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

Background Intraoperative hypothermia is a common complication in elderly patients undergoing joint replacement surgery that can lead to adverse outcomes. Purpose 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. Single-factor 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.

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Journal
Journal of Pharmacology and Pharmacotherapeutics
Published
2025-10-03
DOI
https://doi.org/10.1177/0976500x251383596
Primary Topic
Thermal Regulation in Medicine
Type
article
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article

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

Yanhui Cui, Judy Zhu
Journal of Pharmacology and Pharmacotherapeutics
Thermal Regulation in Medicine
article

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

Yanhui Cui, Judy Zhu
article en

Abstract

Background Intraoperative hypothermia is a common complication in elderly patients undergoing joint replacement surgery that can lead to adverse outcomes. Purpose 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. Single-factor 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.

Journal of Pharmacology and Pharmacotherapeutics
Hebei Medical University (CN), Soochow University (CN), Xingtai People's Hospital (CN), First Affiliated Hospital of Soochow University (CN), The Fifth People’s Hospital of Suzhou (CN)
Openalex Percentile: Top 68%
Thermal Regulation in Medicine
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