Ma Xiaoxu, Li Ang, Jiao Mengfan, Shi Qingmiao, An Xiaocai, Feng Yonghai, Xing Lihua, Liang Hongxia, Chen Jiajun, Li Huiling, Li Juan, Ren Zhigang, Sun Ranran, Cui Guangying, Zhou Yongjian, Cheng Ming, Jiao Pengfei, Wang Yu, Xing Jiyuan, Shen Shen, Zhang Qingxian, Xu Aiguo, Yu Zujiang
Department of Respiration, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Henan Gene Hospital, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Front Public Health. 2020 Sep 8;8:475. doi: 10.3389/fpubh.2020.00475. eCollection 2020.
Certain high-risk factors related to the death of COVID-19 have been reported, however, there were few studies on a death prediction model. This study was conducted to delineate the clinical characteristics of patients with coronavirus disease 2019 (covid-19) of different degree and establish a death prediction model. In this multi-centered, retrospective, observational study, we enrolled 523 COVID-19 cases discharged before February 20, 2020 in Henan Province, China, compared clinical data, screened for high-risk fatal factors, built a death prediction model and validated the model in 429 mild cases, six fatal cases discharged after February 16, 2020 from Henan and 14 cases from Wuhan. Out of the 523 cases, 429 were mild, 78 severe survivors, 16 non-survivors. The non-survivors with median age 71 were older and had more comorbidities than the mild and severe survivors. Non-survivors had a relatively delay in hospitalization, with higher white blood cell count, neutrophil percentage, D-dimer, LDH, BNP, and PCT levels and lower proportion of eosinophils, lymphocytes and albumin. Discriminative models were constructed by using random forest with 16 non-survivors and 78 severe survivors. Age was the leading risk factors for poor prognosis, with AUC of 0.907 (95% CI 0.831-0.983). Mixed model constructed with combination of age, demographics, symptoms, and laboratory findings at admission had better performance ( = 0.021) with a generalized AUC of 0.9852 (95% CI 0.961-1). We chose 0.441 as death prediction threshold (with 0.85 sensitivity and 0.987 specificity) and validated the model in 429 mild cases, six fatal cases discharged after February 16, 2020 from Henan and 14 cases from Wuhan successfully. Mixed model can accurately predict clinical outcomes of COVID-19 patients.
已有研究报道了一些与新型冠状病毒肺炎（COVID-19）死亡相关的高危因素，然而，关于死亡预测模型的研究却很少。本研究旨在描述不同程度的2019冠状病毒病（COVID-19）患者的临床特征，并建立一个死亡预测模型。在这项多中心、回顾性、观察性研究中，我们纳入了2020年2月20日前在中国河南省出院的523例COVID-19病例，比较临床资料，筛选高危致死因素，建立死亡预测模型，并在429例轻症病例、2020年2月16日后从河南出院的6例死亡病例以及14例来自武汉的病例中对该模型进行验证。在这523例病例中，429例为轻症，78例为重症幸存者，16例为非幸存者。非幸存者的中位年龄为71岁，比轻症和重症幸存者年龄更大，合并症更多。非幸存者住院时间相对延迟，白细胞计数、中性粒细胞百分比、D-二聚体、乳酸脱氢酶、脑钠肽和降钙素原水平较高，而嗜酸性粒细胞、淋巴细胞和白蛋白比例较低。利用16例非幸存者和78例重症幸存者构建判别模型。年龄是预后不良的主要危险因素，曲线下面积（AUC）为0.907（95%可信区间0.831-0.983）。将年龄、人口统计学、症状和入院时实验室检查结果相结合构建的混合模型表现更好（P = 0.021），广义AUC为0.9852（95%可信区间0.961-1）。我们选择0.441作为死亡预测阈值（灵敏度为0.85，特异度为0.987），并在429例轻症病例、2020年2月16日后从河南出院的6例死亡病例以及14例来自武汉的病例中成功验证了该模型。混合模型能够准确预测COVID-19患者的临床结局。
