Impact on Public HEalth of a Network in Acute Myocardial Infarction Care

Overview

This is a multicenter retrospective observational study with STEMI (ST Elevation Myocardial Infarction) patients who have been treated in the northern Galician Hospitals. The study tries to verify if the implantation of the PROGALIAM (Galician Assistance Program Acute Myocardial Infarction) has supposed a progress in the quality and expectancy of life of AMI patients in the north area of Galicia. The study will recruit STEMI patients according to the third consensus definition of myocardial infarction type I. It will include all patients who meet these criteria regardless of other demographic or clinical circumstances. There is not exclusion criteria defined for this population.

* Study Hypothesis This study tries to verify if the implantation of the PROGALIAM has supposed a progress in the quality and expectancy of life of AMI patients in the north area of Galicia. * Objectives. The study presents the following objectives: Primary Objectives: To compare morbidity rates between pre and post-PROGALIAM periods in major adverse cardiac events. The outcome to study is a composite of death, reinfarction, heart failure and major bleeding at 30 days, one year and long term follow-up. Secondary Objectives To compare Pre and post PROGALIAM periods regarding; 1\. Overall mortality at 30 days, one year and long term follow up. 2. Reinfarction at 30 days, one year and long term follow up. 3. Heart failure incidence at 30 days, one year and long term follow up 4. Hospital major bleeding and at 30 days. 5. Hospital Vascular complications and at 30 days. 6. Heart failure functional Class at 30 days, one year and long term follow up. * Study Design This is a multicenter retrospective observational study with STEMI patients who have been treated in the northern Galician Hospitals. 1. Pre-PROGALIAM period: January 2001- May 2005 2. Post-PROGALIAM period: June 2005- December 2011 * Rational for Sample size Sample size will be constituted by all STEMI cases occurred in both timeframes described above. According to data obtained in MASCARA register where approximately 38% of ACS patients present ST segment elevation, the estimated sample size would therefore be about 6100 patients. \*Inclusion, Exclusion Criteria and rational The study will recruit STEMI patients according to the third consensus definition of myocardial infarction type I. It was recently published. It will include all patients who meet these criteria regardless of other demographic or clinical circumstances. There is not exclusion criteria defined for this population. \*Statistical analysis Categorical variables will be presented in percentage, calculated from the whole valid information. The CI will be of 95 %. Quantitative variables will be presented as mean ± standard deviation or median (interquartile range) according to a normal underlying distribution or not. Initially a univariate analysis will be done. The comparison of quantitative variables means will be done by student´s t-test in case of normality or by nonparametric tests in the opposite case. Categorical variables will be analyzed by the Chi square test. Survival will be analyzed by Kaplan-Meier curves. The comparison between pre and post PROGALIAM curves will be done by a log-rank test. A p \<0.05 will be considered statistically significant for two-tailed tests. Also there are plans to carry out a multivariate analysis. There will be a quantification of the adjusted effect on mortality due to the introduction of PROGALIAM by a Cox Proportional Hazards model. It will be defined the best model to predict this adjusted event by independent variables which can demonstrate an impact on death outcome in the univariate model and by those independent variables in which significant differences are observed between the pre and post PROGALIAM population. The investigators will verify if the implementation of the PROGALIAM is an independent predictor of survival and the impact that generates in the model. A p \<0.05 result will be considered statistically significant in a two-tailed test. To carry out these analyses it will be necessary to have statistical software like SPSS and/or SAS.