Risk stratification in paediatric open-heart surgery

Objective: The aims of this study were to identify independent risk factors for mortality following paediatric open-heart surgery and to develop risk models for use in clinical audit based on identified risk factors. The study also tests the validity of the recently proposed Risk Adjustment in Congenital Heart Surgery (RACHS-1) method of risk stratification [J Thorac Cardiovasc Surg 123 (2002) 110] as applied to open-heart operations. Methods: A multiple logistic regression analysis was performed on all patients less than 18 years of age undergoing open-heart surgery at a single institution over a 3-year period. Preoperative and operative variables included for analysis were age at operation. weight. sex, American Society of Anaesthesiology (ASA) grade, RACHS-1 risk category, preoperative haemoglobin, bypass time, temperature. cross-clamp time, circulatory arrest time, blood transfusion on bypass and surgeon. The outcome measure was in-hospital death. Results: 1085 consecutive open-heart cases were identified. There were 51 in-hospital deaths (4.7%). Variables identified as being independently significant risk factors for in-hospital death were age (P = 0.0002), RACHS-1 risk category (P < 0.0001) and bypass time (P < 0.0001). Based on these three variables, a risk model was constructed to predict mortality. The area under the receiver-operating-characteristic (ROC) curve for this model was 0.86. A second model was constructed ignoring bypass time. In this model, the significance of the 'preoperative' risk factors was P = 0.0003 for age and P < 0.0001 for RACHS-1 risk category. The area under the ROC curve was 0.81 for the second model. Conclusions: This study identifies age at operation, RACHS-1 risk category and bypass time as highly significant risk factors for mortality after paediatric open-heart surgery. It validates the RACHS-1 risk stratification method as applied to the subset of open-heart surgery. whilst accepting the limitations of such a system. The risk models formulated permit risk prediction and allow for analysis of surgical results. Such risk-adjustment is important when assessing performance and comparing outcomes amongst individuals or institutions. (C) 2004 Elsevier B.V. All rights reserved.