Cardiorespiratory synchronisation and systolic blood pressure correlation of peripheral arterial stiffness during endoscopic thoracic sympathectomy

Abstract Muscle sympathetic nerve activity (MSNA) is known as an effective measure to evaluate peripheral sympathetic activity; however, it requires invasive measurement with the microneurography method. In contrast, peripheral arterial stiffness affected by MSNA is a measure that allows non-invasiv...

Full description

Saved in:
Bibliographic Details
Main Authors: Toshifumi Muneyasu, Harutoyo Hirano, Akira Furui, Zu Soh, Ryuji Nakamura, Noboru Saeki, Yoshiyuki Okada, Masashi Kawamoto, Masao Yoshizumi, Atsuo Yoshino, Takafumi Sasaoka, Shigeto Yamawaki, Toshio Tsuji
Format: article
Language:EN
Published: Nature Portfolio 2021
Subjects:
R
Q
Online Access:https://doaj.org/article/92d9cfe6c10e48809a75ba91d5fa79ea
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Muscle sympathetic nerve activity (MSNA) is known as an effective measure to evaluate peripheral sympathetic activity; however, it requires invasive measurement with the microneurography method. In contrast, peripheral arterial stiffness affected by MSNA is a measure that allows non-invasive evaluation of mechanical changes of arterial elasticity. This paper aims to clarify the features of peripheral arterial stiffness to determine whether it inherits MSNA features towards non-invasive evaluation of its activity. To this end, we propose a method to estimate peripheral arterial stiffness $$\beta$$ β at a high sampling rate. Power spectral analysis of the estimated $$\beta$$ β was then performed on data acquired from 15 patients ( $$23.7 \pm 9.0$$ 23.7 ± 9.0 years) who underwent endoscopic thoracic sympathectomy. We examined whether $$\beta$$ β exhibited the features of MSNA where its frequency components synchronise with heart and respiration rates and correlates with the low-frequency component of systolic blood pressure. Regression analysis revealed that the local peak frequency in the range of heartbeat frequency highly correlate with the heart rate ( $$R^{2}=0.85$$ R 2 = 0.85 , $$p=6.3\times 10^{-13}$$ p = 6.3 × 10 - 13 ) where the regression slope was approximately 1 and intercept was approximately 0. Frequency analysis then found spectral peaks of $$\beta$$ β approximately 0.2 Hz that correspond to the respiratory cycle. Finally, cross power spectral analysis showed a significant magnitude squared coherence between $$\beta$$ β and systolic blood pressure in the frequency band from 0.04 to 0.2 Hz. These results indicate that $$\beta$$ β inherits the features observed in MSNA that require invasive measurements, and thus $$\beta$$ β can be an effective non-invasive substitution for MSNA measure.