In a recent analysis published in the Journal of the American College of Cardiology, a link between silent myocardial infarction and subsequent heart failure has been demonstrated, revealing a novel potential marker for heart failure.
“Silent myocardial infarction, defined as evidence of myocardial infarction on ECG in the absence of history of myocardial infarction, accounts for about half of the total number of myocardial infarctions”, report the authors. Despite this, the risk of heart failure among patients with silent MI was not well established. Dr. Waqas Qureshi and his colleagues evaluated the association of silent myocardial infarction and clinically manifested myocardial infarction, versus no myocardial infarction, with heart failure. The median follow-up duration was 13 years.
According to the senior author of the study, Dr. Elsayed Z. Soliman, Director of Epidemiological Cardiology Research Center (EPICARE) at the Wake Forest School of Medicine, the study is important because “unlike prior reports which used self-report to define prior clinical MI and ECG at one single visit to define unrecognized MI, our analysis used a more meticulous and more longitudinal approach which makes the results more definitive.” He added, “Specifically, we used ECG data from four separate visits spanning over almost a decade, and we used MI events which were adjudicated by an independent committee.”
A total of 9,243 subjects who were enrolled in the Atherosclerosis Risk in Communities (ARIC) study and were free of cardiovascular disease at baseline were analyzed. “The Atherosclerosis Risk in Communities(ARIC) study was designed to study atherosclerosis and its clinical outcomes, cardiac risk factors, medical care and disease among the different races, genders and locations.”
“I believe we have enough evidence that silent MI is associated with poor outcomes such as coronary heart disease and all-cause mortality. We are now adding to this list heart failure too.”-Dr. Elsayed Z. Soliman
In the present analysis, silent myocardial infarction was defined, according to the Minnesota classification, as new appearance of a Q/QS wave abnormality or a minor Q/QS wave plus major ST-T abnormality in the absence of clinical signs of myocardial infarction. Incident heart failure was defined as the first occurrence of a heart failure hospitalization according to the International Classification of Diseases-9th Revision (ICD-9) code.
Overall, there were 976 incident cases of heart failure. Approximately 31% of patients with clinical myocardial infarction developed heart failure and 18% of patients with silent myocardial infarction developed heart failure. These figures compare to only 9.5% of patients without myocardial infarction developing heart failure within the follow-up period. These findings were consistent when the investigators adjusted for patient demographics (age sex, and race) and known risk factors of heart failure including body mass index, smoking status, heart rate, systolic blood pressure, use of blood pressure lowering medications, and diabetes mellitus.
When asked to comment on the implications of these findings on clinical practice, Dr. Soliman remarked, “I believe we have enough evidence that silent MI is associated with poor outcomes such as coronary heart disease and all-cause mortality. We are now adding to this list heart failure too.”
In the publication, the authors acknowledge the possibility for residual confounding despite adjustments of several known confounders and that “future research is needed to examine the cost-effectiveness of screening for SMI as part of HF risk assessment and to identify preventive therapies to improve the risk of HF among patients with SMI.”
In an accompanying editorial, Dr. Michael Gibson, Dr. Tarek Nafee, and Dr. Mathieu Kerneis, from the Beth Israel Deaconess Medical Center, said that this study “contributes to the growing body of evidence on ECG-defined silent MI” and “supports its use as a meaningful clinical endpoint.”
Gibson et. al. added that “the introduction of ECG-defined silent MI to a composite endpoint may increase the number of events among a population enrolled in a clinical trial” and would “increase the statistical power, reduce the required sample size and thus reduce the duration and cost of a randomized clinical trial.”