刘尧妙 1李乐之 1何玲 2杨瑞莉 2谢娟玉 2伍娜娜 2刘艳妹2
作者信息
- 1. 湖南中医药大学 护理学院,湖南 长沙 410508
- 2. 中南大学湘雅二医院 心血管外科,湖南 长沙 410011
- 折叠
摘要
Abstract
Objective To explore the risk factors of subsyndromal delirium(SSD)in patients after cardiac surgery,to construct a prediction model for the occurrence of SSD in this group,and verify its performance.Methods A total of 549 surgical patients in the cardiac surgery department of a tertiary Grade-A hospital in Hunan Province from August 2023 to July 2024 were selected.They were divided into a non-delirium group and a delirium group based on the occurrence of SSD during their ICU stay.The patients were divided into a training set and a test set at a ratio of 7:3.A prediction model was developed using the random forest algorithm on the training set,validated in the testing set,and subjected to variable importance ranking.Results Among the 549 patients,63 were diagnosed with SSD.There were no statistically significant differences between the non-delirium and delirium group in terms of sex,height,place of residence,and mode of admission(P>0.05).The variables selected by Lasso regression were incorporated into the model constructed by random forest algorithm,demonstrating that the predictive efficacy of the model in the test set was 0.959.The variables with importance ranking from high to low were the rate of adrenaline decline,the rate of noradrenaline decline,first-day urine output,mean corpuscular hemoglobin concentration(MCHC),body weight,age,post-MVR(mitral valve replacement),post-CABG(coronary artery bypass grafting),and post-AVR(aortic valve replacement).Conclusion The influencing factors for the occurrence of SSD in patients after cardiac surgery,with importance ranking from high to low are the rate of adrenaline decline,the rate of noradrenaline decline,first-day urine output,MCHC,body weight,age,post-MVR,post-CABG,and post-AVR.The model constructed by random forest algorithm has good predictive efficacy.关键词
随机森林法/心脏外科术后/亚谵妄综合征/预测模型Key words
random forest algorithm/postoperative cardiac surgery/subsyndromal delirium/prediction model分类
临床医学
