Construction and validation of an intraoperative hypothermia prediction model in patients with breast cancer

Abstract

Intraoperative hypothermia is a common issue in breast cancer patients with deep inferior epigastric perforator flap (DIEP), leading to complications. To construct an early warning model to investigate the risk factors of intraoperative hypothermia in patients undergoing breast reconstruction with DIEP. A total of 130 patients undergoing DIEP in a tertiary hospital in Henan from November 2020 to February 2025 were selected by convenience sampling method as the modeling group, and 67 patients in Shanghai were selected as the validation group. Relevant clinical data were collected through the hospital electronic medical record system. The univariate analysis and Logistic regression were used to analyze intraoperative hypothermia risk factors in patients undergoing DIEP. A nomogram prediction model was established accordingly. The incidence of intraoperative hypothermia in patients undergoing DIEP in the modeling group was 50.77%. The results of Logistic regression analysis showed that BMI ≥ 23.41 (OR = 0.145, 95%CI: 0.051 ~ 0.414) and WBC ≥ 5.845 (OR = 0.068, 95%CI: 0.024 ~ 0.196) were protective factors of hypothermia in patients undergoing DIEP, which associated with 85.5% and 93.2% reduction in the odds of hypothermia. Preoperative chemotherapy (OR = 5.011, 95%CI: 1.779–14.111) was a risk factor for hypothermia. The results of risk prediction model show that, the area under the receiver operating characteristic of the subjects was 0.873 in the modeling group, the sensitivity was 0.742 and the specificity was 0.844. The area under the receiver operating characteristic was 0.802 in the validation group, the sensitivity was 0.765 and the specificity was 0.727. The constructed Nomogram model could effectively predict the risk of incident of intraoperative early hypothermia, which has a certain clinical value.