Phase Synchronization of Hemodynamic Variables at Rest and after Deep Breathing Measured during the Course of Pregnancy

Abstract

BackgroundThe autonomic nervous system plays a central role in the functioning of systems critical for the homeostasis maintenance. However, its role in the cardiovascular adaptation to pregnancy-related demands is poorly understood. We explored the maternal cardiovascular systems throughout pregnancy to quantify pregnancy-related autonomic nervous system adaptations.MethodologyContinuous monitoring of heart rate (R-R interval; derived from the 3-lead electrocardiography), blood pressure, and thoracic impedance was carried out in thirty-six women at six time-points throughout pregnancy. In order to quantify in addition to the longitudinal effects on baseline levels throughout gestation the immediate adaptive heart rate and blood pressure changes at each time point, a simple reflex test, deep breathing, was applied. Consequently, heart rate variability and blood pressure variability in the low (LF) and high (HF) frequency range, respiration and baroreceptor sensitivity were analyzed in resting conditions and after deep breathing. The adjustment of the rhythms of the R-R interval, blood pressure and respiration partitioned for the sympathetic and the parasympathetic branch of the autonomic nervous system were quantified by the phase synchronization index γ, which has been adopted from the analysis of weakly coupled chaotic oscillators.ResultsHeart rate and LF/HF ratio increased throughout pregnancy and these effects were accompanied by a continuous loss of baroreceptor sensitivity. The increases in heart rate and LF/HF ratio levels were associated with an increasing decline in the ability to flexibly respond to additional demands (i.e., diminished adaptive responses to deep breathing). The phase synchronization index γ showed that the observed effects could be explained by a decreased coupling of respiration and the cardiovascular system (HF components of heart rate and blood pressure).Conclusions/SignificanceThe findings suggest that during the course of pregnancy the individual systems become increasingly independent to meet the increasing demands placed on the maternal cardiovascular and respiratory system.

The Impact of Obesity Physiologic Indicators

“…[39,40,41] Although the pattern of change in SBP was not significant for the over-weight women, the pattern of a gradual rise, returning to or exceeding early pregnancy levels at 36 weeks, mirrors the reported findings of Moertl and colleagues. [22] The changes seen for over-weight women may be explained as the ability to flexibly respond to additional demands of pregnancy. [22,37] In comparison, a significant pattern of change in the physiologic indicators was not identified for the obese women.…”

“…[6] SBP has been reported to decrease early in gestation, [21] reaching a nadir by 20 weeks, then the SBP starts a gradual increase, returning to or exceeding early pregnancy levels by 35 weeks. [22] From the 1 st trimester onwards, SBPs were higher in each trimester for obese women as compared to non-obese pregnant women. [4,23] However, changes over time were not significant.…”

Respiração lenta e profunda aumenta a modulação vagal em gestantes

“…De acordo com Moertl et al [23], que acompanharam a modulação autonômica de 36 mulheres durante o curso da gravidez, os sistemas individuais tornam-se mais independentes entre si e diminuem a troca de informações ao tentar atender às demandas cardiovascular e respiratórias maternas. O aumento da complexidade indica que uma maior integração entre os sistemas fisiológicos pôde ser observada ao final da manobra, sugerindo melhora na troca de informações entre os sistemas [14,24], como, por exemplo, os centros respiratórios, de pressão e de controle da dor.…”

Mining the hidden dysrhythmia ‐ can machines get smarter at defining the anaesthetised state?

“…As such, all the different systems, including circulatory, respiratory, and autonomic systems, interact or cross‐talk with each other in an inseparable way. Part of such interaction could potentially be estimated by analysing wavelets across various frequency ranges .…”