Construction and validation of a risk warning model for intraoperative hypothermia in patients undergoing thoracoscopic radical resection of lung cancer
Objective To explore the influencing factors of intraoperative hypothermia in patients undergoing thoracoscopic radical resection of lung cancer,and to establish a column chart based on the risk of intraoperative hypothermia in patients undergoing thoracoscopic radical resection of lung cancer and verify it.Methods A retrospective selection was conducted on 189 patients who underwent thoracoscopic radical resection of lung cancer in our hospital from December 2022 to December 2023.Patients were divided into a hypothermia group(85 cases)and a non-hypothermia group(104 cases)based on whether they had hypothermia during surgery.The multiple logistic regression method was used to analyze the risk factors of intraoperative hypothermia in patients undergoing thoracoscopic radical resection of lung cancer,constructing a risk map of intraoperative hypothermia and conducting validation.Results Through multiple logistic regression analysis,the results showed that older patients,High body mass index(BMI),anesthesia time＞2.5 hours,surgery time＞2 hours,total infusion volume＞1 600 ml,and low entry temperature were all independent risk factors for intraoperative hypothermia in patients undergoing thoracoscopic radical resection of lung cancer(P＜0.05).Verify the column chart,the area under the receiver operator characteristic curve(ROC)(95％CI)was 0.885(0.839,0.931),with good discrimination.The optimal critical value of the model was 0.638,sensitivity was 85.9％,and specificity was 77.9％.The theoretical and actual values of the calibration curve had good consistency.Conclusion The column chart of intraoperative hypothermia risk in thoracoscopic radical lung cancer patients has good predictive value,and medical staff can develop targeted intervention measures based on the intraoperative hypothermia risk prediction model of thoracoscopic radical lung cancer patients.
ThoracoscopyLung neoplasmsHypothermiaWarning model
万方数据
维普
