Logistics regression analysis and prediction modelconstruction of hypothermia occurrence in general surgery
Objective To explore the risk factors of intraoperative hypothermia in generalsurgery,construc-tand verify the risk prediction model of intraoperative hypothermia.Methods A total of 117 patients un-derwentgeneral surgery in the hospital were enrolled as the observation objects from December 2020 to De-cember 2022.The clinical data of the patients were collected.According to presence or absence of intraop-erative hypothermia,thepatients were divided into hypothermia group(group A)and non-hypothermia group(group B).The risk factors of intraoperative hypothermia were analyzed byLogistic regression anal-ysis,and the risk prediction model was constructed.The predictive efficiency of the model was detected by receiver operating characteristic(ROC)curves.Results Among the 117 patients,there were 31(26.49％)cases with hypothermia and 86(73.50％)cases without.There were significant differences in age,body mass index,ASA grading,modus operandi,intraoperative infusion volume,operating room temperature and operation time between the 2 groups(P＜0.05).The results of Logistic regression analysis showed that age≥65 years,intraoperative infusion volume≥1 000 mL,anesthesia time≥4 h and operating room temperature＜23℃ were risk factors of hypothermia in general surgery(P＜0.05).The prediction model was as follow:P=1/[1+e(-1.020+0.874 ×(age)+1.114×(intraoperative infusion volume)+1.556 ×(operating room temperature)+1.453 ×(anesthesia time)]The area under the curve(AUC)of the prediction model by ROC curves was 0.754(P＜0.05).The results of Hosmer-Lemeshow goodness of fit test were as follows:x2=1.001,P=0.998.Conclusion Age of patients,intraoperative in-fusion volume,anesthesia time and operating room temperature are independent risk factors of hypother-mia in general surgery.Logistic risk prediction model has good fitting degree and high predictive value.
surgeryhypothermiaLogistics regression analysisconstruction of prediction model
万方数据
维普
