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Updated: Jun 3, 2026

Implantation of Total Artificial Heart in Congenital Heart Disease
Published on: July 18, 2014
The Aristotle Comprehensive Complexity score predicts mortality and morbidity after congenital heart surgery
Mirela Bojan1, Sébastien Gerelli, Simone Gioanni
1Department of Pediatric Cardiac Anesthesiology, Necker Hospital, Paris, France. mirela.bojan@nck.aphp.fr
Insights
The Aristotle Comprehensive Complexity (ACC) score effectively predicts 30-day mortality in congenital heart surgery patients. It also predicts intensive care unit (ICU) stay duration within the first postoperative week.
Area of Science:
- Cardiovascular Surgery
- Pediatric Cardiology
- Health Services Research
Background:
- The Aristotle Comprehensive Complexity (ACC) score was developed to adjust for complexity in congenital heart surgery outcomes.
- It combines the Aristotle Basic Complexity score with additional items for comorbidities and anatomical variability.
- Existing scores have limitations in predicting mortality and morbidity accurately.
Purpose of the Study:
- To evaluate the predictive ability of the ACC score for 30-day mortality after congenital heart surgery.
- To assess the ACC score's capability in predicting morbidity, measured by intensive care unit (ICU) length of stay.
- To validate the ACC score's performance in a real-world clinical setting.
Main Methods:
- Retrospective analysis of 1,454 patients undergoing congenital heart surgery.
- Modeling ACC score as a continuous variable, mortality as binary, and ICU stay as censored.
- Internal validation using bootstrapping, assessing performance with R-squared, calibration slope, and c-index.
Main Results:
- The ACC score demonstrated a strong association with 30-day mortality (c-index = 0.86).
- The score predicted length of ICU stay, particularly within the first postoperative week (R-squared = 0.094).
- Model performance metrics indicated good calibration and discrimination for mortality prediction.
Conclusions:
- The ACC score is a valuable tool for predicting 30-day mortality in patients undergoing congenital heart surgery.
- It adequately predicts intensive care unit length of stay during the initial postoperative period.
- The ACC score facilitates appropriate complexity adjustment in outcome analyses for 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.
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