Strategies to Lower In-Hospital Mortality in STEMI Patients with Primary PCI: Analysing Two Years Data from a High-Volume Interventional Centre

Objectives. We aimed to analyse data from our high-volume interventional centre (>1000 primary percutaneous coronary interventions (PCI) per year) searching for predictors of in-hospital mortality in acute myocardial infarction (MI) patients. Moreover, we looked for realistic strategies and interventions for lowering in-hospital mortality under the “5 percent threshold.” Background. Although interventional and medical treatment options are constantly expanding, recent studies reported a residual in-hospital mortality ranging between 5 and 10 percent after primary PCI. Current data sustain that mortality after ST-elevation MI will soon reach a point when cannot be reduced any further. Methods. In this retrospective observational single-centre cohort study, we investigated two-year data from a primary PCI registry including 2035 consecutive patients. Uni- and multivariate analysis were performed to identify independent predictors for in-hospital mortality. Results. All variables correlated with mortality in univariate analysis were introduced in a stepwise multivariate linear regression model. Female gender, hypertension, depressed left ventricular ejection fraction, history of MI, multivessel disease, culprit left main stenosis, and cardiogenic shock proved to be independent predictors of in-hospital mortality. The model was validated for sensitivity and specificity using receiver operating characteristic curve. For our model, variables can predict in-hospital mortality with a specificity of 96.60% and a sensitivity of 84.68% (p