Published online before print August 16, 2004, doi: 10.1161/01.CIR.0000140765.71014.1C
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(Circulation. 2004;110:1183-1190.)
© 2004 American Heart Association, Inc.
Original Articles |
Prevalent Low-Frequency Oscillation of Heart Rate
Novel Predictor of Mortality After Myocardial Infarction
From the Department of Cardiological Sciences, St George’s Hospital Medical School, London, UK (D.W., A.J.C., M.M.); Department of Internal Medicine, General University Hospital, Prague, Czech Republic (D.W., J.S.); Division of Cardiology, Fondazione "S. Maugeri" IRCCS, Montescano, Italy (M.T.L.R.); and Department of Cardiology, Policlinico S. Matteo IRCCS and University of Pavia, Pavia, Italy (P.J.S.).
Correspondence to Dr Marek Malik, Cardiological Sciences, St. George’s Hospital Medical School, London SW17 0RE UK. E-mail m.malik{at}sghms.ac.uk
Received January 16, 2004; de novo received April 1, 2004; revision received May 12, 2004; accepted May 18, 2004.
Background— This study evaluates a novel method for postinfarction risk stratification based on frequency-domain characteristics of heart rate variability (HRV) in 24-hour Holter recordings.
Methods and Results— A new risk predictor, prevalent low-frequency oscillation (PLF), was determined in the placebo population of the European Myocardial Infarction Amiodarone Trial (EMIAT). Frequencies of peaks detected in 5-minute low-frequency HRV spectra were averaged to obtain the PLF index. PLF 
0.1 Hz was the strongest univariate predictor of all-cause mortality associated with relative risk of 6.4 (95% CI, 3.9 to 10.6; P<10–12). In a multivariate Cox’s regression model including clinical risk factors, mean RR interval, HRV index, low- and high-frequency HRV spectral power, and heart rate turbulence, PLF was the most powerful mortality predictor, with a relative risk of 4.6 (95% CI, 2.2 to 9.3; P=0.00003). Predictive power of PLF was blindly validated in the population of the Autonomic Tone and Reflexes After Myocardial Infarction (ATRAMI) trial. PLF 0.1 Hz was associated with univariate relative risk of 6.1 (95% CI, 2.9 to 12.9; P<10–5) for cardiac mortality or resuscitated cardiac arrest. In multivariate Cox’s regression model including age, left ventricular ejection fraction, baroreflex sensitivity, mean RR interval, standard deviation of normal RR intervals, low- and high-frequency HRV spectral power, and heart rate turbulence, only left ventricular ejection fraction and PLF were significant predictors, with relative risks of 4.2 (95% CI, 1.5 to 11.7; P=0.007) and 3.6 (95% CI, 1.3 to 10.5; P=0.02), respectively.
Conclusions— An innovative analysis of frequency-domain HRV, which characterizes the distribution of spectral power within the low-frequency band, is a potent and independent risk stratifier in postinfarction patients.
Key Words: electrocardiography • heart rate • mortality • myocardial infarction • risk factors
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Circulation 2004 110: 1177.
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