Morbidity and Mortality in Adult Congenital Heart Surgery: Physiologic Component Augments Risk Prediction

We sought to evaluate whether the anatomic and physiologic stratification system (ACAP score), released as part of the American College of Cardiology/American Heart Association updated guidelines for management of adult congenital heart disease (ACHD) in 2018, better estimated mortality and morbidity after cardiac operations for ACHD. The ACAP score was determined for 318 patients (age ≥18 years) with ACHD undergoing heart surgery at our institution between December 2001 and August 2019. The primary end point was perioperative mortality. The secondary aim was to evaluate the performance of the ACAP, The Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery (STAT) Congenital Heart Surgery Mortality Categories, and ACHS mortality scores/categories at predicting a composite adverse outcome of perioperative mortality, prolonged ventilation, and renal failure requiring replacement therapy. Logistic regression models were built to estimate mortality and the composite outcome using anatomic and physiologic components independently and together. Receiver operating characteristic curves were created, and area under the curves were compared using the Delong test. The median age was 37 years (interquartile range, 26.3-50.0 years). There were 9 perioperative mortalities (2.8%). With respect to perioperative mortality, the area under the curve using the anatomic component only was 0.74, which improved to 0.81 after including physiologic severity (P = .05). When physiologic severity was added to the model for the composite outcome, the discriminatory abilities of the ACHS mortality score and the STAT categories increased significantly to 0.83 (95% CI, 0.75-0.91; P = .02) and 0.82 (95% CI, 0.73-0.90; P = .04), comparable to the predictive power of ACAP. Physiologic severity augments ability to predict mortality and morbidity after cardiac surgery for ACHD. There is need for more robust ACHD-specific risk models.