Low-frequency variability in photoplethysmographic waveform and heart rate during on-pump cardiac surgery with or without cardioplegia

Abstract

We studied the properties of low-frequency (LF) heart rate variability (HRV) and photoplethysmographic waveform variability (PPGV) and their interaction under conditions where the hemodynamic connection between them is obviously absent, as well as the LF regulation of PPGV in the absence of heart function. The parameters of HRV and finger PPGV were evaluated in 10 patients during cardiac surgery under cardiopulmonary bypass (on-pump cardiac surgery) with or without cardioplegia. The following spectral indices of PPGV and HRV were ertimated: the total spectral power (TP), the highfrequency (HF) and the LF ranges of TP in percents (HF% and LF%), and the LF/HF ratio. We assessed also the index S of synchronization between the LF oscillations in finger photoplethysmogram (PPG) and heart rate (HR) signals. the analysis of directional couplings was carried out using the methods of phase dynamics modeling. it is shown that the mechanisms leading to the occurrence of oscillations in the LF range of PPGV are independent of the mechanisms causing oscillations in the LF range of HRV. At the same time, the both above-mentioned LF oscillations retain their activity under conditions of artificial blood circulation and cardioplegia (the latter case applies only to LF oscillations in PPG). In artificial blood circulation, there was a coupling from the LF oscillations in PPG to those in HR, whereas the coupling in the opposite direction was absent. the coupling from the Lf oscillations in ppG to those in HR has probably a neurogenic nature, whereas the opposite coupling has a hemodynamic nature (due to cardiac output).Despite the relatively widespread use of photoplethysmography to assess the state of peripheral blood flow 1,2 , the question of the physiological interpretation of the frequency components of photoplethysmographic waveform variability (PPGV) remains largely debatable. Usually, the nature of high-frequency (HF) oscillations in photoplethysmogram (PPG) signal is explained by the mechanical effect of respiration 3-5 , while the low-frequency (LF) oscillations (with a characteristic frequency of about 0.1 Hz) in PPG are associated with sympathetic regulation of peripheral vascular resistance 3,6,7 . It should be noted that besides the PPG, the LF fluctuations at a similar frequency are detected also in the signals of heart rate (HR) 8,9 and blood pressure (BP) 10,11 . Blood pressure variability (BPV) is primarily due to the vasomotor tone, which is not directly related to the heart control. Since blood flow through the distal arteries contributes to the formation of the finger PPG 12 , the autonomic regulation of BP can be indirectly assessed by the PPG signal.

Mathematical modeling of the cardiovascular autonomic control in healthy subjects during a passive head-up tilt test

“…However, some experimental results 44 suggest the functional independence of the LF oscillations in RR-intervals and PPG. Earlier, we also observed the phenomenon of the synchronization between the LF oscillations in RR-intervals and PPG 30,33,48 . Typically, the intervals of synchronization are alternating with the intervals of the desynchronized behavior.…”

“…It is known that PPG allows indirect estimation of the frequency properties of arterial pressure variability (APV), since PPG signal is influenced to a strong degree by oscillations of AP 31 . Also, we demonstrated a perspective clinical application of LF oscillation synchronization to the estimation of fatal cardiovascular risk after myocardial infarction 32,33 , and to the personalization of medical therapy for myocardial infarction patients 34 and hypertensive patients 35 .…”

Simulating Dynamics of Circulation in the Awake State and Different Stages of Sleep Using Non-autonomous Mathematical Model With Time Delay

“…We have proposed a mathematical model that allows one to simulate the heart rate variability and arterial pressure oscillations under the influence of respiration and autonomic control loops. Earlier, it was shown that taking into account the non-linear properties and self-oscillatory dynamics of these loops it is possible to explain the experimentally observed complex chaotic dynamics of the heart rate and synchronization processes within the CVS ( Ringwood and Malpas, 2000 ; Prokhorov et al, 2003 ; Karavaev et al, 2009 , 2016 , 2019 ; Kiselev et al, 2016a , 2020 ). In the present paper, a modified model is proposed that takes into account the influence of the activity of the cerebral cortex on autonomic control in the states of sleep and wakefulness.…”

“…As well as our earlier models, it reproduces the pathological changes that lead to arterial hypertension ( Karavaev et al, 2016 ), reaction to the passive orthostatic test ( Ishbulatov et al, 2018 ), and reaction to the autonomic blockade due to administration of Arfonad ( Karavaev et al, 2016 ). Moreover, the model simulates the chaotic dynamics of heart rate ( Karavaev et al, 2019 ) and phase synchronization between the autonomic control loops ( Ishbulatov et al, 2017 ), which is observed in humans ( Bartsch et al, 2012 ) and is important for diagnostics and understanding of some circulatory diseases ( Prokhorov et al, 2003 ; Kiselev et al, 2016a , b , 2020 ).…”

Vascular origins of low-frequency oscillations in the cerebrospinal fluid signal in resting-state fMRI: Interpretation using photoplethysmography

“…The results of the studies showed significant correlations between HRV and fMRI data (C. . Kiselev et al found that LF oscillations in PPG that lag LF HRV is likely to have a neurogenic nature, whereas HRV changes driven by LF PPG changes are likely to have a hemodynamic nature (due to cardiac output) (Kiselev et al, 2020).…”