Description of time- and frequency- domain-based measures of heart rate variability in individuals taking antiarrhythmics, beta blockers, calcium channel blockers, and/or antihypertensive drugs after sudden cardiac arrest.

Concomitant drug therapies after sudden cardiac arrest and their potential effect of altering heart rate variability (HRV) represent confounding factors in interpreting the outcome of nonpharmacologic therapies on HRV. The purpose of this study is to describe a broad spectrum of time-domain and frequency-domain measurements of HRV in 50 individuals after sudden cardiac arrest. Some of the individuals were taking antiarrhythmics (n = 9), beta blockers (n = 13), calcium channel blockers (n = 10), nitrates (n = 8), cardiac glycosides (n = 10), and/or antihypertensives (n = 12). Heart rate variability was measured using a Holter recorder for 24 hours and the SpaceLabs FT2000 Monitoring System (Redmond, WA). In those individuals taking antiarrhythmic drugs, the power density within the low-frequency range (.016-.04 Hz) was significantly decreased (P = .001) compared to those not taking antiarrhythmics (n = 41). However, 78% of the people taking antiarrhythmics also had congestive heart failure (New York Heart Association functional classes II and III), which also decreased HRV. Those individuals taking beta blockers tended to have slower heart rates (P < .01). The association between beta blocker use and HRV was positive, but not statistically significant except for the increased power density in the low-frequency range (P < .05). In general, the relationships between HRV and drug therapy--calcium channel blockers, antihypertensives, cardiac glycosides, or nitrates--were not statistically significant.

Comparison of autoregression and fast Fourier transform techniques for power spectral analysis of heart period variability of persons with sudden cardiac arrest before and after therapy to increase heart period variability.

Clinical studies have used two types of analysis of the power spectral estimates of heart period variability: autoregressive and fast Fourier transform techniques. Controversy exists regarding which method is the most valid. The specific aims of this study are: (1) to describe the power spectra of heart period variability before and after an intervention designed to increase heart period variability in persons after sudden cardiac arrest; (2) to compare the integral of power spectral density between autoregressive and fast Fourier transform techniques within low and high-frequency bands; (3) to compare the magnitude of the spectral peak values determined by autoregressive and fast Fourier transform techniques approaches within low and high-frequency bands; and (4) to compare the aforementioned parameters using 4-minute, 1-hour, and 24-hour blocks of heart period data. Results indicated high correlations between spectral estimations by autoregressive and fast Fourier transform techniques using integrals or peak values within either the low or high-frequency ranges. The autoregressive technique demonstrated better resolution of sharp peaks than the fast Fourier transform technique, and makes a smoother, more interpretable curve. Lastly, people can cognitively change their heart rate variability.