泛免疫炎症值预测收住重症监护病房的急性缺血性卒中患者的院内死亡

Pan-immune-inflammation value predicts in-hospital mortality in patients with acute ischemic stroke admitted to the intensive care units

目的探讨泛免疫炎症值(pan-immune-inflammation value, PIV)对收住重症监护病房(intensive care unit, ICU)的急性缺血性卒中(acute ischemic stroke, AIS)患者院内死亡的预测价值。方法回顾性纳入并分析美国重症监护医学信息数据库(Medical Information Mart for Intensive Care, MIMIC)-Ⅳ中收住ICU的首次AIS患者的临床资料。根据患者是否院内死亡分为生存组和死亡组, 比较两组基线资料的差异。采用多变量logistic回归模型分析患者院内死亡的独立影响因素, 采用受试者工作特征曲线评价PIV对院内死亡的预测价值。结果共纳入1 068例收住ICU的首次AIS患者, 中位年龄69岁, 男性543例(50.84%), 182例(17.05%)发生院内死亡。多变量logistic回归分析显示, 校正潜在混杂因素后, PIV较高(>1 555.71)是患者院内死亡的独立危险因素(优势比1.924, 95%置信区间1.093~3.387;P=0.023)。受试者工作特征曲线分析显示, PIV预测院内死亡的曲线下面积为0.605(95%置信区间0.556~0.654), 最佳截断值为1 199.93, 预测院内死亡的敏感性和特异性分别为48.9%和70.2%。结论 PIV较高是收住ICU的AIS患者院内死亡的独立危险因素, 可能有助于识别ICU中院内死亡风险较高的AIS患者。

Objective To investigate the predictive value of pan-immune-inflammation value(PIV)for in-hospital mortality in patients with acute ischemic stroke(AIS)admitted to intensive care unit(ICU).Methods The clinical data of the first-ever AIS patients admitted to the ICU in the Medical Information Mart for Intensive Care(MIMIC)-Ⅳof the United States were retrospectively included and analyzed.According to whether the patients died in the hospital,they were divided into a survival group and a death group,and the differences in baseline data between the two groups were compared.Multivariate logistic regression model was used to analyze independent influencing factors of in-hospital mortality in patients.Receiver operating characteristic curve was used to evaluate the predictive value of PIV on in-hospital mortality.Results A total of 1068 first-ever AIS patients admitted to the ICU were included,with a median age of 69 years.There were 543 males(50.84%),and 182(17.05%)experienced in-hospital mortality.Multivariate logistic regression analysis showed that after adjusting for potential confounding factors,a higher PIV(>1555.71)was an independent risk factor for in-hospital mortality in patients(odds ratio 1.924,95%confidence interval 1.093-3.387;P=0.023).The receiver operating characteristic curve analysis showed that the area under the curve for predicting in-hospital mortality by PIV was 0.605(95%confidence interval 0.556-0.654),with an optimal cutoff value of 1199.93.The sensitivity and specificity for predicting in-hospital mortality were 48.9%and 70.2%,respectively.Conclusions A higher PIV is an independent risk factor for in-hospital mortality in AIS patients admitted to ICU,which may help identify AIS patients with a higher risk of in-hospital mortality in the ICU.