[Analysis of in-hospital mortality from coronary artery bypass grafting surgery]

Mortality risk prediction in high-risk patients undergoing coronary artery bypass grafting: Are traditional risk scores accurate?

BACKGROUND

The performance of traditional scores is significantly limited to predict mortality in high-risk cardiac surgery. The aim of this study was to compare the performance of STS, ESII and HiriSCORE models in predicting mortality in high-risk patients undergoing CABG.

METHODS

Cross-sectional analysis in the international prospective database of high-risk patients: HiriSCORE project. We evaluated 248 patients with STS or ESII (5-10%) undergoing CABG in 8 hospitals in Brazil and China. The main outcome was mortality, defined as all deaths occurred during the hospitalization in which the operation was performed, even after 30 days. Five variables were selected as predictors of mortality in this cohort of patients. The model's performance was evaluated through the calibration-in-the-large and the receiver operating curve (ROC) tests.

RESULTS

The mean age was 69.90±9.45, with 52.02% being female, 25% of the patients were on New York Heart Association (NYHA) class IV and 49.6% had Canadian Cardiovascular Society (CCS) class 4 angina, and 85.5% had urgency or emergency status. The mortality observed in the sample was 13.31%. The HiriSCORE model showed better calibration (15.0%) compared to ESII (6.6%) and the STS model (2.0%). In the ROC curve, the HiriSCORE model showed better accuracy (ROC = 0.74) than the traditional models STS (ROC = 0.67) and ESII (ROC = 0.50).

CONCLUSION

Traditional models were inadequate to predict mortality of high-risk patients undergoing CABG. However, the HiriSCORE model was simple and accurate to predict mortality in high-risk patients.

In-hospital mortality rates after CABG by autonomous regions in Spain

PURPOSE

The paper's purpose is twofold: to provide a predictive model for estimating in-hospital mortality rates after coronary artery bypass grafting (CABG) in Spanish autonomous regions (AR) after adjusting relevant factors; and to determine whether there is a difference between expected and observed mortality rates.

DESIGN/METHODOLOGY/APPROACH

All patients registered in a minimum basic data set (MSBD) undergoing CABG between 2000 and 2004 were selected. After bivariate analysis to explore associations between in-hospital death and other variables, a multivariate analysis using logistic regression was conducted. The predictive model was evaluated using calibration and discrimination techniques. Standardized mortality ratios by AR were calculated.

FINDINGS

The expected Spanish in-hospital mortality rate after CABG was 7.68 and the observed rate was 7.69 deaths per 100 operations. Discrimination obtained with the model resulted in an area under the curve of 0.70 (95 per cent CI, 0.69-0.71). When each AR's mortality rate is calculated and compared with the observed rate, some ARs present an observed mortality rate higher or lower than the expected rate according to adjusted variables in the model.

RESEARCH LIMITATIONS/IMPLICATIONS

The MSBD registry does not contain patients' critical data, such as arterial damage severity, or in which hospital procedures were performed.

PRACTICAL IMPLICATIONS

There are factors related to individual patient variation, financial resources or healthcare quality in different ARs, which should be investigated in follow-up studies.

ORIGINALITY/VALUE

The paper shows that, although the global expected mortality rate is almost the same as the observed Spanish mortality rate, this similarity disappears when AR rates are compared.