Prognostic Model to Predict Postoperative Adverse Events in Pediatric Patients With Aortic Coarctation - Gu, Yan; Li, Qianqian; Lin, Rui; Jiang, Wenxi; Wang, Xue; Zhou, Gengxu; Su, Junwu; Fan, Xiangming; Gao, Pei; Jin, Mei; Wang, Yuan; Du, Jie (Frontiers in Cardiovascular Medicine, 2021)
Background: Postoperative adverse events remain excessively high in surgical patients with coarctation of aorta (CoA). Currently, there is no generally accepted strategy to predict these patients’ individual outcomes. Objective: This study aimed to develop a risk model for the prediction of postoperative risk in pediatric patients with CoA. Methods: In total, 514 patients with CoA at two centers were enrolled. Using daily clinical practice data, we developed a model to predict 30-day or in-hospital adverse events after the operation. The least absolute shrinkage and selection operator approach was applied to select predictor variables and logistic regression was used to develop the model. Model performance was estimated using the receiver-operating characteristic curve, the Hosmer–Lemeshow test and the calibration plot. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) compared with existing risk strategies were assessed. Results: Postoperative adverse events occurred in 195 (37.9%) patients in the overall population. Nine predictive variables were identified, including incision of left thoracotomy, preoperative ventilation, concomitant ventricular septal defect, preoperative cardiac dysfunction, severe pulmonary hypertension, height, weight-for-age z-score, left ventricular ejection fraction and left ventricular posterior wall thickness. A multivariable logistic model (area under the curve = 0.8195 [95% CI: 0.7514–0.8876]) with adequate calibration was developed. Model performance was significantly improved compared with the existing Aristotle Basic Complexity (ABC) score (NR I = 47.3%, IDI = 11.5%) and the Risk Adjustment for Congenital Heart Surgery (RACHS-1) (NRI = 75.0%, IDI = 14.9%) in the validation set. Conclusion: Using daily clinical variables, we generated and validated an easy-to-apply postoperative risk model for patients with CoA. This model exhibited a remarkable improvement over the ABC score and the RACHS-1 method.