Scoring systems for predicting mortality for severe patients with COVID-19
Scoring systems for predicting mortality for severe patients with COVID-19
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DOI：
10.1016/j.eclinm.2020.100426
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发表时间：
2020-07-01
影响因子：
15.1
通讯作者：
Zhou, Fuling
中科院分区：
文献类型：
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作者：
Shang, Yufeng;Liu, Tao;Zhou, Fuling
工作背景：2019冠状病毒病（COVID-19）已广泛传播，并导致数万人死亡，尤其是严重的COVID-19患者。本分析旨在探讨重症COVID-19死亡的危险因素，并建立一个评分系统来预测院内死亡。方法：回顾性分析COVID-19患者，比较其临床特征。结果：共对2529例新冠肺炎患者进行回顾性分析，最终纳入符合条件的重症患者452例进行分析。在训练队列中，中位年龄为66.0岁，而在非幸存者中为73.0岁。年龄在60-75岁的患者占感染人群和死亡人数的最大比例。监测抗SARS-CoV-2抗体长达54天，IgG水平在20-30天期间达到最高。重症和非重症患者之间的抗体水平没有观察到差异。重症患者并发症发生率为60.2%。在急性心肌损伤（AMI）、急性肾损伤（阿基）和急性肝损伤（ALI）中，心脏是最早损伤的器官，而从阿基到死亡的时间最短。通过LASSO二元逻辑回归确定年龄、糖尿病、冠心病（CHD）、淋巴细胞百分比（LYM%）、前降钙素（PCT）、血清尿素、C反应蛋白和D-二聚体（DD）与死亡率相关。多因素分析显示高龄、CHD、LYM%、PCT和DD仍是死亡的独立危险因素。基于上述变量，建立了COVID-19（CSS）评分系统，将患者分为低风险和高风险组。该模型显示出良好的区分度（AUC=0.919）和校准（P=0.264）。低危组与高危组并发症发生率差异有统计学意义（P
Background: Coronavirus disease 2019 (COVID-19) has been widely spread and caused tens of thousands of deaths, especially in patients with severe COVID-19. This analysis aimed to explore risk factors for mortality of severe COVID-19, and establish a scoring system to predict in-hospital deaths.Methods: Patients with COVID-19 were retrospectively analyzed and clinical characteristics were compared. LASSO regression as well as multivariable analysis were used to screen variables and establish prediction model.Findings: A total of 2529 patients with COVID-19 was retrospectively analyzed, and 452 eligible severe COVID-19 were used for finally analysis. In training cohort, the median age was 66.0 years while it was 73.0 years in non-survivors. Patients aged 60-75 years accounted for the largest proportion of infected populations and mortality toll. Anti-SARS-CoV-2 antibodies were monitored up to 54 days, and IgG levels reached the highest during 20-30 days. No differences were observed of antibody levels between severe and non-severe patients. About 60.2% of severe patients had complications. Among acute myocardial injury (AMI), acute kidney injury (AKI) and acute liver injury (ALI), the heart was the earliest injured organ, whereas the time from AKI to death was the shortest. Age, diabetes, coronary heart disease (CHD), percentage of lymphocytes (LYM%), procalcitonin (PCT), serum urea, C reactive protein and D-dimer (DD), were identified associated with mortality by LASSO binary logistic regression. Then multivariable analysis was performed to conclude that old age, CHD, LYM%, PCT and DD remained independent risk factors for mortality. Based on the above variables, a scoring system of COVID-19 (CSS) was established to divide patients into low-risk and high-risk groups. This model displayed good discrimination (AUC=0.919) and calibration (P=0.264). Complications in low-risk and high-risk groups were significantly different (P