Search

In cardiovascular variability analysis, the significance of the coupling between two time series is commonly assessed by setting a threshold level in the coherence function. While traditionally used statistical tests consider only the parameters of the adopted estimator, the required zero-coherence level may be affected by some features of the observed series. In this study, three procedures, based on the generation of surrogate series sharing given properties with the original but being structurally uncoupled, were considered: independent identically distributed (IID), Fourier transform (FT), and autoregressive (AR). IID surrogates maintained the distribution of the original series, while FT and AR surrogates preserved the power spectrum. The ability of the three methods to define the threshold for zero coherence was validated and compared by computer simulations reproducing typical cardiovascular interactions. While the IID threshold depended only on record length and design parameters of the coherence estimator, FT and AR thresholds were frequency-dependent with peaks corresponding to the local maxima of the estimated coherence. FT and AR surrogates were able to compensate spurious coherence peaks due to equal-frequency but independent oscillations in the two series. The benefit of frequency-dependent thresholds was evident for short series with narrow-band oscillations. Thus, surrogates preserving the power spectrum of the original series are recommended to avoid false coupling detections in the presence of oscillations occurring at nearby frequencies but produced by different mechanisms, as may frequently happen in cardiovascular and cardiorespiratory regulation. Index Terms--Cardiovascular variability, coherence function, coupling significance, spectral analysis, surrogate data.

To evaluate the effects of record length selection on the accuracy of spectral estimates of heart rate variability (HRV), a simulation study was carried out using a set of 58 signals obtained by autoregressive (AR) fitting a representative sample of real HRV signals. Four record lengths of 180, 300, 420, and 540 s were considered. Spectral estimation was performed by both the Blackman-Tukey (B-T) and AR methods. Accuracy was assessed for: 1) point spectral estimates, by computing the normalized averaged bias (NAB) and variance (NAV); and 2) the most commonly used spectral parameters [total power (TP) and the powers in the bands: very low frequency (VLF) (0 / 0.04 Hz), low frequency (LF) (0.04 / 0.15 Hz), and high frequency (HF) (0.15 / 0.45 Hz)], by computing the normalized bias (NB) and variance (NV). The results are: whatever the record length considered, the 90th percentiles (90P) of the NAB were [less than]10%, whereas those of the NB were [less than]9% for TP, LF, and HF powers, and [less than]14% for the VLF power, in both methods. The NAV was proportional to the reciprocal of record length, showing high 90P values for the shortest record length (26.4% for B-T and 44.2% for AR). The NV showed the same trend but 90P values were much lower ([less than]8% for TP, LF, and HF powers and [less than]19% for VLF power, in both methods). In the final part of the paper a procedure for the computation of approximate upper bounds of the relative absolute error of spectral measures at each record length, based on the knowledge of the NB and NV, is presented.

It is still not known whether the oscillation in heart rate (HR) induced by sleep‐disordered breathing (SDB) in patients with heart failure entails significant chronotropic effects. We hypothesised that since cyclical changes in ventilation and arterial blood gases during SDB affect HR through multiple and complexly interacting mechanisms characterised by large inter‐subject variability, chronotropic effects may change from patient to patient. A total of 42 patients with moderate‐to‐severe chronic heart failure with systolic dysfunction underwent an in‐hospital sleep study. Chronotropic effects of SDB were quantified by comparing the distribution of instantaneous HR during SDB with that during periods without SDB (noSDB) within the same night in each patient. Based on distribution changes from noSDB to SDB, 12, nine, 11, and 10 patients showed a significant tachycardic, bradycardic, tachycardic and bradycardic, and neither significant tachycardic nor significant bradycardic effect, respectively. Tachycardic and bradycardic effects were primarily due to an increase in the rate rather than in the magnitude of cyclical HR elevations and reductions, and were more prevalent and severe in patients with dominant obstructive and central events, respectively. The apnea–hypopnea index did not differ between groups. Conversely, the time spent with an oxygen saturation of <90% was greater in the tachycardic and tachycardic‐bradycardic groups compared to the bradycardic group. These findings indicate that HR distribution changes induced by SDB can vary from patient to patient revealing four distinct and well‐characterised chronotropic effects. These effects are related to the degree of hypoxic burden brought about by SDB and are affected by the type of sleep apnea (central/obstructive). [ABSTRACT FROM AUTHOR]