Disorders of Synchronization of Blood Pressure and Heart Rate Precede the Development of Vasovagal Syncope during Orthostasis

Боровик, А. С.; Negulyaev, V. O.; Tarasova, O. S.; Kheymets, G I; Певзнер, А В; Ермишкин, В. В.; Рогоза, А. Н.; Виноградова, О. Л.

doi:10.1134/s0362119719040029

Cited by 6 publications

(6 citation statements)

References 21 publications

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“…Phase synchronization of baroreflex blood pressure and MSNA oscillations disappears in patients with vasovagal syncope during head-up tilt test a few minutes before the drop in blood pressure (Schwartz et al, 2013a). Regarding the phase synchronization of blood pressure and HR during syncope, we showed, for the first time, that the absence of PSI increase at an early stage of the head-up tilt test is associated with subsequent decompensation of hemodynamics and orthostatic intolerance (Borovik et al, 2019). These results suggest PSI of blood pressure and HR to be an informative measure of baroreflex activity in humans exposed to conditions of simulated or real microgravity.…”

Section: Introductionmentioning

confidence: 66%

“…Violation of baroreflex control was detected already on the 7th day of exposure to dry immersion, persisted during the entire period of exposure and in the early recovery period (1st day). It should be noted that the absence of changes in the PSI in the baroreflex frequency range with a change in body position in the tilt test is typical for patients with fainting of a vasovagal nature (Borovik et al, 2019). Thus, our novel method can be used for assessing orthostasis-induced changes in baroreflex activity in the conditions of microgravity and in the development of countermeasures aimed at preventing orthostatic intolerance that occurs in cosmonauts/astronauts when they return to Earth's gravity.…”

Section: Resultsmentioning

confidence: 97%

“…To evaluate the changes in the cardiac baroreflex during simulated gravitational unloading, we used a novel approach based on estimation of the phase relations of BP and HR fluctuations in the frequency range of baroreflex waves (Borovik et al, 2014(Borovik et al, , 2019Negulyaev et al, 2019). Importantly, the observed changes in cardiac baroreflex sensitivity during orthostasis depend on the method of assessing baroreflex activity.…”

Section: Discussionmentioning

confidence: 99%

“…Noteworthy, the complex dynamics of physiological signals is also determined by their phase relationships. In this study, we introduce a novel approach to the assessment of baroreflex activity, based on the calculation of the phase relations of blood pressure and HR oscillations at the frequency of baroreflex waves using the phase synchronization index (PSI) (Borovik et al, 2014(Borovik et al, , 2019Negulyaev et al, 2019). This method of analysis has several important advantages, since it provides more stable results than traditional methods (such as cross-spectral analysis) and does not require long continuous recording (Negulyaev et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Phase Coupling Between Baroreflex Oscillations of Blood Pressure and Heart Rate Changes in 21-Day Dry Immersion

et al. 2020

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Introduction: Dry immersion (DI) is a ground-based experimental model which reproduces the effects of microgravity on the cardiovascular system and, therefore, can be used to study the mechanisms of post-flight orthostatic intolerance in cosmonauts. However, the effects of long-duration DI on cardiovascular system have not been studied yet. The aim of this work was to study the effects of 21-day DI on systemic hemodynamics and its baroreflex control at rest and during head-up tilt test (HUTT). Methods: Ten healthy young men were exposed to DI for 21 days. The day before, on the 7th, 14th, and 19th day of DI, as well as on the 1st and 5th days of recovery they were subjected to HUTT: 15 min in supine position and then 15 min of orthostasis (60 •). ECG, arterial pressure, stroke volume and respiration rate were continuously recorded during the test. Phase synchronization index (PSI) of beat-to-beat mean arterial pressure (MAP) and heart rate (HR) in the frequency band of baroreflex waves (∼0.1 Hz) was used as a quantitative measure of baroreflex activity. Results: During DI, strong tachycardia and the reduction of stroke volume were observed both in supine position and during HUTT, these indicators did not recover on post-immersion day 5. In contrast, systolic arterial pressure and MAP decreased during HUTT on 14th day of DI, but then restored to pre-immersion values. Before DI and on day 5 of recovery, a transition from supine position to orthostasis was accompanied by an increase in PSI at the baroreflex frequency. However, PSI did not change in HUTT performed during DI and on post-immersion day 1. The amplitude of MAP oscillations at this frequency were increased by HUTT at all time points, while an increase of respective HR oscillations was absent during DI. Conclusion: 21-day DI drastically changed the hemodynamic response to HUTT, while its effect on blood pressure was reduced between days 14 and 19, which speaks in favor of the adaptation to the conditions of DI. The lack of increase in phase synchronization of baroreflex MAP and HR oscillations during HUTT indicates disorders of baroreflex cardiac control during DI.

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Section: Introductionmentioning

confidence: 66%

Section: Resultsmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Phase Coupling Between Baroreflex Oscillations of Blood Pressure and Heart Rate Changes in 21-Day Dry Immersion

et al. 2020

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“…Here, “P.V” means that the integral is taken in the sense of the Cauchy principal value [ 18 ]. The instantaneous phase ϕ ( t ) and amplitude A ( t ) of the signal s ( t ) are thus uniquely given via the construction of the analytic signal ζ ( t ).…”

Section: Methodsmentioning

confidence: 99%

Parkinson’s Disease Rating Scale Using Synchronization Analysis of Gait Dynamics

Asmarian

Ruzitalab

Erjaee

et al. 2021

BioMed Research International

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Analysis of gait dynamics is a noninvasive and totally painless test, and it can be an ideal method for the diagnosis of neurodegenerative diseases. In this study, based on the strength of synchronization between dynamics of strides, we have suggested a rating scale method for Parkinson’s disease (PD). Methods. The sample included 15 persons with PD (age: 66.8 ± 10.9 years) and 16 healthy persons (age: 39.3 ± 18.5 years) which were recruited from the Neurology Outpatient Clinic at Massachusetts General Hospital and were instructed to walk a 77 m long, straight hallway. The time interval of strides and subphases of strides were measured. Using the Hilbert transformation method, we obtained the data phase and used mean absolute error (MAE) to calculate the synchronization strength of the data phase. Results. In order to check the accuracy of our method, we measured the correlation between our numerical results (MAE) and values of the Hoehn-Yahr scale. Spearman’s rank correlation coefficients ( r ) and the P values were calculated. MAE of left and right stride intervals (LRSI) significantly correlates with the Hoehn-Yahr scale for the subjects with PD (with r = 0.60 and P = 0.025 < 0.05 ). Conclusion. We have revealed that the synchronization weakness of LRSI shows the severity of PD. This method seems to be well suited as a rating scale for people with PD.

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Efficient syncope prediction from resting state clinical data using wavelet bispectrum and multilayer perceptron neural network

Myrovali

Fragakis

Vassilikos

et al. 2021

Med Biol Eng Comput

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Disorders of Synchronization of Blood Pressure and Heart Rate Precede the Development of Vasovagal Syncope during Orthostasis

Cited by 6 publications

References 21 publications

Phase Coupling Between Baroreflex Oscillations of Blood Pressure and Heart Rate Changes in 21-Day Dry Immersion

Phase Coupling Between Baroreflex Oscillations of Blood Pressure and Heart Rate Changes in 21-Day Dry Immersion

Parkinson’s Disease Rating Scale Using Synchronization Analysis of Gait Dynamics

Efficient syncope prediction from resting state clinical data using wavelet bispectrum and multilayer perceptron neural network

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