急诊老年创伤病人术后亚谵妄综合征风险预测模型构建及验证OA

Objective:To construct and validate the prediction model of subsyndromal delirium(SSD)in elderly emergency trauma patients after surgery.Methods:A retrospective analysis was conducted on the clinical data of 906 elderly trauma patients admitted to the hospital from June 2018 to October 2024.The patients were divided into a modeling group(n=635)and a validation group(n=271)at a ratio of 7∶3.In the modeling group,patients were further classified into SSD and non-SSD groups based on whether SSD occurred after surgery.The influencing factors were analyzed using the least absolute shrinkage and selection operator(LASSO)and multivariate Logistic regression.The Nomogram model for predicting the risk of SSD in elderly trauma patients in the emergency department was constructed using R 3.6.3 software and the rms package.The model's discrimination,calibration,and clinical applicability were evaluated using the area under the receiver operating characteristic(ROC)area under the curve(AUC),calibration curve,and decision curve analysis(DCA).Results:Among the 635 patients in the modeling group,204 patients developed SSD,with an incidence of 32.13%(204/635).The results of multivariate Logistic regression analysis showed that age,history of alcohol consumption,Injury Severity Score(ISS),Acute Physiology and Chronic Health Evaluation Ⅱ(APACHE Ⅱ)score,mechanical ventilation,blood transfusion,length of stay in the intensive care unit(ICU),postoperative Numerical Rating Scale(NRS)score for pain,and limb restraint were all influencing factors for the occurrence of SSD in elderly trauma patients after emergency surgery(P<0.05).The AUC of the Nomogram model established based on the results was 0.877[95%CI(0.844,0.909)]in the modeling group and 0.836[95%CI(0.801,0.871)]in the validation group.The ROC curve,calibration curve,and DCA results indicated that the Nomogram model had high discrimination and consistency,and good clinical applicability.Conclusions:The risk prediction model for postoperative SSD in elderly emergency trauma patients constructed based on the influencing factors screened by LASSO regression has good discrimination and clinical applicability.