医学
围手术期
回顾性队列研究
接收机工作特性
弗雷明翰风险评分
队列
风险评估
死亡风险
队列研究
急诊医学
外科
内科学
疾病
计算机安全
计算机科学
作者
Xiaodong Wu,Qian Wang,Yuxiang Song,Xian-Yang Chen,Ting Xue,Li Ma,Yungen Luo,Hao Li,Jingsheng Lou,Yanhong Liu,Difen Wang,Qingping Wu,Yu-Ming Peng,Weidong Mi,Jiangbei Cao
标识
DOI:10.1097/js9.0000000000000791
摘要
Background: Identifying the risk factors associated with perioperative mortality is crucial, particularly in older patients. Predicting 6-month mortality risk in older patients based on large datasets can assist patients and surgeons in perioperative clinical decision-making. This study aimed to develop a risk prediction model of mortality within 6 months after noncardiac surgery using the clinical data from 11 894 older patients in China. Materials and methods: A multicentre, retrospective cohort study was conducted in 20 tertiary hospitals. The authors retrospectively included 11 894 patients (aged ≥65 years) who underwent noncardiac surgery between April 2020 and April 2022. The least absolute shrinkage and selection operator model based on linear regression was used to analyse and select risk factors, and various machine learning methods were used to build predictive models of 6-month mortality. Results: The authors predicted 12 preoperative risk factors associated with 6-month mortality in older patients after noncardiac surgery. Including laboratory-associated risk factors such as mononuclear cell ratio and total blood cholesterol level, etc. Also including medical history associated risk factors such as stroke, history of chronic diseases, etc. By using a random forest model, the authors constructed a predictive model with a satisfactory accuracy (area under the receiver operating characteristic curve=0.97). Conclusion: The authors identified 12 preoperative risk factors associated with 6-month mortality in noncardiac surgery older patients. These preoperative risk factors may provide evidence for a comprehensive preoperative anaesthesia assessment as well as necessary information for clinical decision-making by anaesthesiologists.
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