Reliability of new scores in predicting perioperative mortality after isolated aortic valve surgery: a comparison with the society of thoracic surgeons score and logistic EuroSCORE.

BACKGROUND: There is still a wide debate concerning the performance of commonly used risk prediction models in assessing the risk of patients undergoing isolated aortic valve surgery. This study was designed to compare the performances of European System for Cardiac Operative Risk Evaluation (EuroSCORE) II and age, creatinine, and ejection fraction (ACEF) score with those of The Society of Thoracic Surgeons (STS) score and logistic EuroSCORE in patients undergoing isolated aortic valve surgery. METHODS: Data on 1,758 consecutive patients who underwent isolated aortic valve replacement in a 6-year period were retrieved from 3 prospective institutional databases. Discriminatory power was assessed using the c-index. Calibration was evaluated with calibration curves and associated statistics. RESULTS: In-hospital mortality rate was 1.4%. The discriminatory power was similar in all algorithms (area under the curve 0.80, 95% confidence interval [CI] 0.72 to 0.88 for logistic EuroSCORE; 0.81, 95% CI 0.73 to -0.88 for EuroSCORE II; 0.78, 95% CI 0.68 to 0.88 for ACEF; 0.85, 95% CI 0.78-0.93 for STS score) and not significantly different (p values > 0.05 for all tests). The EuroSCORE II had a better calibration, being the only score with nonsignificant associated statistics (unreliability test, Hosmer-Lemeshow test, and Spiegelhalter Z-test for calibration accuracy). Nonetheless, EuroSCORE II calibration plot highlighted a trend over under-prediction. CONCLUSIONS: The EuroSCORE II is a good predictor of perioperative mortality in isolated aortic valve surgery, with lower discrimination if compared with STS and a better calibration when compared with logistic EuroSCORE, ACEF, and STS scores. Its performance is optimal in the lowest tertile of patients, whereas it under-predicts mortality afterward. None of these algorithms seems suitable for risk estimation in mid and high-risk patients that are the ones who might benefit most from transcatheter procedures.

An original model to predict Intensive Care Unit length-of stay after cardiac surgery in a competing risk framework.

BACKGROUND: The aim of the study is to design a specific Intensive Care Unit length-of-stay risk model based on the preoperative factors and surgeries utilizing modeling strategies for time-to-event data in a prospective observational clinical study. METHODS: From January 2004 to April 2011 data on 3861 consecutive heart surgery patients were prospectively collected. ICU length of stay was analyzed as a time-to-event variable in a competing risk framework with death as competing risk. RESULTS: The median ICU-LOS was one day. All factors considered but gender was included in the multivariable modeling. In the final model, factors that mostly affected time-to-discharge from ICU were critical preoperative state (Relative Risk 0.41; 95% Confidence Interval: 0.29-0.58), emergency (0.41; 0.32-0.53), poor left ventricular dysfunction (0.50; 0.44-0.57) and serum creatinine>200 µmol/L (0.54; 0.46-0.65). Most of the predictors had a time-dependent effect that decreased in the first fifteen days and was constant thereafter. After the plateau, the risk profile was changed as most of the factors were no longer significant, Conversely, the time-to-ICU death model included only two variables, critical perioperative state and serum creatinine>200 µmol/L, with a constant RR of 9.1 and 3.37 respectively. CONCLUSIONS: ICU-LOS can be predicted by preoperative data and type of surgeries. The derived ICU-LOS prediction model is dynamic and most predictors have an effect that decreases with time. The algorithm can preoperatively predict ICU-LOS curves and could have a major role in the decision making-behavior of clinicians, resources' allocation and maximization of care for high-risk patients.

Hemoglobin trends in isolated coronary artery bypass grafting performed off-pump and with standard and mini circuits.

The comparison of hemodilution at the end of surgery is of limited use as it represents only a snapshot of a dynamic phenomenon. This study was undertaken to compare the perioperative hemoglobin curves of isolated coronary artery bypass grafting performed with minimized extracorporeal circulation, traditional cardiopulmonary bypass, and off-pump technique. The propensity score method was used to select three groups of patients, homogenous regarding preoperative and operative data, who underwent isolated coronary artery bypass grafting. A generalized linear mixed model was used for estimating differences in perioperative hemoglobin trends among groups. The three groups were each composed of 50 patients with no differences in demographic data, preoperative risk profile, preoperative hemoglobin, or type of surgery. There was no significant difference in major postoperative complications. The pattern of the hemodilution curves was similar in patients operated with mini-circuit and off-pump technique (P > 005). Mini-circuit led to a 3.1 ± 11.9% hemoglobin reduction, which was similar to the off-pump group (1.6 ± 8.9%, P = 0.99 at ANOVA) and significantly different from the standard extracorporeal circuit group (16.0 ± 10.3%, P < 0.001 at ANOVA). The generalized linear mixed model determined that the standard circuit was the only independent predictor for increased hemodilution. Its effect on hemodilution was time-dependent and the slope of the hemoglobin curve was more pronounced between systemic heparinization and the end of surgery. Perioperative hemoglobin trends of patients who underwent myocardial revascularization with mini-circuit were similar to those of off-pump surgery and significantly less pronounced than those of standard extracorporeal circulation.

Aortic valve replacement: reliability of EuroSCORE in predicting early outcomes.

EuroSCORE algorithms were developed to predict perioperative mortality in cardiac surgery. This study was designed to evaluate the reliability of EuroSCORE algorithms and to analyze the predicting role of the scoring system's factors on patients that undergo isolate AVR. 339 patients underwent aortic valve replacement. Data collection was prospective and the logistic and additive EuroSCORE algorithms were calculated according to published guidelines. The observed-over-expected mortality ratio was 0.096. In the ROC curve analysis, the asymptotic significance was greater than 0.05. On multivariate analysis, only critical preoperative state remained significant independent predictor of in-hospital mortality (Odds Ratio 1.6, CI 1.2-2.1). These outcomes suggest that EuroSCORE models may fail in predicting hospital mortality in subsets of cardiac surgery patients and dedicated risk models for isolate aortic valvular surgery may be useful to provide more precise estimates of hospital mortality.