RR variability in healthy, middle-aged persons compared with patients with chronic coronary heart disease or recent acute myocardial infarction.
BACKGROUND
The purpose of this investigation was to establish normal values of RR variability for middle-aged persons and compare them with values found in patients early and late after myocardial infarction. We hypothesized that presence or absence of coronary heart disease, age, and sex (in this order of importance) are all correlated with RR variability.


RESULTS
To determine normal values for RR variability in middle-aged persons, we recruited a sample of 274 healthy persons 40 to 69 years old. To determine the effect of acute myocardial infarction RR variability, we compared measurements of RR variability made 2 weeks after myocardial infarction (n = 684) with measurements made on age- and sex-matched middle-aged subjects with no history of cardiovascular disease (n = 274). To determine the extent of recovery of RR variability after myocardial infarction, we compared measurements of RR variability made in the group of healthy middle-aged persons with measurements made in 278 patients studied 1 year after myocardial infarction. We performed power spectral analyses on continuous 24-hour ECG recordings to quantify total power, ultralow-frequency (ULF) power, very-low-frequency (VLF) power, low-frequency (LF) power, high-frequency (HF) power, and the ratio of LF to HF (LF/HF) power. Time-domain measures also were calculated. All measures of RR variability were significantly and substantially lower in patients with chronic or subacute coronary heart disease than in healthy subjects. The difference from normal values was much greater 2 weeks after myocardial infarction than 1 year after infarction, but the fractional distribution of total power into its four component bands was similar for the three groups. In healthy subjects, ULF power did not change significantly with age; VLF, LF, and HF power decreased significantly as age increased. Patients with chronic coronary heart disease showed little relation between power spectral measures of RR variability and age. Patients with a recent myocardial infarction showed a strong inverse relation between VLF, LF, and HF power and age and a weak inverse relation between ULF power and age. ULF power best separates the healthy group from either of the two coronary heart disease groups. Differences in RR variability between men and women were small and inconsistent among the three groups.


CONCLUSIONS
All measures of RR variability were significantly and substantially higher in healthy subjects than in patients with chronic or subacute coronary heart disease. The difference between healthy middle-aged persons and those with coronary heart disease was much greater 2 weeks after myocardial infarction than 1 year after infarction, but the fractional distribution of total power into its four component bands was similar for the healthy group and the two coronary heart disease groups. Values of RR variability previously reported to predict death in patients with known chronic coronary heart disease are rarely (approximately 1%) found in healthy middle-aged individuals. Thus, when measures of RR variability are used to screen groups of middle-aged persons to identify individuals who have substantial risk of coronary deaths or arrhythmic events, misclassification of healthy middle-aged persons should be rare.
Bigger
J T
JT
Department of Medicine, School of Public Health, Columbia University, New York, NY 10032.
Fleiss
J L
JL
Steinman
R C
RC
Rolnitzky
L M
LM
Schneider
W J
WJ
Stein
P K
PK
D000367:Age Factors; D003327:Coronary Disease / Q000175:diagnosis / Q000401:mortality / Q000503:physiopathology*; D015716:Electrocardiography, Ambulatory; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis / Q000401:mortality / Q000503:physiopathology*; D011237:Predictive Value of Tests; D012016:Reference Values; D012307:Risk Factors; D012737:Sex Factors; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors