A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19

Abstract. Objective:. Coronavirus disease 2019 (COVID-19) exists as a pandemic. Mortality during hospitalization is multifactorial, and there is urgent need for a risk stratification model to predict in-hospital death among COVID-19 patients. Here we aimed to construct a risk score system for early...

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Main Authors: Hesong Zeng, Xingwei He, Wanjun Liu, Jing Kan, Liqun He, Jinhe Zhao, Cynthia Chen, Junjie Zhang, Shaoliang Chen, Xiaoxia Fu, Tianyu Xu
Format: Article
Language:English
Published: Wolters Kluwer Health/LWW 2022-06-01
Series:Cardiology Discovery
Online Access:http://journals.lww.com/10.1097/CD9.0000000000000052
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author Hesong Zeng
Xingwei He
Wanjun Liu
Jing Kan
Liqun He
Jinhe Zhao
Cynthia Chen
Junjie Zhang
Shaoliang Chen
Xiaoxia Fu
Tianyu Xu
author_facet Hesong Zeng
Xingwei He
Wanjun Liu
Jing Kan
Liqun He
Jinhe Zhao
Cynthia Chen
Junjie Zhang
Shaoliang Chen
Xiaoxia Fu
Tianyu Xu
author_sort Hesong Zeng
collection DOAJ
description Abstract. Objective:. Coronavirus disease 2019 (COVID-19) exists as a pandemic. Mortality during hospitalization is multifactorial, and there is urgent need for a risk stratification model to predict in-hospital death among COVID-19 patients. Here we aimed to construct a risk score system for early identification of COVID-19 patients at high probability of dying during in-hospital treatment. Methods:. In this retrospective analysis, a total of 821 confirmed COVID-19 patients from 3 centers were assigned to developmental (n = 411, between January 14, 2020 and February 11, 2020) and validation (n = 410, between February 14, 2020 and March 13, 2020) groups. Based on demographic, symptomatic, and laboratory variables, a new Coronavirus estimation global (CORE-G) score for prediction of in-hospital death was established from the developmental group, and its performance was then evaluated in the validation group. Results:. The CORE-G score consisted of 18 variables (5 demographics, 2 symptoms, and 11 laboratory measurements) with a sum of 69.5 points. Goodness-of-fit tests indicated that the model performed well in the developmental group (H = 3.210, P = 0.880), and it was well validated in the validation group (H = 6.948, P = 0.542). The areas under the receiver operating characteristic curves were 0.955 in the developmental group (sensitivity, 94.1%; specificity, 83.4%) and 0.937 in the validation group (sensitivity, 87.2%; specificity, 84.2%). The mortality rate was not significantly different between the developmental (n = 85,20.7%) and validation (n = 94, 22.9%, P = 0.608) groups. Conclusions:. The CORE-G score provides an estimate of the risk of in-hospital death. This is the first step toward the clinical use of the CORE-G score for predicting outcome in COVID-19 patients.
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spelling doaj-art-ad4a41be25d44f1bab3b2f5b7f31e55e2025-08-20T03:17:55ZengWolters Kluwer Health/LWWCardiology Discovery2096-952X2693-84992022-06-0122697610.1097/CD9.0000000000000052202206000-00001A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19Hesong ZengXingwei HeWanjun LiuJing KanLiqun HeJinhe ZhaoCynthia ChenJunjie ZhangShaoliang ChenXiaoxia FuTianyu XuAbstract. Objective:. Coronavirus disease 2019 (COVID-19) exists as a pandemic. Mortality during hospitalization is multifactorial, and there is urgent need for a risk stratification model to predict in-hospital death among COVID-19 patients. Here we aimed to construct a risk score system for early identification of COVID-19 patients at high probability of dying during in-hospital treatment. Methods:. In this retrospective analysis, a total of 821 confirmed COVID-19 patients from 3 centers were assigned to developmental (n = 411, between January 14, 2020 and February 11, 2020) and validation (n = 410, between February 14, 2020 and March 13, 2020) groups. Based on demographic, symptomatic, and laboratory variables, a new Coronavirus estimation global (CORE-G) score for prediction of in-hospital death was established from the developmental group, and its performance was then evaluated in the validation group. Results:. The CORE-G score consisted of 18 variables (5 demographics, 2 symptoms, and 11 laboratory measurements) with a sum of 69.5 points. Goodness-of-fit tests indicated that the model performed well in the developmental group (H = 3.210, P = 0.880), and it was well validated in the validation group (H = 6.948, P = 0.542). The areas under the receiver operating characteristic curves were 0.955 in the developmental group (sensitivity, 94.1%; specificity, 83.4%) and 0.937 in the validation group (sensitivity, 87.2%; specificity, 84.2%). The mortality rate was not significantly different between the developmental (n = 85,20.7%) and validation (n = 94, 22.9%, P = 0.608) groups. Conclusions:. The CORE-G score provides an estimate of the risk of in-hospital death. This is the first step toward the clinical use of the CORE-G score for predicting outcome in COVID-19 patients.http://journals.lww.com/10.1097/CD9.0000000000000052
spellingShingle Hesong Zeng
Xingwei He
Wanjun Liu
Jing Kan
Liqun He
Jinhe Zhao
Cynthia Chen
Junjie Zhang
Shaoliang Chen
Xiaoxia Fu
Tianyu Xu
A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19
Cardiology Discovery
title A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19
title_full A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19
title_fullStr A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19
title_full_unstemmed A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19
title_short A New Coronavirus Estimation Global Score for Predicting Mortality During Hospitalization in Patients with COVID-19
title_sort new coronavirus estimation global score for predicting mortality during hospitalization in patients with covid 19
url http://journals.lww.com/10.1097/CD9.0000000000000052
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