Cerebral autoregulation is the intrinsic ability of the brain to maintain adequate cerebral perfusion in the presence of blood pressure changes. A large number of methods to assess the quality of cerebral autoregulation have been proposed over the last 30 years. However, no single method has been universally accepted as a gold standard. Therefore, the choice of which method to employ to quantify cerebral autoregulation remains a matter of personal choice. Nevertheless, given the concept that cerebral autoregulation represents the dynamic relationship between blood pressure (stimulus or input) and cerebral blood flow (response or output), transfer function analysis became the most popular approach adopted in studies based on spontaneous fluctuations of blood pressure. Despite its sound theoretical background, the literature shows considerable variation in implementation of transfer function analysis in practice, which has limited comparisons between studies and hindered progress towards clinical application. Therefore, the purpose of the present white paper is to improve standardisation of parameters and settings adopted for application of transfer function analysis in studies of dynamic cerebral autoregulation. The development of these recommendations was initiated by (but not confined to) theCerebral Autoregulation Research Network(CARNet -www.car-net.org).

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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.

Failure to recover from BP decline in the first minute after active standing up is associated with excess mortality in falls clinic patients. A recovery of systolic BP to less than 80% of baseline after 60 seconds may be used as an easily available cardiovascular marker for increased mortality risk in older falls clinic patients.