Trigonometric regressive spectral analysis reliably maps dynamic changes in baroreflex sensitivity and autonomic tone: the effect of gender and age

Abstract

Background: The assessment of baroreflex sensitivity (BRS) has emerged as prognostic tool in cardiology. Although available computer-assisted methods, measuring spontaneous fluctuations of heart rate and blood pressure in the time and frequency domain are easily applicable, they do not allow for quantification of BRS during cardiovascular adaption processes. This, however, seems an essential criterion for clinical application. We evaluated a novel algorithm based on trigonometric regression regarding its ability to map dynamic changes in BRS and autonomic tone during cardiovascular provocation in relation to gender and age.

Methodology/principal findings: We continuously recorded systemic arterial pressure, electrocardiogram and respiration in 23 young subjects (25+/-2 years) and 22 middle-aged subjects (56+/-4 years) during cardiovascular autonomic testing (metronomic breathing, Valsalva manoeuvre, head-up tilt). Baroreflex- and spectral analysis was performed using the algorithm of trigonometric regressive spectral analysis. There was an age-related decline in spontaneous BRS and high frequency oscillations of RR intervals. Changes in autonomic tone evoked by cardiovascular provocation were observed as shifts in the ratio of low to high frequency oscillations of RR intervals and blood pressure. Respiration at 0.1 Hz elicited an increase in BRS while head-up tilt and Valsalva manoeuvre resulted in a downregulation of BRS. The extent of autonomic adaption was in general more pronounced in young individuals and declined stronger with age in women than in men.

Conclusions/significance: The trigonometric regressive spectral analysis reliably maps age- and gender-related differences in baroreflex- and autonomic function and is able to describe adaption processes of baroreceptor circuit during cardiovascular stimulation. Hence, this novel algorithm may be a useful screening tool to detect abnormalities in cardiovascular adaption processes even when resting values appear to be normal.

Figure 1. Baroreflex sensitivity, blood pressure and RR-total weighed average variance during controlled breathing.

Data are mean and SEM; BRS, baroreflex sensitivity; BP, blood pressure; p_t-values for repeated measures, p_age and p_sex from univariate analyses, and p for interaction effects (e.g. p_age*sex).

Figure 2. Baroreflex sensitivity and frequency spectra during head-up tilt.

Data are mean and SEM; BRS, baroreflex sensitivity; Low frequency (LF) and high frequency (HF) power of RR interval and of systolic blood pressure (SBP); p_t-values for repeated measures, p_age and p_sex from univariate analyses, and p for interaction effects (e.g. p_age*sex).

Figure 3. Baroreflex sensitivity and frequency spectra during Valsalva manoeuvre.

Data are mean and SEM; BRS, baroreflex sensitivity; Low frequency (LF) and high frequency (HF) power of RR interval and of systolic blood pressure (SBP); p_t-values for repeated measures, p_age and p_sex from univariate analyses, and p for interaction effects (e.g. p_age*sex).

Figure 4. Associations of baroreflex sensitivity with frequency spectra.

Data are unadjusted individual values; BRS, baroreflex sensitivity; Low frequency (LF) and high frequency (HF) power of RR interval and of systolic blood pressure (SBP); r, Pearson correlation coefficient; p value for unadjusted values; p_adj value after controlling for age and gender.