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Reliability of EuroSCORE II on Prediction of Thirty-Day Mortality and Long-Term Results in Patients Treated with Sutureless Valves.

Lorenzo Di BaccoMichele D'AlonzoMassimo BaudoAndrea MontisciMarco Di EusanioThierry FolliguetMarco SolinasAntonio MiceliTheodor FischleinFabrizio RosatiClaudio Muneretto
Published in: Journal of clinical medicine (2024)
Background: EuroSCORE II (ES2) is a reliable tool for preoperative cardiac surgery mortality risk prediction; however, a patient's age, a surgical procedure's weight and the new devices available may cause its accuracy to drift. We sought to investigate ES2 performance related to the surgical risk and late mortality estimation in patients who underwent aortic valve replacement (AVR) with sutureless valves. Methods : Between 2012 and 2021, a total of 1126 patients with isolated aortic stenosis who underwent surgical AVR by means of sutureless valves were retrospectively collected from six European centers. Patients were stratified into three groups according to the EuroSCORE II risk classes (ES2 < 4%, ES2 4-8% and ES2 > 8%). The accuracy of ES2 in estimating mortality risk was assessed using the standardized mortality ratio (O/E ratio), ROC curves (AUC) and Hosmer-Lemeshow (HL) test for goodness-of-fit. Results : The overall observed mortality was 3.0% (predicted mortality ES2: 5.39%) with an observed/expected (O/E) ratio of 0.64 (confidential interval (CI): 0.49-0.89). In our population, ES2 showed a moderate discriminating power (AUC 0.65, 95%CI 0.56-0.72, p < 0.001; HL p = 0.798). Good accuracy was found in patients with ES2 < 4% (O/E ratio 0.54, 95%CI 0.23-1.20, AUC 0.75, p < 0.001, HL p = 0.999) and for patients with an age < 75 years (O/E ratio 0.98, 95%CI 0.45-1.96, AUC 0.76, p = 0.004, HL p = 0.762). Moderate discrimination was observed for ES2 in the estimation of long-term risk of mortality (AUC 0.64, 95%CI: 0.60-0.68, p < 0.001). Conclusions : EuroSCORE II showed good accuracy in patients with an age < 75 years and patients with ES2 < 4%, while overestimating risk in the other subgroups. A recalibration of the model should be taken into account based on the complexity of actual patients and impact of new technologies.
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