부산대학교 도서관

Predicting New-Onset AF. Background: Atrial fibrillation (AF) increases morbidity and mortality in patients with previous myocardial infarction and left ventricular systolic dysfunction. The purpose of this study was to identify patients with a high risk for new-onset AF in this population using invasive and noninvasive electrophysiological tests. Methods: The study included 271 patients from the Cardiac Arrhythmias and RIsk Stratification after Myocardial InfArction (CARISMA) study with an acute myocardial infarction (AMI) and left ventricular ejection fraction ≤40% without previous AF at enrollment. Within 21 days after the AMI, an implantable loop recorder was inserted and used to diagnose AF over the 2-year study duration. The following tests were performed: heart rate variability (HRV) and turbulence (HRT) analyses from repeated 24-hour Holter recordings, 2-dimensional (2D)-echocardiograms, exercise test, and programmed electrophysiologic stimulation. Results: A total of 101 patients (37%) developed AF during the study. Predictive measures included several indexes of HRV including reduced low-frequency (LF) power from spectral HRV analysis (adjusted HR = 1.6, P = 0.034), HRT slope ≤2.5 (HR = 1.6, P = 0.032) and Detrended Fluctuation Analysis (DFA1) from HRV analysis (HR = 1.8, P = 0.011); all are measures of cardiac autonomic nervous system dysfunction. Combined with age >60 years, low values for LF, HRT slope, and DFA1 provided a powerful risk score for prediction of new-onset AF (1–2 points: HR = 4.3, P = 0.001, 3–4 points: HR = 7.0, P < 0.001). Conclusion: Abnormal HRV and HRT parameters, which are associated with disturbances in the cardiac autonomic regulation, are associated with increased risk of new-onset AF independently of conventional clinical risk variables. (J Cardiovasc Electrophysiol, Vol. 21, pp. 983-990, September 2010) [ABSTRACT FROM AUTHOR]