Prognosis Impact and Prediction of Trans-Radial Access Failure in Patients With STEMI, A Nationwide Observational Study

Abstract

Trans-radial access (TRA) is the primary arterial approach for percutaneous coronary intervention (PCI) in ST-elevation myocardial infarction (STEMI). However, occasionally, a crossover to trans-femoral access is necessary due to unsuccessful TRA. The impact of failed TRA on the prognosis in STEMI patients and the utility of predictive models for TRA failure remains uncertain. Data from the Hungarian Myocardial Infarction Registry (January 2014 - December 2020) were analyzed. Primary endpoints were 1-year mortality and major adverse cardiovascular events (MACE). Propensity score (PS) matching was employed to create a balanced cohort for comparing successful and failed TRA. The impact of unsuccessful TRA on prognosis was evaluated using Cox regression analysis. Machine learning techniques were applied to predict TRA failure. The performance and the clinical applicability of the novel and prior prediction models were comprehensively evaluated. Out of 76,625 registered patients, 34,293 (69.8 ± 13.4 years, male/female: 21,893/12,400) underwent TRA (33,573) or failed TRA (720) PCI for STEMI. After PS-matching, in the unsuccessful TRA group, the risk of mortality (34.3% vs 22.5%, HR: 1.6, 95% CI: [1.3 – 2.0], p < 0.001) and MACE (37.4% vs 26.8%, HR: 1.5, 95% CI: [1.3 – 1.8], p < 0.001) were significantly higher. Door-to-balloon time did not differ significantly (p = 0.835). In predictive analysis, regularized discriminant analysis emerged as the most promising model, surpassing prior prediction models (AUC: 0.66, sensitivity: 0.32, specificity: 0.86). Nevertheless, GRACE 2.0 score demonstrated a remarkable performance (AUC: 0.65, sensitivity: 0.51, specificity: 0.73). This study underscores the pivotal role of successful TRA in enhancing outcomes in STEMI cases, advocating for its prioritization. The inability to conclude interventions via this approach is linked to a poorer prognosis, even in risk-adjusted analyses. Our findings indicate that prediction models utilizing clinical parameters do not outperform the established GRACE 2.0 algorithm, questioning their utility. In conclusion, the results emphasize the significance of TRA success and the continued relevance of the GRACE score in clinical decision-making to optimize patient outcomes.