小儿先天性心脏病术后心脏骤停预测模型的构建OA

Objective To analyze the influencing factors for postoperative cardiac arrest in children with congenital heart disease based on the baseline clinical data and ultrasomics.Methods A total of 993 pediatric patients with congenital heart disease who were admitted to our hospital from February 2020 to February 2025 were enrolled.They were categorized into the event group and the non-event group according to the occurrence of cardiac arrest within 30 days after surgery.Variables were initially screened using LASSO regression model,and subsequently analyzed using multivariate Logistic regression to identify the independent risk factors.A corresponding risk prediction model was established,and the model performance was validated using the receiver operating characteristic(ROC)curve and calibration curve.Results The incidence of cardiac arrest within 30 days after surgery was 5.14%.Five core variables were screened out by the LASSO regression model.Logistic regression analysis identified that risk adjustment for congenital heart surgery 1st version(RACHS-1)category≥4,longer cardiopulmonary bypass(CPB)time,greater early diastolic mitral inflow velocity/early diastolic mitral annular velocity(E/e'),and higher tricuspid regurgitation peak velocity(TR Vmax)were the independent risk factors for postoperative cardiac arrest(P<0.05),while a greater absolute value of left ventricular global longitudinal strain(LVGLS)was identified as a protective factor(P<0.05).A corresponding risk prediction model was established.The area under the curve(AUC)of the model for predicting postoperative cardiac arrest was 0.928,with a sensitivity of 92.16% and a specificity of 84.39%.The Hosmer-Lemeshow test indicated no significant difference between the predicted probability and actual probability for cardiac arrest after pediatric congenital heart disease surgery(χ²=0.415,P=0.296).Conclusion RACHS-1 category≥4,longer CPB time,a greater E/e'ratio,and a higher TR Vmax are the risk factors for cardiac arrest after pediatric congenital heart disease surgery,while a greater absolute value of LVGLS is a protective factor.The prediction model constructed by integrating the above baseline data and ultrasomics indicators demonstrates good performance.