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Construction and validation of a risk prediction model for intraoperative hypothermia in children undergoing thoracoscopic lobectomy.
Article in Science progress. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
To develop a predictive model to assess the risk of peri-operative hypothermia occurrence in children undergoing thoracoscopic lobectomy and validate its effectiveness. 172 children who underwent thoracoscopic lobectomy were randomly divided into a training set of 124 cases and a validation set of 48 cases in a 7:3 ratio. The study found a 33.1% incidence of intraoperative hypothermia (IPH) in children undergoing thoracoscopic lobectomy. Logistic regression analysis was performed using SPSS 26.0 to screen influencing factors, establish a risk prediction model, and draw the receiver-operating characteristic curve. Univariate analysis identified anesthesia-skin incision time, operating-room temperature, humidity, basal body temperature, end body temperature, and body temperature half an hour after anesthesia as influencing factors. Multivariate logistic regression revealed anesthesia-skin incision time (odds ratio (OR) = 1.595), operating-room humidity (OR = 4.094), and body temperature half an hour after anesthesia (OR = 112.595) as independent predictors. The nomogram model demonstrated an excellent discrimination with area under the curve (AUC) of 0.989 (95% confidence interval (CI): 0.976-1.000), maximum Youden index of 0.94, sensitivity of 1, specificity of 0.94, and cutoff value of 0.195. The Hosmer-Lemeshow test (
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