Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure–flow relation: The CARNet study

Abstract

Transfer function analysis (TFA) is a frequently used method to assess dynamic cerebral autoregulation (CA) using spontaneous oscillations in blood pressure (BP) and cerebral blood flow velocity (CBFV). However, controversies and variations exist in how research groups utilise TFA, causing high variability in interpretation. The objective of this study was to evaluate between-centre variability in TFA outcome metrics. 15 centres analysed the same 70 BP and CBFV datasets from healthy subjects (n = 50 rest; n = 20 during hypercapnia); 10 additional datasets were computer-generated. Each centre used their in-house TFA methods; however, certain parameters were specified to reduce a priori between-centre variability. Hypercapnia was used to assess discriminatory performance and synthetic data to evaluate effects of parameter settings. Results were analysed using the Mann–Whitney test and logistic regression. A large non-homogeneous variation was found in TFA outcome metrics between the centres. Logistic regression demonstrated that 11 centres were able to distinguish between normal and impaired CA with an AUC > 0.85. Further analysis identified TFA settings that are associated with large variation in outcome measures. These results indicate the need for standardisation of TFA settings in order to reduce between-centre variability and to allow accurate comparison between studies. Suggestions on optimal signal processing methods are proposed.

The Leicester cerebral haemodynamics database: normative values and the influence of age and sex

“…Secondly, it has been nearly impossible to pool together different studies to increase the statistical power of estimates due to the considerable diversity of methods used by different centres (Meel-van den Abeelen et al 2014b). The recent proposal to improve standardisation of these methods (Claassen et al 2016, Meel-van den Abeelen et al 2014a, should bear fruit in the near future, but in the meantime alternative approaches are needed. To address these two main limitations, the Department of Cardiovascular Sciences, University of Leicester, UK, has constructed a large database incorporating recordings from a series of separate studies that were all performed in the same laboratory, using similar protocols and equipment.…”

The Effects of Flumazenil After Midazolam Sedation on Cerebral Blood Flow and Dynamic Cerebral Autoregulation in Healthy Young Males

“…12,13,18 Moreover, dynamic cerebral autoregulation can be evaluated over a wide time range (from about 3 s to about 1 min) by assessing changes in arterial pressure using spectral and transfer function analysis. 19 The other methods that induce MAP changes (eg, leg cuff deflation method) calculate autoregulation indices only from "a momentary (a few seconds)" reduction in arterial pressure.…”

Further understanding of cerebral autoregulation at the bedside: possible implications for future therapy

“…In a speculative 5-year view of autoregulation research, we propose progress in several key areas. From a methodological viewpoint, improving the reproducibility of our autoregulation assessments and analytical methods is essential and necessitates widespread cooperation and large data sets [111]. From a bioinformatics point of view, improving the diversity, frequency and quality of both physiological and clinical data will undoubtedly improve understanding of how cerebral autoregulation interacts with cerebral metabolism, cardio-respiratory control, biochemical homeostasis, as well as clinical interventions.…”