OBJECTIVES: Different risk models have been introduced and refined in the past in order to improve standards of care. However, the predictive power of any risk algorithms can decline over time due to changes in surgical practice and the population's risk profile. The present study aimed to develop and validate a risk model for predicting operative mortality in patients with ischaemic heart failure (HF) undergoing surgical ventricular reconstruction (SVR). METHODS: The study population included 525 patients with previous myocardial infarction and left ventricular remodelling referred to our centre for SVR. All patients underwent surgical reshaping; coronary artery bypass grafting was performed in 489 (93%) patients and mitral valve (MV) repair in 142 (27%). Operative mortality was defined as death within 30 days after surgery. All patients received an operative risk assessment using the logistic EuroSCORE and the ACEF score. RESULTS: Better accuracy was achieved by the ACEF score (0.771) compared with the EuroSCORE (0.747). On multivariable logistic regression analysis, forcing the ACEF score in the model, three additional factors remained as independent predictors of operative mortality: atrial fibrillation, NYHA Class 3-4 and MV surgery (odds ratio 2.2, 2.6 and 2.1, respectively) and were computed in the ACEF-SVR. The ACEF-SVR score demonstrated an improved accuracy in respect of the ACEF score (from 0.771 to 0.792) and a better calibration (Hosmer-Lemeshow χ2 of 5.40, P = 0.714). CONCLUSIONS: The ACEF-SVR score, starting from a simplified model of risk enabled improvement in the accuracy and calibration of the model, tailoring the risk to a specific population of patients with HF undergoing a specific surgical procedure.
- Heart failure
- Operative mortality
- Risk stratification
- Surgical ventricular reconstruction
ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine
- Pulmonary and Respiratory Medicine