We recently developed an R-based software that could model closedloop
cardiovascular interactions. In this study, we applied this tool
on the EUROBAVAR data set to further test its applicability. The aim of this work is to test the effectiveness
of our software to identify cardiovascular regulatory mechanisms and
baroreflex impairment from these data. We first uploaded each recording into our software to model the
interactions present between systolic blood pressure (SBP) and IBI
by employing a wavelet detrending and multivariate autoregressive
modeling algorithm. Then, our software estimated causal coherence
and Gaussian-weighted baroreflex sensitivity (BRS) indexes from
each model at the low frequency (LF, 0.04-0.15 Hz, sympathetic) and
high frequency (HF, 0.15-0.4 Hz, parasympathetic) bands. Immediate
variability transfer from SBP to IBI was also computed for each
subject. Our results showed that, when standing, the estimates of
only two subjects, B005 and B010, were below percentile P10 of the
BRS distribution (0.719 ms/mmHg at HF, 1.678 ms/mmHg at LF) at
both bands. A literature review indicated that these two subjects had
a baroreflex impairment. In non-baroreflex-impaired subjects, causal
coherence from IBI to SBP at LF was significantly predominant at rest
when compared with the coupling from SBP to IBI (p < 0.001). This
predominance disappeared during standing due to changes in the couplings,
suggesting a baroreflex interaction. Closed-loop BRS supineto-
standing ratios in these subjects were 1.69 ± 0.93 (LF band) and
3.1 ± 1.32 (HF band), showing a significantly decreased BRS during
standing position (p < 0.01, LF; p < 0.001, HF). Immediate transfer
also decreased during standing (p < 0.001). In conclusion, our software
managed to evaluate causal closed-loop interactions between cardiovascular
variables from the data set, evidencing a baroreflex coupling, Thus, this allows it to
be a useful tool for baroreceptor evaluations.
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