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

objectivesWe 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 "

methodsIn 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.

resultsAll 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% (

conclusionsOur analysis identified a predictive model for in-hospital mortality. The majority of deaths were due to cardiogenic shock. We suggested that in order to lower mortality under 5 percent, focus should be on creating a cardiogenic shock system based on the US experience. A shock hub-centre, together with specific transfer algorithms, mobile interventional teams, ventricular assist devices, and surgical hybrid procedures seem to be the next step toward a better management of ST-elevation MI patients and subsequently lower death rates.