机械通气患者重症监护获得性肌无力的列线图模型建立

Establishment of nomogram model for prediction of intensive care unit-acquired weakness of mechanically ventilated patients

目的建立机械通气患者重症监护获得性肌无力(ICU-AW)风险列线图预测模型。方法选取2018年11月-2020年5月江苏大学附属医院入住ICU接受机械通气治疗患者353例为研究对象,其中发生ICU-AW的200例作为ICU-AW组,未发生ICU-AW的153例作为对照组,利用单因素和多因素Logistic回归筛选ICU-AW的独立危险因素。采用R软件包建立ICU-AW预测列线图,并对其预测效果进行评价。结果本次研究ICU-AW的发生率为43.34%。Logistic回归分析显示:年龄、APACHE II评分、血糖、是否使用神经阻滞药物、乳酸水平、机械通气时间是ICU-AW独立危险因素(P<0.05)。纳入该6项独立危险因素建立列线图预测模型,经验证C-index为0.873(95%CI 0.837~0.910)。结论本研究基于患者临床资料和实验室检查结果构建的ICU-AW列线图模型具有良好的特异性和敏感性,值得临床推广应用。

Objective To investigate the establishment of a risk model for intensive care unit-acquired weakness(ICU-AW)of mechanically ventilated patients by using a nomogram prediction model.Methods A total of 353 patients treated with mechanical ventilation in the department of critical care medicine in a tertiary hospital from November 2018 to May 2020 were selected,200 patients with ICU-AW were treated as ICU-AW group and 153 patients were treated as control group.Univariate analysis and logistic regression analysis were used to screen out the risk factors of ICU-AW.The nomogram prediction model was constructed by R software,and the accuracy of the model was validated.The six independent risk factors were included to establish the nomogram prediction model,the C-index was 0.873(95%CI 0.837~0.910).Conclusion In this study,ICU-AW predictive nomograms were established by the clinical data of patients and laboratory examination,with good specificity and sensitivity,which is worthy of clinical application.