Development and Validation of a Risk Prediction Model for Intraoperative Hypothermia in Elderly Patients Undergoing Total Hip Replacement Surgery

ABSTRACT

Background: Intraoperative hypothermia is a common complication in elderly patients undergoing joint replacement surgery that can lead to adverse outcomes. Objectives: This study aimed to analyze the pertinent risk factors influencing intraoperative hypothermia in elderly patients undergoing joint replacement and to develop and validate a risk prediction model. Materials and Methods: A retrospective analysis was conducted on clinical data from 302 elderly patients undergoing hip joint replacement surgery. These patients were divided into two groups: the hypothermia group (intraoperative hypothermia (IH) group) and the non-hypothermia group (non-IH group) based on the presence of intraoperative hypothermia. Singlefactor and multivariate logistic regression analyses were employed to identify the risk factors associated with intraoperative hypothermia in elderly joint replacement patients and to establish a predictive model for hypothermia risk. The receiver operating characteristic curve (ROC) was utilized to assess and validate the model. Results: Among the 302 patients, 92 experienced intraoperative hypothermia, resulting in an incidence rate of 30.46%. Multivariate logistic regression analysis revealed that age and fasting time were independent risk factors for hypothermia, whereas body mass index (BMI), baseline temperature, preoperative heart rate, and anesthesia method were identified as protective factors (p < .05). ROC curve analysis demonstrated an area under the curve (AUC) of 0.902, sensitivity of 71.4%, and specificity of 93.0%. The calibration of the prediction model exhibited satisfactory consistency between actual hypothermia occurrences and predicted outcomes. Conclusion: The risk prediction model developed in this study exhibits robust predictive performance and holds significant clinical utility.

KEYWORDS

• Hip joint replacement surgery
• hypothermia
• risk prediction model

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• DOI10.1177/0976500X251383596Copy

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