BACKGROUND: The Aristotle Comprehensive Complexity (ACC) score has been proposed for complexity adjustment in the analysis of outcome after congenital heart surgery. The score is the sum of the Aristotle Basic Complexity score, largely used but poorly related to mortality and morbidity, and of the Comprehensive Complexity items accounting for comorbidities and procedure-specific and anatomic variability. This study aims to demonstrate the ability of the ACC score to predict 30-day mortality and morbidity assessed by the length of the intensive care unit (ICU) stay. METHODS: We retrospectively enrolled patients undergoing congenital heart surgery in our institution. We modeled the ACC score as a continuous variable, mortality as a binary variable, and length of ICU stay as a censored variable. For each mortality and morbidity model we performed internal validation by bootstrapping and assessed overall performance by R(2), calibration by the calibration slope, and discrimination by the c index. RESULTS: Among all 1,454 patients enrolled, 30-day mortality rate was 3.4% and median length of ICU stay was 3 days. The ACC score strongly related to mortality, but related to length of ICU stay only during the first postoperative week. For the mortality model, R(2) = 0.24, calibration slope = 0.98, c index = 0.86, and 95% confidence interval was 0.82 to 0.91. For the morbidity model, R(2) = 0.094, calibration slope = 0.94, c index = 0.64, and 95% confidence interval was 0.62 to 0.66. CONCLUSIONS: The ACC score predicts 30-day mortality and length of ICU stay during the first postoperative week. The score is an adequate tool for complexity adjustment in the analysis of outcome after congenital heart surgery.
BACKGROUND: The Aristotle Comprehensive Complexity (ACC) score has been proposed for complexity adjustment in the analysis of outcome after congenital heart surgery. The score is the sum of the Aristotle Basic Complexity score, largely used but poorly related to mortality and morbidity, and of the Comprehensive Complexity items accounting for comorbidities and procedure-specific and anatomic variability. This study aims to demonstrate the ability of the ACC score to predict 30-day mortality and morbidity assessed by the length of the intensive care unit (ICU) stay. METHODS: We retrospectively enrolled patients undergoing congenital heart surgery in our institution. We modeled the ACC score as a continuous variable, mortality as a binary variable, and length of ICU stay as a censored variable. For each mortality and morbidity model we performed internal validation by bootstrapping and assessed overall performance by R(2), calibration by the calibration slope, and discrimination by the c index. RESULTS: Among all 1,454 patients enrolled, 30-day mortality rate was 3.4% and median length of ICU stay was 3 days. The ACC score strongly related to mortality, but related to length of ICU stay only during the first postoperative week. For the mortality model, R(2) = 0.24, calibration slope = 0.98, c index = 0.86, and 95% confidence interval was 0.82 to 0.91. For the morbidity model, R(2) = 0.094, calibration slope = 0.94, c index = 0.64, and 95% confidence interval was 0.62 to 0.66. CONCLUSIONS: The ACC score predicts 30-day mortality and length of ICU stay during the first postoperative week. The score is an adequate tool for complexity adjustment in the analysis of outcome after congenital heart surgery.
Authors: Gerdien A Zeilmaker-Roest; Joost van Rosmalen; Monique van Dijk; Erik Koomen; Nicolaas J G Jansen; Martin C J Kneyber; Sofie Maebe; Greet van den Berghe; Dirk Vlasselaers; Ad J J C Bogers; Dick Tibboel; Enno D Wildschut Journal: Trials Date: 2018-06-13 Impact factor: 2.279