RESUMO
Background: Current guidelines recommend that glycoprotein IIb/IIIa inhibitor (GPI) and manual aspiration thrombectomy should not be routinely used in patients with ST-segment elevation myocardial infarction (STEMI) treated by primary percutaneous coronary intervention (pPCI), although there is a lack of dedicated studies. The aim of this study was to examine the impact of combined usage of a potent P2Y12 inhibitor, GPI, and manual aspiration thrombectomy on long-term survival after STEMI. Methods: All STEMI patients treated by pPCI in a tertiary center who have been included prospectively in the local PCI registry between January 2016 and December 2022 were analyzed in this study. Patients were excluded if they required oral anticoagulation or bridging between clopidogrel or ticagrelor during hospitalization. Results: A total of 1,210 patients were included in the present study, with a median follow-up of 2.78 (1.00-4.88) years. Ticagrelor significantly reduced all-cause and cardiovascular-cause mortality [HR = 0.27 (0.21-0.34), p < 0.0001 and HR = 0.23 (0.17-0.30), p < 0.0001, respectively]. Eptifibatide significantly reduced all-cause and cardiovascular-cause mortality [HR = 0.72 (0.57-0.92), p = 0.002, and HR = 0.68 (0.52-0.89), p = 0.001, respectively]. Manual thrombus aspiration had no significant effect on both all-cause and cardiovascular-cause mortality. In multivariate Cox regression, all-cause mortality was reduced by ticagrelor, while eptifibatide or manual thrombus aspiration had no significant effect. However, cardiovascular-cause mortality was reduced by both ticagrelor and eptifibatide, while manual thrombus aspiration had no significant effect. Conclusion: Ticagrelor consistently reduced cardiovascular and all-cause mortality, while eptifibatide reduced only cardiovascular mortality. Manual thrombus aspiration provided no long-term benefit. Our findings support the current guideline recommendation that GPI and manual aspiration thrombectomy should not be routinely used in treatment of STEMI with pPCI.
RESUMO
BACKGROUND AND AIMS: Machine learning (ML) models have been proposed as a prognostic clinical tool and superiority over clinical risk scores is yet to be established. Our aim was to analyse the performance of predicting 3-year all-cause- and cardiovascular cause mortality using ML techniques and compare it with clinical scores in a percutaneous coronary intervention (PCI) population. METHODS: An all-comers patient population treated by PCI in a tertiary cardiovascular centre that have been included prospectively in the local registry between January 2016-December 2017 was analysed. The ML model was trained to predict 3-year mortality and prediction performance was compared with that of GRACE, ACEF, SYNTAX II 2020 and TIMI scores. RESULTS: A total number of 2242 patients were included with 12.1% and 14.9% 3-year cardiovascular and -all-cause mortality, respectively. The area under receiver operator characteristic curve for the ML model was higher than that of GRACE, ACEF, SYNTAX II and TIMI scores: 0.886 vs. 0.797, 0.792, 0.757 and 0.696 for 3-year cardiovascular- and 0.854 vs. 0.762, 0.764, 0.730 and 0.691 for 3-year all-cause mortality prediction, respectively (all p ≤ 0.001). Similarly, the area under precision-recall curve for the ML model was higher than that of GRACE, ACEF, SYNTAX II and TIMI scores: 0.729 vs. 0.474, 0.469, 0.365 and 0.389 for 3-year cardiovascular- and 0.718 vs. 0.483, 0.466, 0.388 and 0.395 for 3-year all-cause mortality prediction, respectively (all p ≤ 0.001). CONCLUSION: The ML model was superior in predicting 3-year cardiovascular- and all-cause mortality when compared to clinical scores in a prospective PCI registry.
