Abstract
BACKGROUND: Effective body temperature management is crucial for the favorable prognosis of patients undergoing surgery. The purpose of this study is to explore the risk factors of intraoperative hypothermia and to develop a risk prediction model to provide basis for clinical treatment. METHODS: Patients who underwent laparoscopic surgery in a tertiary hospital in China from February 1, 2023 to January 31, 2024 were included. The body temperature characteristics of patients in hypothermia group and non-hypothermia group were collected and evaluated. Univariate and Logistic regression analysis were used to evaluate the influencing factors. Based on the regression coefficients of risk factors, a risk prediction model of hypothermia was established. The model was assessed by Hosmer's Lemeshow (H- L) test and receiver working characteristic (ROC) curve. RESULTS: In 216 patients undergoing laparoscopic surgery, the incidence of hypothermia was 52.78 %. BMI≤23 kg/m(2)(OR = 2.061, 95%CI: 1.413-3.263), basal body temperature≤36.1 °C (OR = 3.715, 95%CI: 3.011-4.335), operating room temperature≤22 °C (OR = 2.481, 95%CI: 1.906-3.014), length of surgery≥120 min (OR = 2.228, 95%CI: 1.925-2.981) were the risk factors of hypothermia in patients undergoing laparoscopic surgery (all P < 0.05). The P value of H-L test was 0.098, the area under ROC curve and 95%CI were 0.806 (0.746-0.869). The sensitivity and specificity of the model in this study were good. CONCLUSIONS: Patients undergoing laparoscopic surgery are at a high risk of developing hypothermia, a condition influenced by a multitude of factors. This model is designed to be integrated into clinical practice, enabling healthcare providers to identify patients with a higher risk and to implement targeted preventive measures.