Noninvasive risk modeling after myocardial infarction.
The aim of this study was to extract and combine non-invasive risk parameters from the signal-averaged electrocardiogram (SAECG) and heart rate variability (HRV) based on 24-hour ambulatory electrocardiography to optimize the prognostic value for arrhythmic events after acute myocardial infarction. A prospective series of 553 men < 66 years of age enrolled in the Post-Infarction Late Potential study were analyzed. Within 2 to 4 weeks after acute myocardial infarction, all patients underwent SAECG and 24-hour ambulatory electrocardiography before hospital discharge. During 6 months of followup, 25 patients (4.5%) experienced arrhythmic events (sustained ventricular tachycardia, n = 11; ventricular fibrillation, n = 7; sudden cardiac death, n = 7). The predictive power of SAECG and HRV parameters was assessed using a Cox proportional-hazards model. In HRV analysis, the most significant differences between patients with and without arrhythmic events were observed for the beat-to-beat parameter root-meansquare of successive RR differences [RMSSD]): 25.7 +/- 16.9 ms in patients with arrhythmic events versus 34.1 +/- 18.6 ms in patients free of arrhythmic events (p = 0.004). Time domain analysis of the SAECG showed the QRS duration to be most significantly different in both patient groups: 106.4 +/- 18.7 ms (arrhythmic events) versus 95.3 +/- 18.7 ms (no arrhythmic events) (p = 0.001). Based on the Cox regression model, RMSSD and QRS duration were demonstrated to be independent significant risk factors (regression coefficient for QRS duration: cq = 0.014 +/- 0.006 ms(-1), p = 0.014; for RMSSD: cr = -0.041 +/- 0.016 ms(-1), p = 0.009). Based on the regression coefficients, an analytic risk model was developed describing the arrhythmic risk as a function of QRS duration, RMSSD, and time after infarction. We conclude that the combination of beat-to-beat changes of heart rate measured by RMSSD and QRS duration from the SAECG enhances noninvasive risk stratification after myocardial infarction.
Reinhardt
L
L
Department of Cardiology and Angiology, Hospital of the Westfälische Wilhelms-Universität, Münster, Germany.
Mäkijärvi
M
M
Fetsch
T
T
Schulte
G
G
Sierra
G
G
Martínez-Rubio
A
A
Montonen
J
J
Katila
T
T
Borggrefe
M
M
Breithardt
G
G
D001145:Arrhythmias, Cardiac / Q000209:etiology*; D015986:Confounding Factors, Epidemiologic; D004562:Electrocardiography; D006339:Heart Rate; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000150:complications* / Q000503:physiopathology*; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012306:Risk; D012815:Signal Processing, Computer-Assisted