Estimating confidence intervals for cerebral autoregulation: a parametric bootstrap approach
Estimating confidence intervals for cerebral autoregulation: a parametric bootstrap approach
Cerebral autoregulation (CA) refers to the ability of the brain vasculature to control blood flow in the face of changing blood pressure. One of the methods commonly used to assess cerebral autoregulation, especially in participants at rest, is the analysis of phase derived from transfer function analysis (TFA), relating arterial blood pressure (ABP) to cerebral blood flow (CBF). This and other indexes of CA can provide consistent results when comparing groups of subjects (e.g. patients and healthy controls or normocapnia and hypercapnia) but can be quite variable within and between individuals. The objective of this paper is to present a novel parametric bootstrap method, used to estimate the sampling distribution and hence confidence intervals (CIs) of the mean phase estimate in the low-frequency band, in order to optimise estimation of measures of CA function and allow more robust inferences on the status of CA from individual recordings. A set of simulations was used to verify the proposed method under controlled conditions. In 20 healthy adult volunteers (age 25.53.5 years), ABP and CBF velocity (CBFV) were measured at rest, using a Finometer device and Transcranial Doppler (applied to the middle cerebral artery), respectively. For each volunteer, five individual recordings were taken on different days, each approximately 18 min long. Phase was estimated using TFA. Analysis of recorded data showed widely changing CIs over the duration of recordings, which could be reduced when noisy data and frequencies with low coherence were excluded from the analysis (Wilcoxon signed rank test p = 0.0065). The TFA window-lengths of 50s gave smaller CIs than lengths of 100s (p < 0.001) or 20s (p < 0.001), challenging the usual recommendation of 100s. The method adds a much needed flexible statistical tool for CA analysis in individual recordings.
Blood pressure, Bootstrap, Cerebral autoregulation, Cerebral blood flow, Confidence intervals, Phase estimates, Physiological model estimation
Bryant, Jack, Edward Douglas
048e7b16-56e7-4697-9838-0a1ef7ad8d71
Birch, Anthony
755f2236-4c0c-49b5-9884-de4021acd42d
Panerai, Ronney B.
7acaf714-a17c-4df2-a1f3-b148c1445517
Nikolic, Dragana
772b3eb2-c994-440a-ab86-27e862bd39f7
Bulters, Diederik
d6f9644a-a32f-45d8-b5ed-be54486ec21d
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
1 October 2021
Bryant, Jack, Edward Douglas
048e7b16-56e7-4697-9838-0a1ef7ad8d71
Birch, Anthony
755f2236-4c0c-49b5-9884-de4021acd42d
Panerai, Ronney B.
7acaf714-a17c-4df2-a1f3-b148c1445517
Nikolic, Dragana
772b3eb2-c994-440a-ab86-27e862bd39f7
Bulters, Diederik
d6f9644a-a32f-45d8-b5ed-be54486ec21d
Simpson, David
53674880-f381-4cc9-8505-6a97eeac3c2a
Bryant, Jack, Edward Douglas, Birch, Anthony, Panerai, Ronney B., Nikolic, Dragana, Bulters, Diederik and Simpson, David
(2021)
Estimating confidence intervals for cerebral autoregulation: a parametric bootstrap approach.
Physiological Measurement, 42 (10), [104004].
(doi:10.1088/1361-6579/ac27b8).
Abstract
Cerebral autoregulation (CA) refers to the ability of the brain vasculature to control blood flow in the face of changing blood pressure. One of the methods commonly used to assess cerebral autoregulation, especially in participants at rest, is the analysis of phase derived from transfer function analysis (TFA), relating arterial blood pressure (ABP) to cerebral blood flow (CBF). This and other indexes of CA can provide consistent results when comparing groups of subjects (e.g. patients and healthy controls or normocapnia and hypercapnia) but can be quite variable within and between individuals. The objective of this paper is to present a novel parametric bootstrap method, used to estimate the sampling distribution and hence confidence intervals (CIs) of the mean phase estimate in the low-frequency band, in order to optimise estimation of measures of CA function and allow more robust inferences on the status of CA from individual recordings. A set of simulations was used to verify the proposed method under controlled conditions. In 20 healthy adult volunteers (age 25.53.5 years), ABP and CBF velocity (CBFV) were measured at rest, using a Finometer device and Transcranial Doppler (applied to the middle cerebral artery), respectively. For each volunteer, five individual recordings were taken on different days, each approximately 18 min long. Phase was estimated using TFA. Analysis of recorded data showed widely changing CIs over the duration of recordings, which could be reduced when noisy data and frequencies with low coherence were excluded from the analysis (Wilcoxon signed rank test p = 0.0065). The TFA window-lengths of 50s gave smaller CIs than lengths of 100s (p < 0.001) or 20s (p < 0.001), challenging the usual recommendation of 100s. The method adds a much needed flexible statistical tool for CA analysis in individual recordings.
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Bryant_2021_Physiol._Meas._42_104004
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Accepted/In Press date: 17 September 2021
Published date: 1 October 2021
Additional Information:
Publisher Copyright:
© 2021 Institute of Physics and Engineering in Medicine
Keywords:
Blood pressure, Bootstrap, Cerebral autoregulation, Cerebral blood flow, Confidence intervals, Phase estimates, Physiological model estimation
Identifiers
Local EPrints ID: 453058
URI: http://eprints.soton.ac.uk/id/eprint/453058
ISSN: 0967-3334
PURE UUID: 0dae2ba5-c182-41c2-8e8d-8824284b2e0f
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Date deposited: 07 Jan 2022 17:49
Last modified: 17 Mar 2024 03:51
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