Abstract
Inadvertent intraoperative hypothermia (IOH) significantly increases the risk of complications in elderly patients undergoing general anesthesia. This study aimed to develop and validate a predictive model for IOH specifically for elderly patients in Southwest China. A total of 443 patients aged ≥ 60 years from 24 hospitals were enrolled and randomly assigned to a derivation cohort (n = 310) and an internal validation cohort (n = 133). Logistic regression, LASSO regression, and random forest models were developed, with internal validation used to select the optimal approach. External validation was performed on 334 patients from 4 participating and 4 non-participating hospitals. In the internal validation, the Logistic Regression model outperformed machine learning algorithms, demonstrating an area under the receiver operating characteristic curve (AUC) of 0.841 (95% CI: 0.772–0.910), with a specificity of 81.48%, sensitivity of 70.21%, and optimal risk threshold of 48%. In the external validation cohort (n = 334), the model maintained robust discriminative ability (AUC: 0.760; 95% CI: 0.703–0.817). Crucially, in a subgroup analysis of patients with normal temperature (≥ 36.5℃) at 10 min before anesthesia induction, the model successfully identified 34 high-risk individuals who would likely be overlooked by standard clinical assessment. The Logistic Regression model effectively predicts IOH risk in elderly patients, and a risk probability ≥ 48% serves as a critical threshold to guide stratified temperature management.
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The data for this study and the protocol can be obtained by contacting the corresponding author.
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This study was funded by Chinese Society of Cardiothoracic and Vascular Anesthesiology (2022-CSCTVA-AAS-01).
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*Acquisition, analysis, or interpretation of data: * All authors.*Critical revision of the manuscript for important intellectual content: * All authors.*Administrative, technical, or material support: * Ke Wei, Jun Hu, Feng Lv, Chunyuan Liu, Hao Li, Chaoyang Zeng, Ailing Wu, Hui Zhong, Guihua Huang, Jianxiong Wu, Yongfeng Liu, Deyuan Li, Daishun Xiao, Feng Xu, Jian Xian, Yunming Yu, Shuiping Xu, Yue Li, Zeliang Huang, Qingyan Lin, Jin Hua, Zhonghui Wang, Feng Chen, Chaoyu Li, Tiande Yang, Xianfeng Xie, Su Min.
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Wei, D., Tao, Y., Min, S. et al. A multicenter predictive model for inadvertent intraoperative hypothermia management in elderly patients in Southwest China. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41395-5
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DOI: https://doi.org/10.1038/s41598-026-41395-5
