Development and validation of the HNC-LL score for predicting the severity of coronavirus disease 2019
Development and validation of the HNC-LL score for predicting the severity of coronavirus disease 2019
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DOI：
10.1016/j.ebiom.2020.102880
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发表时间：
2020-07-01
期刊：
影响因子：
11.1
通讯作者：
Zhu, Hong
中科院分区：
文献类型：
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作者：
Xiao, Lu-shan;Zhang, Wen-Feng;Zhu, Hong
背景：有关与严重冠状病毒疾病（COVID-19）相关的风险因素的信息有限。本研究旨在建立一个预测COVID-19严重程度的模型。方法：总体而言，在2020年1月1日至3月18日期间，从洪湖和南昌的医院招募了690名确诊的COVID-19患者;最终，对442名患者进行了评估。数据被归类到训练和测试集，以开发和验证模型，foreign.Findings：一个预测HNC-LL（高血压，中性粒细胞计数，C-反应蛋白，淋巴细胞计数，乳酸脱氢酶）得分建立使用多元逻辑回归分析。HNC-LL评分准确预测洪湖培训队列的疾病严重程度（曲线下面积[AUC]=0.861，95%置信区间[CI]：0.800-0.922; P
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