Scores based on neutrophil percentage and lactate dehydrogenase with or without oxygen saturation predict hospital mortality risk in severe COVID-19 patients.
机构：[1]Department of Infectious Diseases, First Affiliated Hospital of Xi’an JiaotongUniversity, No .277 Yanta West Road, Xi’an 710061, Shaanxi Province, People’sRepublic of China[2]Department of Pharmacy, Beijing Tiantan Hospital, CapitalMedical University, Beijing, China首都医科大学附属天坛医院[3]Immunology Research Center, Tabriz Universityof Medical Sciences, Tabriz, Iran[4]Department of Respiratory and CriticalCare Medicine, Beijing Institute of Respiratory Medicine, Beijing ChaoyangHospital, Capital Medical University, Beijing, People’s Republic of China北京朝阳医院[5]Department of Inflammation and Immunity, Cleveland Clinic, Cleveland,OH, USA[6]Science and Technology Innovation Center, Guangzhou Universityof Chinese Medicine, Guangzhou, Guangdong Province, China[7]DME Center,Institute of Clinical Pharmacology, Guangzhou University of Chinese Medicine,Guangzhou, Guangdong Province, People’s Republic of China[8]Tuberculosisand Lung Disease Research Center, Tabriz University of Medical Sciences,Tabriz, Iran[9]Department of Hepatobiliary Surgery, Union Hospital, TongjiMedical College, Huazhong University of Science and Technology, Wuhan,People’s Republic of China华中科技大学同济医学院附属协和医院
Risk scores are needed to predict the risk of death in severe coronavirus disease 2019 (COVID-19) patients in the context of rapid disease progression.
Using data from China (training dataset, n = 96), prediction models were developed by logistic regression and then risk scores were established. Leave-one-out cross validation was used for internal validation and data from Iran (test dataset, n = 43) was used for external validation.
A NSL model (area under the curve (AUC) 0.932) and a NL model (AUC 0.903) were developed based on neutrophil percentage and lactate dehydrogenase with and without oxygen saturation (SaO2) using the training dataset. AUCs of the NSL and NL models in the test dataset were 0.910 and 0.871, respectively. The risk scoring systems corresponding to these two models were established. The AUCs of the NSL and NL scores in the training dataset were 0.928 and 0.901, respectively. At the optimal cut-off value of NSL score, the sensitivity and specificity were 94% and 82%, respectively. The sensitivity and specificity of NL score were 94% and 75%, respectively.
These scores may be used to predict the risk of death in severe COVID-19 patients and the NL score could be used in regions where patients' SaO2 cannot be tested.
第一作者机构：[1]Department of Infectious Diseases, First Affiliated Hospital of Xi’an JiaotongUniversity, No .277 Yanta West Road, Xi’an 710061, Shaanxi Province, People’sRepublic of China
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推荐引用方式(GB/T 7714)：
Xiude Fan,Bin Zhu,Masoud Nouri‑Vaskeh,et al.Scores based on neutrophil percentage and lactate dehydrogenase with or without oxygen saturation predict hospital mortality risk in severe COVID-19 patients.[J].VIROLOGY JOURNAL.2021,18(1):doi:10.1186/s12985-021-01538-8.
APA：
Xiude Fan,Bin Zhu,Masoud Nouri‑Vaskeh,Chunguo Jiang,Xiaokai Feng...&Zhengwen Liu.(2021).Scores based on neutrophil percentage and lactate dehydrogenase with or without oxygen saturation predict hospital mortality risk in severe COVID-19 patients..VIROLOGY JOURNAL,18,(1)
MLA：
Xiude Fan,et al."Scores based on neutrophil percentage and lactate dehydrogenase with or without oxygen saturation predict hospital mortality risk in severe COVID-19 patients.".VIROLOGY JOURNAL 18..1(2021)
