AUTHOR=Sanders Marit L. , Elting Jan Willem J. , Panerai Ronney B. , Aries Marcel , Bor-Seng-Shu Edson , Caicedo Alexander , Chacon Max , Gommer Erik D. , Van Huffel Sabine , Jara José L. , Kostoglou Kyriaki , Mahdi Adam , Marmarelis Vasilis Z. , Mitsis Georgios D. , Müller Martin , Nikolic Dragana , Nogueira Ricardo C. , Payne Stephen J. , Puppo Corina , Shin Dae C. , Simpson David M. , Tarumi Takashi , Yelicich Bernardo , Zhang Rong , Claassen Jurgen A. H. R. TITLE=Dynamic Cerebral Autoregulation Reproducibility Is Affected by Physiological Variability JOURNAL=Frontiers in Physiology VOLUME=10 YEAR=2019 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2019.00865 DOI=10.3389/fphys.2019.00865 ISSN=1664-042X ABSTRACT=
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 (