Lack of linear correlation between dynamic and steady‐state cerebral autoregulation

Jong, Daan L.K. de; Tarumi, Takashi; Liu, Jie; Zhang, Rong; Claassen, Jurgen A.H.R.

doi:10.1113/jp274304

Cited by 30 publications

(34 citation statements)

References 61 publications

(72 reference statements)

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“…In contrast, an absence of linear relationship between metrics of static and dynamic cerebral autoregulation has been reported in aged adults (de Jong et al. ). The different populations and methodologies and the drugs used in these studies are possible explanations for this discrepancy.…”

Section: Discussionmentioning

confidence: 97%

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Dynamic cerebral autoregulation is preserved during isometric handgrip and head-down tilt in healthy volunteers

2018

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In healthy humans, cerebral blood flow (CBF) is autoregulated against changes in arterial blood pressure. Spontaneous fluctuations in mean arterial pressure (MAP) and CBF can be used to assess cerebral autoregulation. We hypothesized that dynamic cerebral autoregulation is affected by changes in autonomic activity, MAP, and cardiac output (CO) induced by handgrip (HG), head‐down tilt (HDT), and their combination. In thirteen healthy volunteers, we recorded blood velocity by ultrasound in the internal carotid artery (ICA), HR, MAP and CO‐estimates from continuous finger blood pressure, and end‐tidal CO 2. Instantaneous ICA beat volume (ICABV, mL) and ICA blood flow (ICABF, mL/min) were calculated. Wavelet synchronization index γ (0–1) was calculated for the pairs: MAP–ICABF, CO–ICABF and HR–ICABV in the low (0.05–0.15 Hz; LF) and high (0.15–0.4 Hz; HF) frequency bands. ICABF did not change between experimental states. MAP and CO were increased during HG (+16% and +15%, respectively, P < 0.001) and during HDT + HG (+12% and +23%, respectively, P < 0.001). In the LF interval, median γ for the MAP–ICABF pair (baseline: 0.23 [0.12–0.28]) and the CO–ICABF pair (baseline: 0.22 [0.15–0.28]) did not change with HG, HDT, or their combination. High γ was observed for the HR–ICABV pair at the respiratory frequency, the oscillations in these variables being in inverse phase. The unaltered ICABF and the low synchronization between MAP and ICABF in the LF interval suggest intact dynamic cerebral autoregulation during HG, HDT, and their combination.

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Section: Discussionmentioning

confidence: 97%

“…It is also possible that different mechanisms control cerebrovascular resistance and the CBF response to arterial blood pressure changes over different time scales (de Jong et al. ).…”

Section: Discussionmentioning

confidence: 99%

Dynamic cerebral autoregulation is preserved during isometric handgrip and head-down tilt in healthy volunteers

2018

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“…This is consistent with recent work showing that static and dynamic indices are not correlated in healthy older adults (de Jong et al . ), suggesting that they could indeed be different reflexes. Our prior work showed an effect of calcium channel blockade at 0.03 Hz oscillatory LBNP, although not at higher frequencies (Tan et al .…”

Section: Discussionmentioning

confidence: 99%

Revisiting human cerebral blood flow responses to augmented blood pressure oscillations

Hamner

Ishibashi

Tan

2019

The Journal of Physiology

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Key points Cerebral autoregulation is most effective in buffering against pressure fluctuations slower than 0.03 Hz (∼30 s). This suggests that frequency bands for characterizing cerebral autoregulation should be redefined Low cross‐spectral coherence below 0.03 Hz highlights the limitations of transfer function approaches Haemodynamic changes induced by lower body pressure could not fully explain the differences in autoregulation estimated from spontaneous vs. augmented fluctuations, and thus, observations of spontaneous fluctuations should not be relied on whenever possible. Abstract There is currently little empirical basis for time scales that are considered to be most significant in cerebrovascular counter‐regulation of changes in arterial pressure. Although it is well established that cerebral autoregulation behaves as a ‘high‐pass’ filter, recommended frequency bands have been largely arbitrarily determined. To test effectiveness of cerebral autoregulation, we refined oscillatory lower body pressure (LBP) to augment resting pressure fluctuations below 0.1 Hz by a factor of two in 13 young male volunteers, and thoroughly characterized the time and frequency responses of cerebral autoregulation. We observed that despite a threefold increase in arterial pressure power <0.03 Hz with oscillatory LBP, there was no change in cerebral blood flow power, indicating near perfect counter‐regulation. By contrast, in the range 0.03–0.10 Hz, both cerebral blood flow and arterial pressure power more than doubled. Our data demonstrate that cerebral autoregulation is most effective in buffering against pressure fluctuations slower than 0.03 Hz (∼30 s). This suggests that frequency bands of interest should be redefined and recording length should be increased considerably to account for this. Furthermore, low cross‐spectral coherence below 0.03 Hz, even when pressure fluctuations were augmented, highlights the uncertainty in transfer function approaches and the need to either report precision or use non‐linear approaches. Finally, haemodynamic changes induced by LBP could not fully explain the differences in autoregulation estimated from spontaneous vs. augmented fluctuations, and thus, observations of spontaneous fluctuations should not be relied on whenever possible.

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“…; de Jong et al . ). Invention of the pressure reactivity index (PRx), calculated as a moving correlation coefficient between ABP and ICP, has allowed for continuous monitoring of CA over extended periods of time (Czosnyka et al .…”

Section: Introductionmentioning

confidence: 97%

“…The interrelationship between arterial blood pressure (ABP), intracranial pressure (ICP) and cerebral arterial blood flow velocity (FV) provides information about functioning of CA (Aaslid et al 1986;Shigemori et al 1989;Giller, 1990;Chan et al 1992;Schmidt et al 1999;de Jong et al 2017). Invention of the pressure reactivity index (PRx), calculated as a moving correlation coefficient between ABP and ICP, has allowed for continuous monitoring of CA over extended periods of time (Czosnyka et al 1997).…”

Section: Introductionmentioning

confidence: 99%

Wavelet pressure reactivity index: a validation study

Liu

Czosnyka

Donnelly

et al. 2018

The Journal of Physiology

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We present a novel method to monitor cerebral autoregulation (CA) using the wavelet transform (WT). The new method is validated against the pressure reactivity index (PRx) in two piglet experiments with controlled hypotension. The first experiment (n = 12) had controlled haemorrhage with artificial stationary arterial blood pressure (ABP) and intracranial pressure (ICP) oscillations induced by sinusoidal slow changes in positive end-expiratory pressure ('PEEP group'). The second experiment (n = 17) had venous balloon inflation during spontaneous, non-stationary ABP and ICP oscillations ('non-PEEP group'). The wavelet transform phase shift (WTP) between ABP and ICP was calculated in the frequency range 0.0067-0.05 Hz. Wavelet semblance, the cosine of WTP, was used to make the values comparable to PRx, and the new index was termed wavelet pressure reactivity index (wPRx). The traditional PRx, the running correlation coefficient between ABP and ICP, was calculated. The result showed a significant linear relationship between wPRx and PRx in the PEEP group (R = 0.88) and non-PEEP group (R = 0.56). In the non-PEEP group, wPRx showed better performance than PRx in distinguishing cerebral perfusion pressure (CPP) above and below the lower limit of autoregulation (LLA). When CPP was decreased below LLA, wPRx increased from 0.43 ± 0.28 to 0.69 ± 0.12 (P = 0.003) while PRx increased from 0.07 ± 0.21 to 0.27 ± 0.37 (P = 0.04). Moreover, wPRx provided a more stable result than PRx (SD of PRx was 0.40 ± 0.07, and SD of wPRx was 0.28 ± 0.11, P = 0.001). Assessment of CA using wavelet-derived phase shift between ABP and ICP is feasible.

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Lack of linear correlation between dynamic and steady‐state cerebral autoregulation

Cited by 30 publications

References 61 publications

Dynamic cerebral autoregulation is preserved during isometric handgrip and head-down tilt in healthy volunteers

Dynamic cerebral autoregulation is preserved during isometric handgrip and head-down tilt in healthy volunteers

Revisiting human cerebral blood flow responses to augmented blood pressure oscillations

Wavelet pressure reactivity index: a validation study

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