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Atrial fibrillation (AF) is most common persistent supra-ventricular arrhythmia. It is responsible for a significant socioeconomic burden by causing strokes and heart failure. Hence, identification of risk factors that predispose to AF is important especially since the onset of AF is often asymptomatic. Autonomic dysfunction has been proposed to be one of the many factors associated with pathogenesis of tachyarrhythmias. A new study now has shown that autonomic dysfunction may have a role to play in new-onset AF in post myocardial infarction patients with systolic dysfunction.
Jons and colleagues recently published their results in Journal of cardiovascular electrophysiology. In their study, the investigators studied patients with systolic dysfunction after a myocardial infarction. These patients have a high likelihood to develop AF compared to normal population. The study was aimed at identifying the factors that may predict an increased risk of developing new-onset AF in such patients. According to the investigators, the mechanism of AF involves multiple factors including structural changes in the heart and neurohormonal changes.
In this retrospective analysis of Cardiac Arrhythmias and Risk Stratification after Myocardial Infarction (CARISMA) study, they studied 271 patients who had recent myocardial infarction with left ventricular ejection fraction (LVEF) < 40% for two years. All patients included in the study had an implantable loop recorder placement and were followed every three months for two years. Additionally, these patients underwent electrophysiology study, holter monitoring, 2D-echocardiography, exercise testing and interval ECGs at prespecified times. The holter readings were analyzed for measures of automonic dysfunction in a diseased heart such as heart rate variability (HRV) and heart rate turbulence (HRT). HRV assessment was done using standard deviation of normal-to-normal beat intervals (SDNN) and frequency domain measures in the form of detrended fluctuation analysis short-term scaling exponent (DFA1).
As expected, the incidence of new-onset AF was pretty high at about 37%. When the investigators compared the patients with new AF with whose without, they found that patients who were diagnosed with new AF were more likely to be older, have larger left atrial size, have NYHA class II-IV symptoms and COPD, and less likely to have undergone PCI after MI.
The study found that electrophysiology testing parameters did not predict future AF. Both 2D ECHO and holter had predictive variables for future AF risk. The investigators report “The highest predictive values were obtained using HR variability and turbulence at the Holter monitoring. A turbulence slope value ≤2.5 ms/RR, the lower tertile of the low-frequency power (LFIn <4.60) from spectral HRV measurements and the lower tertile of the short-term scaling exponential from fractal HRV analysis (DFA1 <1.0) were consistently associated with an increased risk of AF at baseline and at week 6. SDNN was not predictive for AF.” They also mention that Holter monitoring and the echocardiograms obtained 3–7 days after AMI and at week 6 revealed very similar predictive values for future AF and combination of the early and late test did not increase the predictive value of the tests.
Measures of reduced heart rate variability have been use to predict post-MI fatal arrhythmias and risk of sudden cardiac death. This study would expand the HRV analysis with holter monitoring in post-MI patients to predict future AF risk as well. In this study, they found the slope of HRT as the single best predictor of future AF. When compared to HRT onset, the slope is more likely to be stable than the HRT onset.
Using multivariate regression, the authors devised a risk predictor model. The model assigns 1 integer point for each of the four risk factors: age >60 years, HRT slope ≤2.5, LFIn <4.60, DFA1 <1.0. Using this model, the patients with 3-4 points were found be at the highest risk, followed by those with 1-2 points when compared to those with no points. This risk calculator should allow physicians assess the risk of future occurrence of AF in post MI patients with systolic dysfunction. Studies would be needed in future to ascertain if aggressive risk factor management after identifying these high risk patients can mitigate part of the risk.
Jons C, Raatikainen P, Gang UJ, Huikuri HV, Joergensen RM, Johannesen A, Dixen U, Messier M, McNitt S, Thomsen PE; for the Cardiac Arrhythmias and Risk Stratification after Acute Myocardial Infarction (CARISMA) Study Group. Autonomic Dysfunction and New-Onset Atrial Fibrillation in Patients With Left Ventricular Systolic Dysfunction After Acute Myocardial Infarction: A CARISMA Substudy. J Cardiovasc Electrophysiol. 2010 May 7.
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