Potential demographic and baselines variables for risk stratification of high-risk post-myocardial infarction patients in the era of implantable cardioverter-defibrillator — A prognostic indicator

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Abstract

Background

Risk stratification after myocardial infarction (MI) remains expensive and disappointing. We designed a prognostic indicator using demographic information to select patients at risk of dying after MI.

Method and results

We combined individual patient data from the placebo arms of EMIAT, CAMIAT, TRACE and DIAMOND-MI with LVEF 40% or ventricular arrhythmias (i.e. > 10 ventricular premature beats/hour or a run of ventricular tachycardia). Risk factors for mortality beginning at day 45 post-MI up to 2 years were examined using Cox regression analysis. Risk scores were derived from the equation of a Cox regression model containing only significant variables. The prognostic index was the sum of the individual contribution from the risk factors. 2707 patients were pooled (age: 66 (23–92) years, 78.8% M) with 480 deaths at 2-years (44% arrhythmic and 35.6% non-arrhythmic cardiac deaths). Variables predicting mortality were age, sex, previous MI or angina, hypertension, diabetes, systolic blood pressure, heart rate, NYHA functional class and non-Q wave infarct on electrocardiogram. Distinct survival curves were obtained for 3 risk groups based on the median and inter-quartile range for the prognostic index. In the high-risk group, up to 40% of patients died (all-cause mortality), 19.1% died of arrhythmic and 18.2% died of non-arrhythmic cardiac causes at 2-years.

Conclusion

In post-MI patients with LVEF ≤ 40% or frequent ventricular premature beats, the additional use of a simple prognostic indicator based on demographic information was able to provide clinically meaningful risk stratification on patients that were at high risk of dying and may be used to identify patients for prophylactic implantable cardioverter-defibrillator therapy.

Introduction

Ischaemic heart disease is the leading cause of death worldwide, accounting for 29% of all deaths [1]. Despite the improved survival with modern therapy in patients after acute myocardial infarction (AMI) [2], [3], approximately 10% of patients who survive the acute and sub-acute phases of MI will die during the first year after hospital discharge [3]. Death is often sudden and mostly arrhythmic in about half of the cases [4]. Risk stratification after MI has therefore attracted attention, in an attempt to identify patients at risk of sudden cardiac death who may potentially be treated prophylactically with an antiarrhythmic drug or implantable cardioverter-defibrillator (ICD). The Multicenter Automatic Defibrillator Implantation Trial II (MADIT II) demonstrated that prophylactic ICD therapy improved survival in post-MI patients stratified using reduced left ventricular function [5]. However, despite the approval by the U.S. Food and Drug Administration for ICD therapy based on the MADIT II indications, this practice has not been widely followed due to the high cost of the therapy. Thus, further improvement in risk stratification is necessary to identify higher risk subsets of coronary patients so that more focused ICD therapy can be carried out.

Risk stratification in post-MI patients involves analysis of the available demographic and clinical information. Previous studies addressing the prognostic values of demographic factors were performed in the pre-thrombolytic era and did not address cause specific stratification [6], [7], [8]. Thus, to improve the currently available risk stratification strategy in a cost-effective manner on post-MI patients who are most at risk of dying suddenly, we proposed a simple prognostic indicator, derived from the baseline and demographic variables of patients receiving placebo in a group of recently conducted, randomised multicenter prospective trials of post-myocardial infarction patients who had been pre-selected based on reduced left ventricular ejection fraction (LVEF) or frequent ventricular premature beats.

Section snippets

Data retrieval

We conducted an analysis on the pooled individual patient data from the placebo limbs of the European Myocardial Infarct Amiodarone Trial (EMIAT), the Canadian Amiodarone Myocardial Infarction Arrhythmia Trial (CAMIAT), the TRAndolapril Cardiac Evaluation (TRACE) trial and the Danish Investigation of Arrhythmias and Mortality on Dofetilide — Myocardial Infarction (DIAMOND-MI) trial. The detailed design and study protocol of these studies have already been previously published elsewhere [9], [10]

Results

The baseline characteristics of patients were summarised in Table 1. Of a total of 2972 patients, 2707 survived at least 45 days from MI and were included in the final analysis: 766 from TRACE, 594 from CAMIAT, 621 from DIAMOND-MI and 726 from EMIAT. Median elapsed time from MI to randomisation was 7 days (range 0–53 days). The majority of patients (79%) were male. Median age was 66 years (range 23–92 years). There were 480 deaths within the first 2 years, 213 of which were of arrhythmic causes

Discussion

Previous studies have demonstrated the prognostic values of demographic variables in the prediction of mortality after MI [6], [7], [8]. However, to our knowledge, there has been no contemporary study that has attempted to provide a quantitative scoring system to stratify high-risk patients after MI using this information, particularly with regard to arrhythmic death, for possible ICD therapy. However, the clinical usefulness of a scoring system depends on both its ease of use and its

Conclusions

Our study suggests that in post-MI patients, pre-selected using LVEF or frequent ventricular premature beats, the additional use of a simple prognostic indicator based on demographic and baseline information was able to segregate patients that were at high risk of dying, for 3 different modes of mortality. We have designed a simple but strong prognostic indicator using up-to-date, readily available demographic and clinical information. This prognostic indicator identifies a subgroup of

Acknowledgments

This study was supported by a British Heart Foundation project grant (No. PG/98006). Dr. Y.G. Yap was a British Heart Foundation Research Fellow in Cardiology. Professor A.J. Camm is British Heart Foundation Professor of Clinical Cardiology.

References (17)

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