate two clinical risk scores to detect coronavirus disease 2019 (COVID-19) during local outbreaks. Methods: Medical records were extracted for a retrospective cohort of 336 suspected patients admitted to Baodi hospital between 27 January to 20 February 2020...

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Autores principales: Sun, Zhuoyu, Guo, Yi’an, He, Wei, Chen, Shiyue, Sun, Changqing, Zhu, Hong, Li, Jing, Chen, Yongjie, Du, Yue, Wang, Guangshun, Yang, Xilin, Su, Hongjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9485465/
https://www.ncbi.nlm.nih.gov/pubmed/36147884
http://dx.doi.org/10.3389/ijph.2022.1604794
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author Sun, Zhuoyu
Guo, Yi’an
He, Wei
Chen, Shiyue
Sun, Changqing
Zhu, Hong
Li, Jing
Chen, Yongjie
Du, Yue
Wang, Guangshun
Yang, Xilin
Su, Hongjun
author_facet Sun, Zhuoyu
Guo, Yi’an
He, Wei
Chen, Shiyue
Sun, Changqing
Zhu, Hong
Li, Jing
Chen, Yongjie
Du, Yue
Wang, Guangshun
Yang, Xilin
Su, Hongjun
author_sort Sun, Zhuoyu
collection PubMed
description Objectives: To develop and internally validate two clinical risk scores to detect coronavirus disease 2019 (COVID-19) during local outbreaks. Methods: Medical records were extracted for a retrospective cohort of 336 suspected patients admitted to Baodi hospital between 27 January to 20 February 2020. Multivariate logistic regression was applied to develop the risk-scoring models, which were internally validated using a 5-fold cross-validation method and Hosmer-Lemeshow (H-L) tests. Results: Fifty-six cases were diagnosed from the cohort. The first model was developed based on seven significant predictors, including age, close contact with confirmed/suspected cases, same location of exposure, temperature, leukocyte counts, radiological findings of pneumonia and bilateral involvement (the mean area under the receiver operating characteristic curve [AUC]:0.88, 95% CI: 0.84–0.93). The second model had the same predictors except leukocyte and radiological findings (AUC: 0.84, 95% CI: 0.78–0.89, Z = 2.56, p = 0.01). Both were internally validated using H-L tests and showed good calibration (both p > 0.10). Conclusion: Two clinical risk scores to detect COVID-19 in local outbreaks were developed with excellent predictive performances, using commonly measured clinical variables. Further external validations in new outbreaks are warranted.
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spelling pubmed-94854652022-09-21 Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study Sun, Zhuoyu Guo, Yi’an He, Wei Chen, Shiyue Sun, Changqing Zhu, Hong Li, Jing Chen, Yongjie Du, Yue Wang, Guangshun Yang, Xilin Su, Hongjun Int J Public Health Public Health Archive Objectives: To develop and internally validate two clinical risk scores to detect coronavirus disease 2019 (COVID-19) during local outbreaks. Methods: Medical records were extracted for a retrospective cohort of 336 suspected patients admitted to Baodi hospital between 27 January to 20 February 2020. Multivariate logistic regression was applied to develop the risk-scoring models, which were internally validated using a 5-fold cross-validation method and Hosmer-Lemeshow (H-L) tests. Results: Fifty-six cases were diagnosed from the cohort. The first model was developed based on seven significant predictors, including age, close contact with confirmed/suspected cases, same location of exposure, temperature, leukocyte counts, radiological findings of pneumonia and bilateral involvement (the mean area under the receiver operating characteristic curve [AUC]:0.88, 95% CI: 0.84–0.93). The second model had the same predictors except leukocyte and radiological findings (AUC: 0.84, 95% CI: 0.78–0.89, Z = 2.56, p = 0.01). Both were internally validated using H-L tests and showed good calibration (both p > 0.10). Conclusion: Two clinical risk scores to detect COVID-19 in local outbreaks were developed with excellent predictive performances, using commonly measured clinical variables. Further external validations in new outbreaks are warranted. Frontiers Media S.A. 2022-09-06 /pmc/articles/PMC9485465/ /pubmed/36147884 http://dx.doi.org/10.3389/ijph.2022.1604794 Text en Copyright © 2022 Sun, Guo, He, Chen, Sun, Zhu, Li, Chen, Du, Wang, Yang and Su. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health Archive
Sun, Zhuoyu
Guo, Yi’an
He, Wei
Chen, Shiyue
Sun, Changqing
Zhu, Hong
Li, Jing
Chen, Yongjie
Du, Yue
Wang, Guangshun
Yang, Xilin
Su, Hongjun
Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study
title Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study
title_full Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study
title_fullStr Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study
title_full_unstemmed Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study
title_short Development of Clinical Risk Scores for Detection of COVID-19 in Suspected Patients During a Local Outbreak in China: A Retrospective Cohort Study
title_sort development of clinical risk scores for detection of covid-19 in suspected patients during a local outbreak in china: a retrospective cohort study
topic Public Health Archive
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9485465/
https://www.ncbi.nlm.nih.gov/pubmed/36147884
http://dx.doi.org/10.3389/ijph.2022.1604794
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