The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19

This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients adm...

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Autores principales:	Zhichuang Lian, Yafang Li, Wenyi Wang, Wei Ding, Zongxin Niu, Xiaohong Yang, Chao Wu
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Medical emergencies. Critical care. Intensive care. First aid RC86-88.9
Acceso en línea:	https://doaj.org/article/bcfa8771072541cda8745c9904059472
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spelling	oai:doaj.org-article:bcfa8771072541cda8745c99040594722021-11-29T00:56:56ZThe Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-192090-285910.1155/2021/7711056https://doaj.org/article/bcfa8771072541cda8745c99040594722021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/7711056https://doaj.org/toc/2090-2859This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466–18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227–87.021), cough (OR = 5517, 95% CI 0.258–65.024), and venous thrombosis (OR = 7322, 95% CI 0.278–95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients’ ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was −3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients’ conditions and providing early intervention for those with risk factors.Zhichuang LianYafang LiWenyi WangWei DingZongxin NiuXiaohong YangChao WuHindawi LimitedarticleMedical emergencies. Critical care. Intensive care. First aidRC86-88.9ENEmergency Medicine International, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medical emergencies. Critical care. Intensive care. First aid RC86-88.9
spellingShingle	Medical emergencies. Critical care. Intensive care. First aid RC86-88.9 Zhichuang Lian Yafang Li Wenyi Wang Wei Ding Zongxin Niu Xiaohong Yang Chao Wu The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19
description	This study analyzed the risk factors for patients with COVID-19 developing severe illnesses and explored the value of applying the logistic model combined with ROC curve analysis to predict the risk of severe illnesses at COVID-19 patients’ admissions. The clinical data of 1046 COVID-19 patients admitted to a designated hospital in a certain city from July to September 2020 were retrospectively analyzed, the clinical characteristics of the patients were collected, and a multivariate unconditional logistic regression analysis was used to determine the risk factors for severe illnesses in COVID-19 patients during hospitalization. Based on the analysis results, a prediction model for severe conditions and the ROC curve were constructed, and the predictive value of the model was assessed. Logistic regression analysis showed that age (OR = 3.257, 95% CI 10.466–18.584), complications with chronic obstructive pulmonary disease (OR = 7.337, 95% CI 0.227–87.021), cough (OR = 5517, 95% CI 0.258–65.024), and venous thrombosis (OR = 7322, 95% CI 0.278–95.020) were risk factors for COVID-19 patients developing severe conditions during hospitalization. When complications were not taken into consideration, COVID-19 patients’ ages, number of diseases, and underlying diseases were risk factors influencing the development of severe illnesses. The ROC curve analysis results showed that the AUC that predicted the severity of COVID-19 patients at admission was 0.943, the optimal threshold was −3.24, and the specificity was 0.824, while the sensitivity was 0.827. The changes in the condition of severe COVID-19 patients are related to many factors such as age, clinical symptoms, and underlying diseases. This study has a certain value in predicting COVID-19 patients that develop from mild to severe conditions, and this prediction model is a useful tool in the quick prediction of the changes in patients’ conditions and providing early intervention for those with risk factors.
format	article
author	Zhichuang Lian Yafang Li Wenyi Wang Wei Ding Zongxin Niu Xiaohong Yang Chao Wu
author_facet	Zhichuang Lian Yafang Li Wenyi Wang Wei Ding Zongxin Niu Xiaohong Yang Chao Wu
author_sort	Zhichuang Lian
title	The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19
title_short	The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19
title_full	The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19
title_fullStr	The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19
title_full_unstemmed	The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19
title_sort	prediction model of risk factors for covid-19 developing into severe illness based on 1046 patients with covid-19
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/bcfa8771072541cda8745c9904059472
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The Prediction Model of Risk Factors for COVID-19 Developing into Severe Illness Based on 1046 Patients with COVID-19

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