Circulation, Vol 88, 927-934, Copyright © 1993 by American Heart Association
JT Bigger, JL Fleiss, LM Rolnitzky and RC Steinman
BACKGROUND. We studied 715 patients 2 weeks after myocardial infarction to
test the hypothesis that short-term power spectral measures of RR
variability (calculated from 2 to 15 minutes of normal RR interval data)
will predict all-cause mortality or arrhythmic death. METHODS AND RESULTS.
We performed power spectral analyses on the entire 24-hour RR interval time
series. To compare with the 24-hour analyses, we selected short segments of
ECG recordings from two time periods for analysis: 8 AM to 4 PM and
midnight to 5 AM. The former corresponds to the time interval during which
short-term measures of RR variability would most likely be obtained. The
latter, during sleep, represent a period of increased vagal tone, which may
simulate the conditions that exist when patients have a signal-averaged ECG
recorded, ie, lying quietly in the laboratory. Four frequency domain
measures were calculated from spectral analysis of heart period data over a
24-hour interval. We computed the 24-hour power spectral density and
calculated the power within three frequency bands: (1) 0.0033 to < 0.04
Hz, very low frequency power, (2) 0.04 to < 0.15 Hz, low frequency
power, and (3) 0.15 to 0.40 Hz, high frequency power. In addition, we
calculated the ratio of low to high frequency power. These measures were
calculated for 15-, 10-, 5-, and 2-minute segments during the day and at
night. Mean power spectral values from short periods during the day and
night were similar to 24-hour values, and the correlations between short
segment values and 24-hour values were strong (many correlations were >
or = 0.75). Using the optimal cutpoints determined previously for the
24-hour power spectral values, we compared the survival experience of
patients with low values for RR variability in short segments of ECG
recordings to those with high values. We found that power spectral measures
of RR variability were excellent predictors of all-cause, cardiac, and
arrhythmic mortality and sudden death. Patients with low values were 2 to 4
times as likely to die over an average follow-up of 31 months as were
patients with high values. The power spectral measures of RR variability
did not predict arrhythmic or sudden deaths substantially better than
all-cause mortality. CONCLUSIONS. Power spectral measures of RR variability
calculated from short (2 to 15 minutes) ECG recordings are remarkably
similar to those calculated over 24 hours. The power spectral measures of
RR variability are excellent predictors of all-cause mortality and sudden
cardiac death.
ARTICLES
The ability of several short-term measures of RR variability to predict mortality after myocardial infarction
Department of Medicine, School of Public Health, Columbia University, New York, NY 10032.
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