Construction of risk prediction model for hypothermia during pancreaticoduodenectomy

To investigate the factors influencing hypothermia during pancreaticoduodenectomy and establish and verify a prediction model.

The clinical data of patients undergoing pancreaticoduodenectomy in Hunan People's Hospital between January 1, 2022 and October 15, 2022 were analysed. The patients were divided into a hypothermia group (n = 302) and a non-hypothermia group (n = 164) according to whether hypothermia occurred during surgery. A binary logistic regression model was used to analyse the independent risk factors for hypothermia in patients undergoing pancreaticoduodenectomy. A risk prediction model was established, and R software was used to plot a column graph. The predictive value of the model was evaluated using the receiver operating characteristic (ROC) curve.

Among the 466 patients undergoing pancreaticoduodenectomy, 302 (64.81 %) had hypothermia, including 154 men and 148 women, with a median age of 58.6 (38-86) years. The binary logistic regression analysis showed that low body mass index (BMI), room temperature at the time of entry, intraoperative flushing fluid volume and peritoneal flushing fluid temperature were independent risk factors for intraoperative hypothermia in patients undergoing pancreaticoduodenal surgery (P < 0.05). A multivariate logistic regression analysis (backward logistic regression) was used to establish the prediction model. The area under the ROC curve was 0.927, P ≤ 0.001, the sensitivity was 0.921 and the specificity was 0.848, indicating good differentiation by the prediction model.

The nomogram constructed using four independent risk factors: BMI, room temperature at the time of entry, intraoperative peritoneal flushing fluid volume and intraoperative peritoneal flushing fluid temperature, has good predictive efficacy and good clinical application value for predicting intraoperative hypothermia in patients undergoing pancreaticoduodenectomy.