Abstract
OBJECTIVE: To analyze the factors associated with intraoperative hypothermia (IHC) in elderly patients undergoing total joint replacement under general anesthesia based on preoperative nutritional status, intraoperative fluid administration volume, operating room temperature, and anesthesia duration, and to construct and validate a risk prediction model. METHODS: A retrospective study was conducted on 120 elderly patients who underwent joint replacement surgery at our hospital between March 2023 and March 2025. All patient data were obtained from the electronic medical record system, and patients were divided into an IHC group and a non-IHC group based on whether they experienced IHC. Patient-related data were collected and compared. Selection operator (LASSO) regression analysis and multivariate logistic analysis were performed to identify risk factors for IHC in elderly patients undergoing joint replacement surgery. A prediction model was established using R software and validated. RESULTS: A total of 120 elderly patients who underwent joint replacement surgery at our hospital were included in this study. According to medical record system records, 21 patients developed IHC, accounting for 17.50%, and were included in the IHC group. Ninety-nine patients did not develop IHC, accounting for 82.50%, and were included in the non-IHC group. There were significant statistical differences between the IHC group and the non-IHC group in terms of BMI, intraoperative fluid administration volume, operating room temperature, anesthesia duration, serum albumin (ALB), and total protein (TP; p < 0.05). After LASSO regression analysis, none of the above indicators exhibited multicollinearity or overfitting. Logistic regression analysis revealed that intraoperative fluid administration volume and anesthesia duration were risk factors for IHC in elderly joint replacement surgery patients (OR = 1.002, 142.629, p < 0.05), Operating room temperature and ALB were protective factors for IHC in elderly joint replacement surgery patients (OR = 0.626, 0.712, p < 0.05); Based on the results of the logistic regression analysis, a risk prediction model for IHC in elderly joint replacement surgery patients was constructed using a nomogram. The ROC curve showed an AUC value of 0.994 (95% CI: 0.985-1.000). While this indicates excellent discriminative ability in the current cohort, we acknowledge that such a high value may reflect overfitting due to the limited sample size. External validation is required to confirm the model's generalizability. The calibration curve indicated that the model's predicted results were well aligned with the actual occurrence of IHC in patients. The Cox-Snell R(2) was 0.89, Nagelkerke R(2) was 0.538, Brier Score was 0.027, model fit p-value was 1.00, and the statistic was 0.08. The clinical decision curve was generally above the two extreme curves, indicating that the factors included in the nomogram have a high net benefit in predicting IHC occurrence in patients. CONCLUSION: There are numerous factors associated with the occurrence of IHC in elderly patients undergoing joint replacement surgery, primarily including intraoperative fluid administration volume, operating room temperature, anesthesia duration, and ALB. The risk prediction nomogram model constructed based on these factors demonstrates certain predictive value for the risk of IHC occurrence. Clinically, early screening of high-risk populations and implementation of targeted nursing interventions hold significant implications for clinical outcomes.