摘要
目的:构建ICU获得性肌无力的风险预测模型并验证应用效果。方法:选取2020年8月—2021年12月广东省4所三级甲等综合医院成人综合重症医学科330例ICU病人作为研究对象,采用自行设计的病例报告表收集病人资料。采用多因素Logistic回归方法构建风险预测模型,对模型进行内部验证和外部验证。基于Logistic回归模型开发微信小程序和绘制列线图。结果:最终纳入ICU住院天数、是否机械通气、年龄、呼吸机使用时间、急性生理与慢性健康状况评分(APACHEⅡ)5个因素构建多因素Logistic回归模型。模型内部验证:受试者工作特征曲线下面积(AUC)为0.879,灵敏度为0.762,特异度为0.838,准确性为0.805;外部验证:AUC为0.755,灵敏度为0.682,特异度为0.740,准确性为0.727。模型的两种临床实际应用方法:小程序得出概率≥0.648时,提示病人有发生ICU获得性肌无力的风险;列线图总得分≥14.2分时,表明病人极有可能发生ICU获得性肌无力。结论:构建的ICU获得性肌无力风险预测模型具有较高的区分度和校准度,微信小程序和列线图两种方法均能帮助临床快速、高效地筛查出病人发生ICU获得性肌无力的风险。
Objective:To construct risk prediction model of intensive care unit⁃acquired weakness,and to verify its application effect.Methods:A total of 330 ICU patients in the adult general intensive care department of 4 tertiary grade A hospitals in Guangdong province from August 2020 to December 2021,were selected as the study objects,and patients data were collected by self⁃designed case report form.Multivariate Logistic regression method was used to construct the risk prediction model,and the model was verified internally and externally.WeChat mini program and Nomograph based on Logistic regression model were developed.Results:Multivariate Logistic regression model included the length of stay in ICU,mechanical ventilation,age,ventilator use time and APACHEⅡ.The internal verification results of the model showed that the area under the receiver operating characteristic curve(AUC)was 0.879,the sensitivity was 0.762,the specificity was 0.838,and the accuracy was 0.805.External verification results showed that AUC was 0.755,the sensitivity was 0.682,the specificity was 0.740,and the accuracy was 0.727.The results of clinical application of the model showed that:the probability≥0.648 from the mini⁃program suggested that patients were at risk for ICU acquired weakness;the total Nomogram score≥14.2 suggested that patients were at high risk for ICU acquired weakness.Conclusion:The constructed risk prediction model of intensive care unit⁃acquired weakness had high degree of distinction and calibration.Both WeChat mini program and Nomograph methods could help patients to screen the risk of ICU acquired weakness quickly and efficiently.
作者
杨霞
于红静
潘泽林
梁梓杨
叶敏怡
何志丽
梅楚楠
覃湘君
凌冬兰
陈利芬
YANG Xia;YU Hongjing;PAN Zelin;LIANG Ziyang;YE Minyi;HE Zhili;MEI Chunan;QIN Xiangjun;LING Donglan;CHEN Lifen(The Second Affiliated Hospital of Guangzhou Medical University,Guangdong 510260 China)
出处
《护理研究》
北大核心
2023年第15期2673-2683,共11页
Chinese Nursing Research
基金
广州医科大学附属第二医院护理科研基金项目,编号:A202001
2021年广州护理学会科研课题立项项目,编号:A2021079。
关键词
重症监护室
ICU获得性肌无力
危险因素
列线图
intensive care unit
intensive care unit⁃acquired weakness
risk factors
Nomograph
