Intraoperative hypothermia risk prediction models for patients undergoing cancer surgery: a scoping review
10.3760/cma.j.cn211501-20240624-01661
- VernacularTitle:癌症手术患者术中低体温风险预测模型的范围综述
- Author:
Yuting ZOU
1
;
Ruichen LIANG
;
Yue ZHAO
;
Jie CHENG
;
Xiaoli XIA
;
Xue LIN
;
Daiying ZHANG
Author Information
1. 西南医科大学护理学院，泸州 646000
- Publication Type:Journal Article
- Keywords:
Neoplasms;
Risk assessment;
Intraoperative hypothermia;
Prediction model;
Scoping review
- From:
Chinese Journal of Practical Nursing
2025;41(19):1504-1511
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To conduct a scoping review of risk prediction models for the development of intraoperative hypothermia in patients undergoing cancer surgery to inform clinical nursing practice and future research.Methods:Relevant literature on constructing or validating intraoperative hypothermia risk prediction models for cancer surgery patients in five foreign language databases (PubMed, Embase, Web of Science, Cochrane Library, CINAHL) and four Chinese language databases (China National Knowledge Infrastructure, Wanfang, VIP, Chinese Biomedical Database) were searched from the time of library construction to June 1, 2024, extracted information on the applicable target, incidence of intraoperative hypothermia, methodology of model construction, predictors and performance, etc. The Prediction model Risk Of Bias Assessment Tool was used to evaluate the risk of bias of the studies, and the included literature was analyzed and discussed.Results:A total of 15 pieces of literature involving 18 models were included, with the study population focussing on patients undergoing surgery for colorectal cancer. The rate of intraoperative hypothermia ranged from 15.14% to 61.5%. Model construction methods included 2 types of Logistic regression models and machine learning, and model presentation was based on column-line plots. There were 8 predictors that appeared with a frequency of ≥5, including age, body mass index, operation time, anaesthesia time, operating room temperature, intraoperative rehydration volume, intraoperative bleeding volume, and heat preservation method.Conclusions:The performance of the included model was good, but the risk of bias was high for the predictors and the analysis part, and nursing staff should pay close attention to the risk factors of intraoperative hypothermia in patients undergoing cancer surgery, construct a risk prediction model with low bias and high applicability, and validate and improve the existing risk prediction model.
