Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability
journal contributionposted on 05.08.2019 by ML Sanders, JWJ Elting, RB Panerai, M Aries, E Bor-Seng-Shu, A Caicedo, M Chacon, ED Gommers, S Van Huffel, JL Jara, K Kostoglou, A Mandi, VZ Marmarelis, GD Mitsis, M Muller, D Nikolic, RC Nogueira, SJ Payne, C Puppo, DC Shin, DM Simpson, T Tarumi, B Yelicich, R Zhangs, JAHR Claassen
Any type of content formally published in an academic journal, usually following a peer-review process.
Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctuations in blood pressure and cerebral blood flow velocity signals, based on their usual methods of analysis. DCA methods were grouped into three broad categories, depending on output types: (1) transfer function analysis (TFA); (2) autoregulation index (ARI); and (3) correlation coefficient. Only TFA gain in the low frequency (LF) band showed good reproducibility in approximately half of the estimates of gain, defined as an intraclass correlation coefficient (ICC) of >0.6. None of the other DCA metrics had good reproducibility. For TFA-like and ARI-like methods, ICCs were lower than values obtained with surrogate data (p < 0.05). For TFA-like methods, ICCs were lower for the very LF band (gain 0.38 ± 0.057, phase 0.17 ± 0.13) than for LF band (gain 0.59 ± 0.078, phase 0.39 ± 0.11, p ≤ 0.001 for both gain and phase). For ARI-like methods, the mean ICC was 0.30 ± 0.12 and for the correlation methods 0.24 ± 0.23. Based on comparisons with ICC estimates obtained from surrogate data, we conclude that physiological variability or non-stationarity is likely to be the main reason for the poor reproducibility of DCA parameters.