Reproducibility of dynamic cerebral autoregulation Introduction Under normal conditions, despite variations in cerebral perfusion pressure (CPP), cerebral blood flow is kept relatively constant in correspondence with the metabolic needs of the brain. The control mechanism that compensates for CPP variations is called cerebral autoregulation 2, 19, 24. Various methods have been described to characterize this control system. A sudden step-wise decrease in arterial blood pressure evokes a response, characterized by a few seconds lasting decreased flow followed by a relatively slow return to the base level. This CBFV- response can be interpreted as a kind of step-response of the control system and can be quantified by the so-called autoregulatory index (ARI) 30 ranging be- tween 0 and 9. Another approach to quantify the dynamics of cerebral autoregu- lation (dCA) 4, 22, 33 is transfer function analysis (TFA) of the presumed linear control system with arterial blood pressure (ABP) as the input and cerebral blood flow velocity (CBFV) as the output signal. The transfer function gain and phase are estimated from the auto- and cross spectra of ABP and CBFV and the strength of the linear relation between ABP and CBFV is expressed in the sys- tem’s coherence. From the step response function resulting from this transfer function the system’s ARI can be determined using least squares estimation. For each of the ten ARI responses the sum of squared differences with the TFA response is determined. A parabolic interpolation through these ten values can be performed to estimate the value of ARI to one decimal space 23 at the minimum of the parabola. A recently published and different approach to overcome some difficulties with Fourier-based spectral analysis is the multimodal pressure flow (MMPF) analysis 15, 20. The authors showed that MMPF analysis may be less sensitive to prob- lems with data non-stationarities and trends 15. In a study on traumatic brain injury patients better reproducibility was shown with MMPF phase compared to ARI 11. Also non-linear approaches have been tried to evaluate dCA 13, 17, but clear benefits have not been shown yet. A limiting factor in (clinical) use of quantitative dCA is the high variability ob- served in calculated parameters, such as gain, phase and ARI 6, 16, 23, 27. This high variability is likely to limit reproducibility of these measurements. Brodie et al 6 showed poor ARI reproducibility with an intraclass correlation (ICC) below 0.5. It is unknown if reproducibility may be influenced by procedural and methodological options. Currently, there is neither a procedural nor a methodological standard to com- pute dCA. A procedural aspect is the choice between using spontaneous 22, 33 and induced blood pressure variations e.g. by paced breathing at a frequency of 21
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