4.6 Article

Outcome prediction in coronary artery bypass grafting and valve surgery in the Netherlands: development of the Amphiascore and its comparison with the Euroscore

Journal

EUROPEAN JOURNAL OF CARDIO-THORACIC SURGERY
Volume 24, Issue 5, Pages 741-749

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/S1010-7940(03)00471-8

Keywords

outcome prediction; in-hospital death; major adverse cardiac events; extended length of stay intensive care; Euroscore

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Objectives: (1) To define models that predict in-hospital death, major adverse cardiac events and extended intensive care unit duration for patients who underwent coronary artery bypass grafting (CABG), a heart valve operation or combined; and (2) to validate the Euroscore model in our population. Methods: Data of all 7282 patient who underwent a CABG and/or heart valve operation in 1997-2001 were prospectively collected. Three outcomes were examined: in-hospital death, major adverse cardiac events (MACE) and extended length of stay on intensive care (ELOS). Predicting models were made by multivariate logistic regression. The patient population was randomly divided in a derivation (two thirds) and a validation (one third) set. Area under the receiver operating characteristics curve (AUC) was used to study the discriminatory abilities of these models and the Euroscore. Hosmer-Lemeshow goodness-of-fit was used to study calibration of the predictive models. Results: 2.4% of the patients died in-hospital, 17% of the patients had a MACE and 14% had ELOS. The models for in-hospital mortality and ELOS had a good validation (AUC 0.84 and 0.79, respectively). The validation for MACE was moderate (receiver-operating characteristic, ROC 0.67). All models were well calibrated. The validation of the Euroscore was as good as our model for in-hospital mortality (ROC 0.84). Conclusions: The Amphia score performs as well as the Euroscore in discriminating patients with respect to in-hospital death. Our models for predicting major adverse cardiac events and extended length of stay on intensive care may be useful tools in categorising patients in various subgroups of risk for postoperative morbidity. (C) 2003 Elsevier B.V. All rights reserved.

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