Abstract

INTRODUCTION The scales available to predict death and complica-tions after acute coronary syndrome include angiographic studies and serum biomarkers that are not within reach of services with limited resources. Such services need specifi c and sensitive instruments to evaluate risk using accessible resources and information. OBJECTIVE Develop a scale to estimate and stratify the risk of intra-hospital death in patients with acute ST-segment elevation myocardial infarction. METHODS An analytical observational study was conducted in a universe of 769 patients with acute ST-segment elevation myocardial infarction who were admitted consecutively to the Camilo Cienfuegos Provincial Hospital in Sancti Spíritus Province, Cuba, from January 2013 to March 2018. The fi nal study cohort included 667 patients, ex-cluding 102 due to branch blocks, atrial fi brillation, drugs that prolong the QT interval, low life expectancy or history of myocardial infarction. The demographic variables of age, sex, skin color, classic cardiovas-cular risk factors, blood pressure, heart rate, blood glucose level, in addition to duration and dispersion of the QT interval with and without correction, left ventricular ejection fraction, and glomerular fi ltration rate were included in the analysis. Patients were categorized according to the Killip-Kimball Classifi cation for degree of heart failure. A risk scale was constructed, the predictive ability of which was evaluated using the detectability index associated with an receiver-operator curve.RESULTS Seventy-seven patients died (11.5%). Mean blood glucose levels were higher among the deceased, while their systolic and dia-stolic blood pressure, left ventricular ejection fraction, and glomerular fi ltration rate were lower than those participants discharged alive. Rel-evant variables included in the scale were systolic blood pressure, Killip-Kimball class, cardiorespiratory arrest, glomerular fi ltration rate, corrected QT interval dispersion, left ventricular ejection fraction, and blood glucose levels. The variable with the best predictive ability was cardiorespiratory arrest, followed by a blood glucose level higher than 11.1 mmol/L. The scale demonstrated a great predictive ability with a detectability index of 0.92. CONCLUSIONS The numeric scale we designed estimates and strati-fi es risk of death during hospitalization for patients with ST-segment elevation myocardial infarction and has good metric properties for predictive ability and calibration. KEYWORDS ST-segment elevation myocardial infarction, mortality, risk assessment, Cuba.

Highlights

  • The scales available to predict death and complications after acute coronary syndrome include angiographic studies and serum biomarkers that are not within reach of services with limited resources

  • Mean blood glucose levels were higher among the deceased, while their systolic and diastolic blood pressure, left ventricular ejection fraction, and glomerular filtration rate were lower than those participants discharged alive

  • Relevant variables included in the scale were systolic blood pressure, Killip-Kimball class, cardiorespiratory arrest, glomerular filtration rate, corrected QT interval dispersion, left ventricular ejection fraction, and blood glucose levels

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Summary

Introduction

The scales available to predict death and complications after acute coronary syndrome include angiographic studies and serum biomarkers that are not within reach of services with limited resources. Such services need specific and sensitive instruments to evaluate risk using accessible resources and information. In Cuba, the mortality rate from heart disease in 2018 was 228.6 deaths per 100,000 population, with 63.3% of these deaths due to ischemic heart disease. For AMI, the mortality rate was 65.3 deaths per 100,000 population, of which 45.2% of deaths were due to ischemic heart disease. In Sancti Spíritus Province, in the center of the country, heart disease is a health issue with a crude death rate of 237.9 deaths per 100,000 population and an age-adjusted death rate of 109.7 deaths per 100,000 population.[6]

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