The ability of the RACHS-1 score to predict in-hospital mortality and morbidity in pediatric patients undergoing congenital heart surgery

Abstract

Background: Advancements in pediatric cardiac care have improved survival outcomes. This study aims to evaluate the predictive ability of the Risk Adjustment for Congenital Heart Surgery Score (RACHS-1) for in-hospital mortality and morbidity in pediatric cardiac surgery patients and to analyze the relationships among procedural complexity, age groups, and clinical outcomes. A retrospective cohort study was conducted at a single tertiary referral center from April 2011 to April 2014; 955 pediatric patients were included. Data were collected on demographic information, surgical procedures, Risk adjustment score, mortality, complications, and Intensive care unit length of stay. Results: The study included 955 patients (30% in-hospital mortality). Higher Risk Adjustment scores were correlated with increased mortality. The predictive ability of the score for mortality was moderate, with area under the receiver operator characteristic curve (ROC) of 61%. The predicted mortality rate increased according to the category in all age groups. The score had a greater predictive ability for neonates and children rather than for infants (aucROC = 64%, 63.9%, and 60%, respectively). Morbidity was noted in 57.5% of patients, with significant associations between higher score categories and complications. The median duration of the Intensive care unit stay was 5 days. A positive correlation was identified between the score and the duration of the stay (p value = 0.002), particularly among infants (p value = 0.029) and children (p value = 0.017), whereas no significant correlation was detected in neonates (p value = 0.939). Conclusions: RACHS-1 score is a moderate predictor for in-hospital mortality and morbidity in pediatric cardiac surgery patients. The score performance varied according to the age group. This highlights the need for enhanced risk stratification tools that incorporate patient-specific variables and socioeconomic factors. Understanding the limitations of the score can guide hospital administrators in optimizing resource allocation. This could lead to more tailored surgical and postoperative care strategies, ultimately improving patient outcomes. Future studies could explore the integration of additional predictive factors, such as genetic predispositions, comorbidities, and social determinants of health, into existing scoring systems.