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Development and validation of the HNC-LL score for predicting the severity of coronavirus disease 2019

Authors :
Lu-shan Xiao
Wen-Feng Zhang
Meng-chun Gong
Yan-pei Zhang
Li-ya Chen
Hong-bo Zhu
Chen-yi Hu
Pei Kang
Li Liu
Hong Zhu
Source :
EBioMedicine, Vol 57, Iss , Pp 102880- (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Background: Information regarding risk factors associated with severe coronavirus disease (COVID-19) is limited. This study aimed to develop a model for predicting COVID-19 severity. Methods: Overall, 690 patients with confirmed COVID-19 were recruited between 1 January and 18 March 2020 from hospitals in Honghu and Nanchang; finally, 442 patients were assessed. Data were categorised into the training and test sets to develop and validate the model, respectively. Findings: A predictive HNC-LL (Hypertension, Neutrophil count, C-reactive protein, Lymphocyte count, Lactate dehydrogenase) score was established using multivariate logistic regression analysis. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC]=0.861, 95% confidence interval [CI]: 0.800–0.922; P

Details

Language :
English
ISSN :
23523964
Volume :
57
Issue :
102880-
Database :
Directory of Open Access Journals
Journal :
EBioMedicine
Publication Type :
Academic Journal
Accession number :
edsdoj.4fa9aa62aa824e29b5b91eaa9e32c26d
Document Type :
article
Full Text :
https://doi.org/10.1016/j.ebiom.2020.102880