Frequency domain measures of heart period variability and mortality after myocardial infarction

• Published in: Circulation (New York, N.Y.) Vol. 85; no. 1; pp. 164 - 171
• Main Authors: THOMAS BIGGER, J. JR, FLEISS, J. L, STEINMAN, R. C, ROLNITZKY, L. M, KLEIGER, R. E, ROTTMAN, J. N
• Format: Conference Proceeding Journal Article
• Language: English
• Published: Hagerstown, MD Lippincott Williams & Wilkins 1992
• Subjects: Aged; Biological and medical sciences; Cardiology. Vascular system; Coronary heart disease; Forecasting; Heart; Heart Rate; Humans; Medical sciences; Multivariate Analysis; Myocardial Infarction - mortality; Myocardial Infarction - physiopathology; Risk Factors; Survival Analysis; Human; Infarct; Mortality; Cardiovascular disease; Exploration; Coronary heart disease; Electrodiagnosis; Follow up study; Autonomic nervous system; Electrocardiography; Myocardium; Ambulatory; Monitoring
• ISSN: 0009-7322; 1524-4539
• DOI: 10.1161/01.cir.85.1.164

We studied 715 patients 2 weeks after myocardial infarction to establish the associations between six frequency domain measures of heart period variability (HPV) and mortality during 4 years of follow-up.
Each measure of HPV had a significant and at least moderately strong univariate association with all-cause mortality, cardiac death, and arrhythmic death. Power in the lower-frequency bands--ultra low frequency (ULF) and very low frequency (VLF) power--had stronger associations with all three mortality end points than power in the higher-frequency bands--low frequency (LF) and high frequency (HF) power. The 24-hour total power also had a significant and strong association with all three mortality end points. VLF power was the only variable that was more strongly associated with arrhythmic death than with cardiac death or all-cause mortality. In multivariate Cox regression models using a step-up approach to evaluate the independent associations between frequency domain measures of heart period variability and death of all causes, ULF power was selected first (i.e., was the single component with the strongest association). Adding VLF or LF power to the Cox regression model significantly improved the prediction of outcome. With both ULF and VLF power in the Cox regression model, the addition of the other two components, LF and HF power, singly or together, did not significantly improve the prediction of all-cause mortality. We explored the relation between the heart period variability measures and all-cause mortality, cardiac death, and arrhythmic death before and after adjusting for five previously established postinfarction risk predictors: age, New York Heart Association functional class, rales in the coronary care unit, left ventricular ejection fraction, and ventricular arrhythmias detected in a 24-hour Holter ECG recording.
After adjustment for the five risk predictors, the association between mortality and total, ULF, and VLF power remained significant and strong, whereas LF and HF power were only moderately strongly associated with mortality. The tendency for VLF power to be more strongly associated with arrhythmic death than with all-cause or cardiac death was still evident after adjusting for the five covariates. Adding measures of HPV to previously known predictors of risk after myocardial infarction identifies small subgroups with a 2.5-year mortality risk of approximately 50%.