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[Preprint]. 2024 Oct 15:2024.10.11.617927.
doi: 10.1101/2024.10.11.617927.

Noninvasive Assessment of Temporal Dynamics in Sympathetic and Parasympathetic Baroreflex Responses

Heberto Suarez-Roca  1 , Negmeldeen Mamoun  2 , Joseph P Mathew  2 , Andrey V Bortsov  1
Affiliations

Noninvasive Assessment of Temporal Dynamics in Sympathetic and Parasympathetic Baroreflex Responses

Heberto Suarez-Roca et al. bioRxiv. .

Update in

Abstract

Background: The baroreflex system is crucial for cardiovascular regulation and autonomic homeostasis. A comprehensive assessment requires understanding the simultaneous temporal dynamics of its multiple functional branches, which traditional methods often overlook.

Objective: To develop and validate a noninvasive method for simultaneously assessing the temporal dynamics of sympathetic and parasympathetic baroreflexes using pulse contour analysis and the sequence method.

Methods: Beat-to-beat blood pressure and ECG recordings were analyzed from 55 preoperative cardiothoracic surgery patients in the supine position and 21 subjects from the EUROBAVAR dataset in both supine and standing positions. Systolic arterial pressure (SAP), interbeat interval (IBI), cardiac output (CO), myocardial contraction (dP/dtmax), and systemic vascular resistance (SVR) were estimated using pulse contour analysis. Baroreflex sensitivity (BRS) was calculated via the sequence method and correlated with hemodynamic and heart rate variability (HRV) parameters.

Results: Parasympathetic BRS for IBI was correlated with the root mean square of successive differences of ECG RR intervals (RMSSD-HRV) at 0-beat delay. Sympathetic BRS for SVR strongly correlated with SVR, CO, and RMSSD-HRV, particularly at 3-beat delay, and was uniquely associated with SAP at 1-beat delay. Sympathetic BRS for dP/dtmax correlated with dP/dtmax at 1-beat delay. In contrast, BRS for CO correlated with CO and SVR at 0- and 3-beat delays. Postural changes mainly affected parasympathetically-mediated BRS for IBI and, to a lesser extent, the sympathetic vascular and myocardial branches.

Conclusions: This method effectively captures multiple baroreflex responses and their temporal dynamics, revealing distinct autonomic mechanisms and the impact of postural changes. Further validation is warranted.

Keywords: Baroreflex; Heart Rate Variability; Hemodynamics; Parasympathetic; Postural Change; Sympathetic.

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Figures

Figure 1.
Figure 1.. Influence of systolic arterial pressure (SAP) on four baroreflex effectors: peripheral vascular tone (SVR), myocardial contraction (dP/dtmax), cardiac output (CO), and heart rate (HR) across different beat delays (0, 1, 2, 3, and 6).
Each panel displays three parameters: baroreflex sensitivity (BRS, circles), baroreflex effectiveness index (BEI, triangles), and the number of baroreflex sequences over 10 minutes (SQ, squares). Data symbols represent the mean ± 95% confidence interval. Colored lines contain statistically significant values, with asterisks denoting significant differences compared to the lowest data point in the line (repeated measures one-way ANOVA, followed by Bonferroni-corrected post hoc tests for multiple comparisons; p < 0.05, two-tailed test).
Figure 2.
Figure 2.. Correlations of vascular BRS (vBRS) with hemodynamic and HRV parameters across beat delays relative to the SAP peak.
The hemodynamic parameters analyzed include systolic arterial pressure (SAP), systemic vascular resistance (SVR), cardiac output (CO), maximal rate of pulse pressure changes over time (dP/dt), interbeat interval (IBI), root mean square of successive differences in heart rate (RMSSD), and the low-frequency to high-frequency HRV ratio (LF/HF). Dots represent Spearman’s correlation coefficients. *Significant correlations are indicated at five beat delays; the significance level was adjusted for multiple comparisons with α = 0.01 (two-tailed test). For correlations involving five beat delays and two HRV parameters (RMSSD and LF/HF), the significance level was further adjusted to α = 0.005 (two-tailed test).
Figure 3.
Figure 3.. Correlations of myocardial BRS (mBRS) with hemodynamic and HRV parameters across beat delays relative to the SAP peak.
The hemodynamic parameters analyzed include systolic arterial pressure (SAP), systemic vascular resistance (SVR), cardiac output (CO), maximal rate of pulse pressure changes over time (dP/dt), interbeat interval (IBI), root mean square of successive differences in heart rate (RMSSD), and the low-frequency to high-frequency HRV ratio (LF/HF). Dots represent Spearman’s correlation coefficients. *Significant correlations are indicated at five beat delays; the significance level was adjusted for multiple comparisons with α = 0.01 (two-tailed test).
Figure 4.
Figure 4.. Correlations of BRS for cardiac output (coBRS) with hemodynamic and HRV parameters across beat delays relative to the SAP peak.
The hemodynamic parameters analyzed include systolic arterial pressure (SAP), systemic vascular resistance (SVR), cardiac output (CO), maximal rate of pulse pressure changes over time (dP/dt), interbeat interval (IBI), root mean square of successive differences in heart rate (RMSSD), and the low-frequency to high-frequency HRV ratio (LF/HF). Dots represent Spearman’s correlation coefficients. *Significant correlations are indicated at five beat delays; the significance level was adjusted for multiple comparisons with α = 0.01 (two-tailed test).
Figure 5.
Figure 5.. Correlations of BRS for interbeat interval (ibiBRS) with hemodynamic and HRV parameters across beat delays relative to the SAP peak.
The hemodynamic parameters analyzed include systolic arterial pressure (SAP), systemic vascular resistance (SVR), cardiac output (CO), maximal rate of pulse pressure changes over time (dP/dt), interbeat interval (IBI), root mean square of successive differences in heart rate (RMSSD), and the low-frequency to high-frequency HRV ratio (LF/HF). Dots represent Spearman’s correlation coefficients. *Significant correlations are indicated at five beat delays; the significance level was adjusted for multiple comparisons with α = 0.01 (two-tailed test). For correlations involving five beat delays and two HRV parameters (RMSSD and LF/HF), the significance level was further adjusted to α = 0.005 (two-tailed test).
Figure 6.
Figure 6.. Impact of Postural Changes on Peak BRS, BEI, and SQ Values.
This figure illustrates the effects of postural changes—from supine to standing—on various types of baroreflex sensitivity (BRS): vascular (vBRS), myocardial (mBRS), cardiac output (coBRS), and heart rate (ibiBRS) across beat delays of 0, 1, 2, 3, and 6. Each panel shows BRS values (mean ± 95% confidence interval). Colored lines contain statistically significant values, with asterisks denoting significant differences compared to the lowest data point in the line (repeated measures one-way ANOVA, followed by Bonferroni-corrected post hoc tests for multiple comparisons; p < 0.05, two-tailed test).
Figure 7.
Figure 7.. Impact of Postural Changes on Different BRS Types.
This figure illustrates the effects of postural changes—from lying down to standing—on various types of baroreflex sensitivity (BRS): vascular (vBRS), myocardial (mBRS), cardiac output (coBRS), and interbeat interval (ibiBRS) across beat delays of 0, 1, 2, 3, and 6. Each panel shows BRS values (mean ± 95% confidence interval) in both lying down (gray lines) and standing (black, red, and blue lines) positions. Red and blue lines in the standing position indicate a statistically significant main effect of position, highlighting differences compared to the corresponding beat delay value in the lying down position (repeated measures two-way ANOVA, followed by Bonferroni-corrected post hoc tests for multiple comparisons; p < 0.05, two-tailed test).
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References

    1. Båth E., Lindblad L.E., Wallin B.G. 1981. Effects of dynamic and static neck suction on muscle nerve sympathetic activity, heart rate and blood pressure in man. J Physiol 311, 551–564. - PMC - PubMed
    1. Berntson G.G., Bigger J.T. Jr., Eckberg D.L., Grossman P., Kaufmann P.G., Malik M., Nagaraja H.N., Porges S.W., Saul J.P., Stone P.H., van der Molen M.W. 1997. Heart rate variability: origins, methods, and interpretive caveats. Psychophysiology 34, 623–648. - PubMed
    1. Bertinieri G., di Rienzo M., Cavallazzi A., Ferrari A.U., Pedotti A., Mancia G. 1985. A new approach to analysis of the arterial baroreflex. J Hypertens Suppl 3, S79–81. - PubMed
    1. Borgers A.J., van den Born B.J., Alkemade A., Eeftinck Schattenkerk D.W., van Lieshout J.J., Wesseling K.H., Bisschop P.H., Westerhof B.E. 2014. Determinants of vascular and cardiac baroreflex sensitivity values in a random population sample. Med Biol Eng Comput 52, 65–73. - PubMed
    1. Chao-Ecija A., Dawid-Milner M.S. 2023. BaroWavelet: An R-based tool for dynamic baroreflex evaluation through wavelet analysis techniques. Comput Methods Programs Biomed 242, 107758. - PubMed

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