Reply to Letters Regarding Article, “Risk of Assessing Mortality Risk in Elective Cardiac Operations: Age, Creatinine, Ejection Fraction, and the Law of Parsimony”

Abstract

We thank Dr Lown et al and Dr Miceli et al for their comments about our article. 1 They raise several different and interesting points.It is of course possible that the selection of a limited number of variables for the risk model may better benefit from other more sophisticated statistical approaches. However, even if our model is apparently simplistic, it seems to work better than other complex models. We agree that an area under curve value of 0.744 is probably inadequate for clinical purposes, but this is the value reached by the widely used EuroSCORE in many clinical settings. 2 Actually, in the validation series, the area under curve value of the ACEF score (age, creatinine, ejection fraction) was higher than 0.8. 2 As stated in our article, it is a matter of terminology. We could say that the ACEF and the EuroSCORE are equally good or equally bad models. To answer the authors' question, we did sensitivity analyses in a subgroup of patients at low, medium, and high risk, and the worst accuracy was achieved in the high-risk patients (EuroSCORE Ͼ5). However, it should be considered that the ACEF is built for elective patients. When addressing the whole range of cardiac surgery population, more variables are needed to improve the accuracy of the model, up to 5 for medium-risk patients and even 12 in high-risk patients. 2 Dichotomization of continuous variables is always arbitrary in statistics but is a common practice in the development of risk scores. The important point is to dichotomise according to a method that may guarantee the best specificity and sensitivity of the identified cutoff value. We did dichotomise the serum creatinine value (as in the great majority of the existing scores) using the sensitivity and specificity values of the receiver operating characteristics curve coordinates and the Youden index. We agree that every kind of preoperative renal function impairment may strongly affect the operative mortality, and we cannot exclude that using serum creatinine as a continuous variable (as we did for age and ejection fraction) may improve the accuracy of the model, however at the expenses of more complex calculations.We agree with Lown et al about the limitations of area under curve-based systems and the risk of overfitted models, availability of data, and subjectivity, and these last reasons led us to propose a parsimonious model. Conversely, we are not sure that simple models may be more adequate for acute settings and complex models for elective settings. Actually, our experience is that when acute risk conditions intervene, more factors are needed to stratify the risk. 2 It was demonstrated that when severe acute conditions are present, the current scores are inadequate to stratify mortality risk. 3 When developing this model, we considered many potential factors that could be independently associated with operative mortality after cardiac surgery. Among these factors are those mentioned by Miceli et al (gender, chronic obstructive pulmonary disease, operations other than isolated coronary a...

Comparison of the EuroSCORE and Cardiac Anesthesia Risk Evaluation (CARE) score for risk-adjusted mortality analysis in cardiac surgery

“…It was also found that mortality prediction with only five of the EuroSCORE variables (age, left-ventricular ejection fraction, serum creatinine, emergency operation, and non-isolated coronary operation) provides the same level of discrimination and better calibration than with the 17-risk factor model [15]. Those results are supported by other studies which also showed that risk models with a limited number of variables provide accurate and reproducible risk predictions in cardiac surgery [8,9,18]. The good predictive performance of the CARE score in this study represents additional evidence supporting those findings.…”

Surgical Ventricular Restoration: Is There Any Difference in Outcome Between Anterior and Posterior Remodeling?

“…The primary end point of the present study was 30-day mortality from any cause. The operative risk assessment was performed using the age, creatinine, and ejection fraction (ACEF) score, based on 3 factors: age and ejection fraction (EF) as continuous variables and preoperative serum creatinine value as a binary variable [7]. The secondary end point was long-term freedom from all-cause mortality.…”

“…Both preoperative and postoperative echocardiographic examinations were performed in our department by the same cardiologist (SC). LV and right ventricular (RV) chamber dimensions and function were measured according to the recommendations for chamber quantification from the American Society of Echocardiography/European Association of Echocardiography guidelines [7].…”

A Global Risk Approach to Identify Patients With Left Main or 3-Vessel Disease Who Could Safely and Efficaciously Be Treated With Percutaneous Coronary Intervention

“…This analysis allowed for the assessment of the predictive ability of the Global Risk: 1) the HosmerLemeshow test for calibration-the assessment of the correctness of the prediction by the risk model, with poor fit indicated by a significant p value (Ͻ0.05); 2) receiver operator curves for discrimination (C-statistic)-the ability of the risk model to appropriately assign the correct risk prediction in patients who have the outcome, ranging from 0.50 (no discrimination) to 1.0 (perfect discrimination); 3) the Brier score-an overall risk model performance measure capturing both discrimination and calibration aspects of the risk model, ranging from 0 to 1, with a lower value (closer to 0) suggestive of a more predictive risk model (34 -36). Comparisons were made with other risk models, namely, the SXscore (2,4); age, creatinine, and ejection fraction/modified age, creatinine, and ejection fraction scores (37,38); the Clinical SXscore (39,40); and the additive/logistic EuroSCOREs (22,23)-a brief description of which is enclosed in the Online Appendix.…”