Abstract
OBJECTIVES: Postoperative hypothermia is a common clinical complication with a high incidence rate, potentially adversely affecting postoperative recovery. Transurethral holmium laser enucleation of the prostate (HoLEP) is a minimally invasive procedure for benign prostatic hyperplasia (BPH). Offering advantages such as minimal bleeding, broad indications, and rapid postoperative recovery. However, research on risk factors for postoperative hypothermia following HoLEP remains limited, and predictive models for guiding clinical practice are lacking. This study aims to develop a predictive model for assessing the risk of postoperative hypothermia in HoLEP patients and to identify relevant risk factors. METHODS: Clinical data from patients who underwent HoLEP at affiliated Hospital of Shandong Second Medical University were retrospectively collected. Patients were categorized into a hypothermia group and a non-hypothermia group based on whether postoperative hypothermia occurred. Preoperative, intraoperative, and postoperative indicators were compared between the 2 groups. Least absolute shrinkage and selection operator (LASSO) regression combined with logistic regression analysis was used to analyze clinical data. A predictive model for assessing the risk of postoperative hypothermia after HoLEP was constructed and internally validated using bootstrap resampling. RESULTS: A total of 403 patients were included in the analysis, among whom 85 patients developed postoperative hypothermia, with an incidence rate of 21.1%. Logistic regression analysis identified operative duration (OR=1.009, 95% CI 1.003 to 1.015), underweight status (OR=9.881, 95% CI 4.038 to 24.910), and prostate weight (OR=1.021, 95% CI 1.012 to 1.030) as independent risk factors for postoperative hypothermia, and these variables were incorporated into the nomogram model. Internal validation showed strong discriminative ability of the nomogram, with an area under the receiver operating characteristic curve (AUC) of 0.755 (95% CI 0.686 to 0.820) and a C-index of 0.832 (95% CI 0.787 to 0.865). The calibration curve demonstrated good consistency between predicted and observed outcomes. Decision curve analysis showed that the nomogram provided greater clinical utility when the risk threshold for postoperative hypothermia was between 8% and 97%. CONCLUSIONS: This study developed a nomogram model for predicting the risk of postoperative hypothermia in HoLEP patients, providing clinicians with a simple and effective predictive tool for individualized risk assessment and preoperative decision-making.