Comparative study of the Aristotle Comprehensive Complexity and the Risk Adjustment in Congenital Heart Surgery scores.

Abstract

The Aristotle Comprehensive Complexity (ACC) and the Risk Adjustment in Congenital Heart Surgery (RACHS-1) scores have been proposed for complexity adjustment in the analysis of outcome after congenital heart surgery. Previous studies found RACHS-1 to be a better predictor of outcome than the Aristotle Basic Complexity score. We compared the ability to predict operative mortality and morbidity between ACC, the latest update of the Aristotle method and RACHS-1. Morbidity was assessed by length of intensive care unit stay. We retrospectively enrolled patients undergoing congenital heart surgery. We modeled each score as a continuous variable, mortality as a binary variable, and length of stay as a censored variable. We compared performance between mortality and morbidity models using likelihood ratio tests for nested models and paired concordance statistics. Among all 1,384 patients enrolled, 30-day mortality rate was 3.5% and median length of intensive care unit stay was 3 days. Both scores strongly related to mortality, but ACC made better prediction than RACHS-1; c-indexes 0.87 (0.84, 0.91) vs 0.75 (0.65, 0.82). Both scores related to overall length of stay only during the first postoperative week, but ACC made better predictions than RACHS-1; U statistic=0.22, p<0.001. No significant difference was noted after adjusting RACHS-1 models on age, prematurity, and major extracardiac abnormalities. The ACC was a better predictor of operative mortality and length of intensive care unit stay than RACHS-1. In order to achieve similar performance, regression models including RACHS-1 need to be further adjusted on age, prematurity, and major extracardiac abnormalities.