Validation of EGSYS Score in Prediction of Cardiogenic Syncope

Introduction. Evaluation of Guidelines in Syncope Study (EGSYS) is designed to differentiate between cardiac and noncardiac causes of syncope. The present study aimed to evaluate the accuracy of this predictive model. Methods. In this prospective cross-sectional study, screening performance characteristics of EGSYS-U (univariate) and EGSYS-M (multivariate) in prediction of cardiac syncope were calculated for syncope patients who were referred to the emergency department (ED). Results. 198 patients with mean age of 59.26 ± 19.5 years were evaluated (62.3% male). 115 (58.4%) patients were diagnosed with cardiac syncope. Area under the ROC curve was 0.818 (95% CI: 0.75–0.87) for EGSYS-U and 0.805 (CI 95%: 0.74–0.86) for EGSYS-M (p = 0.53). Best cut-off point for both models was ≥3. Sensitivity and specificity were 86.08% (95% CI: 78.09–91.59) and 68.29% (95% CI: 56.97–77.86) for EGSYS-U and 91.30% (95% CI: 84.20–95.52) and 57.32% (95% CI: 45.92–68.02) for EGSYS-M, respectively. Conclusion. The results of this study demonstrated the acceptable accuracy of EGSYS score in predicting cardiogenic causes of syncope at the ≥3 cut-off point. It seems that using this model in daily practice can help physicians select at risk patients and properly triage them.