ArticleAnnals of medicine2025
Development and validation of a novel risk assessment model for accurate prediction of intraoperative hypothermia in adult patients undergoing different types of surgery: insights from a multicentre, retrospective cohort study.
Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Preoperative geriatric nutritional risk index as a predictor of intraoperative hypothermia in esophageal cancer surgery.Asia-Pacific journal of oncology nursing · 2026Article
- Risk prediction models for inadvertent intraoperative hypothermia in surgical patients: a systematic review and meta-analysis.International journal of nursing studies advances · 2026Review
- Prevalence and risk factors associated with inadvertent intraoperative hypothermia in patients undergoing trauma surgery: a single-center retrospective study.BMC surgery · 2026Article
- The relationship between preoperative temperature and intraoperative hypothermia in patients undergoing robotic colorectal cancer surgery.Journal of robotic surgery · 2025Article
- Development and validation of a machine learning-based prediction model for intraoperative hypothermia in Chinese patients undergoing gastrointestinal surgery.Perioperative medicine (London, England) · 2025Article
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Authors and funding
8 authors.
Funding
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Abstract
backgroundIntraoperative hypothermia is a prevalent complication that may significant clinical and economic burdens. Previous risk assessment models have demonstrated limitations in accurately predicting intraoperative hypothermia, particularly in diverse surgical populations. This study aims to develop and validate a model in adult surgical patients to improve outcomes.
methodsThis retrospective cohort study utilized data extracted from electronic medical records and anaesthesia information management systems between June 2022 and August 2023. The analysis included information of 3,405 adult surgical patients from three independent centres in China who underwent elective surgical procedures with body temperature monitoring. Intraoperative hypothermia was defined as a core temperature below 36 °C during surgery. The Least Absolute Shrinkage and Selection Operator (LASSO) regression employed to select optimal features and multivariate logistic regression was used to identify independent predictors of intraoperative hypothermia and then built the risk assessment model. We further evaluated the discriminative ability, calibration curves, and clinical utility of the predictive model.
resultsThe total incidences of intraoperative hypothermia in adult surgical patients were 42.5%. The predictors in the intraoperative hypothermia model included: age, BMI, baseline HR, baseline temperature, minimally invasive surgery, smoking, previous surgery and serum creatine level. In the training cohort, the model demonstrated strong discriminatory ability, with C-index values of 0.721 (95% CI 0.697-0.744). Internal and external validation further confirmed the model's robustness and generalizability.
conclusionThese findings suggest that our model may help us more accurately identify patients at risk of intraoperative hypothermia.
trial registrationChina Clinical Trial Registration Center (ChiCTR2300071859), Date registered May/26/2023.
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