Random squat/stand maneuvers: a novel approach for assessment of dynamic cerebral autoregulation?

A systematic review, meta-analysis and meta-regression amalgamating the driven approaches used to quantify dynamic cerebral autoregulation

Numerous driven techniques have been utilized to assess dynamic cerebral autoregulation (dCA) in healthy and clinical populations. The current review aimed to amalgamate this literature and provide recommendations to create greater standardization for future research. The PubMed database was searched with inclusion criteria consisting of original research articles using driven dCA assessments in humans. Risk of bias were completed using Scottish Intercollegiate Guidelines Network and Methodological Index for Non-Randomized Studies. Meta-analyses were conducted for coherence, phase, and gain metrics at 0.05 and 0.10 Hz using deep-breathing, oscillatory lower body negative pressure (OLBNP), sit-to-stand maneuvers, and squat-stand maneuvers. A total of 113 studies were included, with 40 of these incorporating clinical populations. A total of 4126 participants were identified, with younger adults (18-40 years) being the most studied population. The most common techniques were squat-stands (n = 43), deep-breathing (n = 25), OLBNP (n = 20), and sit-to-stands (n = 16). Pooled coherence point estimates were: OLBNP 0.70 (95%CI:0.59-0.82), sit-to-stands 0.87 (95%CI:0.79-0.95), and squat-stands 0.98 (95%CI:0.98-0.99) at 0.05 Hz; and deep-breathing 0.90 (95%CI:0.81-0.99); OLBNP 0.67 (95%CI:0.44-0.90); and squat-stands 0.99 (95%CI:0.99-0.99) at 0.10 Hz. This review summarizes clinical findings, discusses the pros/cons of the 11 unique driven techniques included, and provides recommendations for future investigations into the unique physiological intricacies of dCA.

Quantification of dynamic cerebral autoregulation: welcome to the jungle!

PURPOSE

Patients with dysautonomia often experience symptoms such as dizziness, syncope, blurred vision and brain fog. Dynamic cerebral autoregulation, or the ability of the cerebrovasculature to react to transient changes in arterial blood pressure, could be associated with these symptoms.

METHODS

In this narrative review, we go beyond the classical view of cerebral autoregulation to discuss dynamic cerebral autoregulation, focusing on recent advances pitfalls and future directions.

RESULTS

Following some historical background, this narrative review provides a brief overview of the concept of cerebral autoregulation, with a focus on the quantification of dynamic cerebral autoregulation. We then discuss the main protocols and analytical approaches to assess dynamic cerebral autoregulation, including recent advances and important issues which need to be tackled.

CONCLUSION

The researcher or clinician new to this field needs an adequate comprehension of the toolbox they have to adequately assess, and interpret, the complex relationship between arterial blood pressure and cerebral blood flow in healthy individuals and clinical populations, including patients with autonomic disorders.

Force sensor reduced measurement error compared with verbal command during sit-to-stand assessment of cerebral autoregulation

Current methods estimate the time delay (TD) before the onset of dynamic cerebral autoregulation (dCA) from verbal command to stand. A force sensor used during a sit-to-stand dCA measure provides an objective moment an individual stands (arise-and-off, AO). We hypothesized that the detection of AO would improve the accuracy of TD compared with estimation. We measured middle cerebral artery blood velocity (MCAv) and mean arterial pressure (MAP) for 60 s sitting followed by 2-min standing, three times separated by 20 min. TD was calculated as the time from: (1) verbal command and (2) AO, until an increase in cerebrovascular conductance index (CVCi = MCAv/MAP). Sixty-five participants were enrolled: young adults (n = 25), older adults (n = 20), and individuals post-stroke (n = 20). The TD calculated from AO (x ¯ $$ \overline{x} $$  = 2.98 ± 1.64 s) was shorter than TD estimated from verbal command (x ¯ $$ \overline{x} $$  = 3.35 ± 1.72 s, η2  = 0.49, p < 0.001), improving measurement error by ~17%. TD measurement error was not related to age or stroke. Therefore, the force sensor provided an objective method to improve the calculation of TD compared with current methods. Our data support using a force sensor during sit-to-stand dCA measures in adults across the lifespan and post-stroke.

Directional sensitivity of dynamic cerebral autoregulation during spontaneous fluctuations in arterial blood pressure at rest

Directional sensitivity, the more efficient response of cerebral autoregulation to increases, compared to decreases, in mean arterial pressure (MAP), has been demonstrated with repeated squat-stand maneuvers (SSM). In 43 healthy subjects (26 male, 23.1 ± 4.2 years old), five min. recordings of cerebral blood velocity (bilateral Doppler ultrasound), MAP (Finometer), end-tidal CO₂ (capnograph), and heart rate (ECG) were obtained during sitting (SIT), standing (STA) and SSM. A new analytical procedure, based on autoregressive-moving average models, allowed distinct estimates of the autoregulation index (ARI) by separating the MAP signal into its positive (MAP_+D) and negative (MAP_-D) derivatives. ARI_+D was higher than ARI_-D (p < 0.0001), SIT: 5.61 ± 1.58 vs 4.31 ± 2.16; STA: 5.70 ± 1.24 vs 4.63 ± 1.92; SSM: 4.70 ± 1.11 vs 3.31 ± 1.53, but the difference ARI_+D-ARI_-D was not influenced by the condition. A bootstrap procedure determined the critical number of subjects needed to identify a significant difference between ARI_+D and ARI_-D, corresponding to 24, 37 and 38 subjects, respectively, for SSM, STA and SIT. Further investigations are needed on the influences of sex, aging and other phenotypical characteristics on the phenomenon of directional sensitivity of dynamic autoregulation.

Transfer function analysis of dynamic cerebral autoregulation: A CARNet white paper 2022 update

Cerebral autoregulation (CA) refers to the control of cerebral tissue blood flow (CBF) in response to changes in perfusion pressure. Due to the challenges of measuring intracranial pressure, CA is often described as the relationship between mean arterial pressure (MAP) and CBF. Dynamic CA (dCA) can be assessed using multiple techniques, with transfer function analysis (TFA) being the most common. A 2016 white paper by members of an international Cerebrovascular Research Network (CARNet) that is focused on CA strove to improve TFA standardization by way of introducing data acquisition, analysis, and reporting guidelines. Since then, additional evidence has allowed for the improvement and refinement of the original recommendations, as well as for the inclusion of new guidelines to reflect recent advances in the field. This second edition of the white paper contains more robust, evidence-based recommendations, which have been expanded to address current streams of inquiry, including optimizing MAP variability, acquiring CBF estimates from alternative methods, estimating alternative dCA metrics, and incorporating dCA quantification into clinical trials. Implementation of these new and revised recommendations is important to improve the reliability and reproducibility of dCA studies, and to facilitate inter-institutional collaboration and the comparison of results between studies.

Novel application of a force sensor during sit-to-stands to measure dynamic cerebral autoregulation onset

Current sit-to-stand methods measuring dynamic cerebral autoregulation (dCA) do not capture the precise onset of the time delay (TD) response. Reduced sit-to-stand reactions in older adults and individuals post-stroke could inadvertently introduce variability, error, and imprecise timing. We applied a force sensor during a sit-to-stand task to more accurately determine how TD before the onset of dCA may be altered. Middle cerebral artery blood velocity (MCAv) and mean arterial pressure (MAP) were measured during two sit-to-stands separated by 15 min. Recordings started with participants sitting on a force-sensitive resistor for 60 s, then asked to stand for 2 min. Upon standing, the force sensor voltage immediately dropped and marked the exact moment of arise-and-off (AO). Time from AO until an increase in cerebrovascular conductance (CVC = MCAv/MAP) was calculated as TD. We tested the sensor in four healthy young adults, two older adults, and two individuals post-stroke. Healthy young adults stood quickly and the force sensor detected a small change in TD compared to classically estimated AO, from verbal command to stand. When compared to the estimated AO, older adults had a delayed measured AO and TD decreased up to ~53% while individuals post-stroke had an early AO and TD increased up to ~14%. The stance time during the sit-to-stand has the potential to influence the TD before the onset of dCA metric. As observed in the older adults and participants with stroke, this response may drastically vary and influence TD.

Machine Learning Models and Statistical Complexity to Analyze the Effects of Posture on Cerebral Hemodynamics

The mechanism of cerebral blood flow autoregulation can be of great importance in diagnosing and controlling a diversity of cerebrovascular pathologies such as vascular dementia, brain injury, and neurodegenerative diseases. To assess it, there are several methods that use changing postures, such as sit-stand or squat-stand maneuvers. However, the evaluation of the dynamic cerebral blood flow autoregulation (dCA) in these postures has not been adequately studied using more complex models, such as non-linear ones. Moreover, dCA can be considered part of a more complex mechanism called cerebral hemodynamics, where others (CO2 reactivity and neurovascular-coupling) that affect cerebral blood flow (BF) are included. In this work, we analyzed postural influences using non-linear machine learning models of dCA and studied characteristics of cerebral hemodynamics under statistical complexity using eighteen young adult subjects, aged 27 ± 6.29 years, who took the systemic or arterial blood pressure (BP) and cerebral blood flow velocity (BFV) for five minutes in three different postures: stand, sit, and lay. With models of a Support Vector Machine (SVM) through time, we used an AutoRegulatory Index (ARI) to compare the dCA in different postures. Using wavelet entropy, we estimated the statistical complexity of BFV for three postures. Repeated measures ANOVA showed that only the complexity of lay-sit had significant differences.

Long-term heart transplant recipients: heart rate-related effects on augmented transfer function coherence during repeated squat-stand maneuvers in males

Previous research has highlighted that squat-stand maneuvers (SSMs) augment coherence values within the cerebral pressure-flow relationship to ∼0.99. However, it is not fully elucidated if mean arterial pressure (MAP) leads to this physiological entrainment independently, or if heart rate (HR) and/or the partial pressure of carbon dioxide (Pco₂) also have contributing influences. A 2:1 control-to-case model was used in the present investigation [participant number (n) = 40; n = 16 age-matched (AM); n = 16 donor control (DM); n = 8 heart transplant recipients (HTRs)]. The latter group was used to mechanistically isolate the extent to which HR influences the cerebral pressure-flow relationship. Participants completed 5 min of squat-stand maneuvers at 0.05 Hz (10 s) and 0.10 Hz (5 s). Linear transfer function analysis (TFA) examined the relationship between different physiological inputs (i.e., MAP, HR, and Pco₂) and output [cerebral blood velocity (CBV)] during SSM; and cardiac baroreceptor sensitivity (BRS). Compared with DM, cardiac BRS was reduced in AM (P < 0.001), which was further reduced in HTR (P < 0.045). In addition, during the SSM, HR was elevated in HTR compared with both control groups (P < 0.001), but all groups had near-maximal coherence metrics ≥0.98 at 0.05 Hz and ≥0.99 at 0.10 Hz (P ≥ 0.399). In contrast, the mean HR-CBV/Pco₂-CBV relationships ranged from 0.38 (HTR) to 0.81 (DM). Despite near abolishment of BRS and blunted HR following heart transplantation, long-term HTR exhibited near-maximal coherence within the MAP-CBV relationship, comparable with AM and DM. Therefore, these results show that the augmented coherence with SSM is driven by blood pressure, whereas elevations in TFA coherence as a result of HR contribution are likely correlational in nature.

Extremes of cerebral blood flow during hypercapnic squat-stand maneuvers

Squat-stand maneuvers (SSMs) are a popular method of inducing blood pressure (BP) oscillations to reliably assess dynamic cerebral autoregulation (dCA), but their effects on the cerebral circulation remain controversial. We designed a protocol whereby participants would perform SSMs under hypercapnic conditions. Alarmingly high values of cerebral blood flow velocity (CBFV) were recorded, leading to early study termination after the recruitment of a single participant. One healthy subject underwent recordings at rest (5 min sitting, 5 min standing) and during two SSMs (fixed and random frequency). Two sets of recordings were collected; one while breathing room air, one while breathing 5% CO2 . Continuous recordings of bilateral CBFV (transcranial Doppler), heart rate (ECG), BP (Finometer), and end-tidal CO2 (capnography) were collected. Peak values of systolic CBFV were significantly higher during hypercapnia (p < 0.01), and maximal values exceeded 200 cm.s-1 . Estimates of dCA (ARI) during hypercapnia were impaired relative to poikilocapnia (p = 0.03). The phase was significantly reduced under hypercapnic conditions (p = 0.03). Here we report extremely high values of CBFV in response to repeated SSMs during induced hypercapnia, in an otherwise healthy subject. Our findings suggest that protocols performing hypercapnic SSMs are potentially dangerous. We, therefore, urge caution if other research groups plan to undertake similar protocols.

Determinants of cerebral blood flow velocity change during squat-stand maneuvers

The large changes in mean arterial blood pressure (MABP) and cerebral blood flow velocity (CBFV) induced by squat-stand maneuvers (SSM) make this approach particularly suited for studying dynamic cerebral autoregulation (CA). However, the role of other systemic determinants of CBFV has not been described and could provide alternative physiological interpretations of SSM results. In 32 healthy subjects (16 female), continuous recordings of MABP (Finometer), bilateral CBFV (transcranial Doppler, MCA), end-tidal CO₂ (EtCO₂; capnography), and heart rate (HR; electrocardiogram) were performed for 5 min standing at rest, and during 15 SSM at the frequency of 0.05 Hz. A time-domain, multivariate dynamic model estimated the CBFV variance explained by different inputs, corresponding to significant contributions from MABP (P < 0.00001), EtCO₂ (P < 0.0001), and HR (P = 0.041). The autoregulation index (ARI; range 0-9) was estimated from the CBFV response to a step change in MABP. At rest, ARI values (typically 5.7) were independent of the number of model inputs, but during SSM, ARI was reduced compared with baseline (P < 0.0001), and the three input model yielded lower values for the right and left MCA (3.4 ± 1.2, 3.1 ± 1.3) when compared with the single-input MABP-CBFV model (4.1 ± 1.1, 3.9 ± 1.0; P < 0.0001). The high coherence of the MABP-CBFV transfer function at 0.05 Hz (typically 0.98) was considerably reduced (around 0.71-0.73; P < 0.0001) when the contribution of CBFV covariates was taken into account. Not taking into consideration other determinants of CBFV, in addition to MABP, could be misleading and introduce biases in physiological and clinical studies.

Incomplete recovery of cerebral blood flow dynamics in sufficiently treated high blood pressure

Objective:

Whether cerebrovascular regulation is different in patients with controlled high blood pressure (HBP) with and without small vessel disease (SVD).

Methods:

Sixty-seven healthy controls (mean age ± SD, 45 ± 16 years; 30 women, 37 men) and 40 patients (mean age, 64 ± 13 years; 14 women, 26 men) with HBP and different stages of SVD, underwent simultaneous recordings of the spontaneous fluctuations of BP, blood flow velocity (CBFV) in both middle cerebral arteries (MCA), and of end-tidal CO₂ (ETCO₂). Coherence and transfer function gain and phase between BP and CBFV were assessed in the frequency ranges of VLF (0.02–0.07 Hz), low frequency (0.07–0.15), and high frequency (>0.15). BP SD indicated BP variability (BPV).

Results:

In controls (BP, 86 ± 13 mmHg; ETCO₂, 39 ± 4 mmHg; BPV, 15 ± 6 mmHg), gain, phase and coherence were not age-dependent in simple or a multiple regression models. BPV correlated significantly in both MCAs with gain in low frequency and high frequency, and with phase in VLF and high frequency. In patients (BP, 91 ± 16 mmHg, ETCO₂, 39 ± 4 mmHg, BPV 18 ± 5 mmHg), only gain showed some differences between different SVD groups. Comparing all patients with 25 controls of similar age and sex, patients exhibited significantly (P < 0.05–P < 0.005): increased coherence and gain in VLF, decreased phase in VLF and low frequency, correlations between BPV with phase in low frequency (left) and with gain in VLF (left) and in high frequency (left and right).

Conclusion:

Phase seems an age independent autoregulatory index. In controlled HBP, CBF regulation is degraded at longlasting CBF changes; BPV effects lose their physiological bilateral distribution.

Directional sensitivity of dynamic cerebral autoregulation in squat-stand maneuvers

Dynamic cerebral autoregulation (CA), the transient response of cerebral blood flow (CBF) to rapid changes in arterial blood pressure (BP), is usually modeled as a linear mechanism. We tested the hypothesis that dynamic CA can display nonlinear behavior resulting from differential efficiency dependent on the direction of BP changes. Cerebral blood velocity (CBV) (transcranial Doppler), heart rate (HR) (three-lead ECG), continuous BP (Finometer), and end-tidal CO2 (capnograph) were measured in 10 healthy young subjects during 15 squat-stand maneuvers (SSM) with a frequency of 0.05 Hz. The protocol was repeated with a median (interquartile range) of 44 (35–64) days apart. Dynamic CA was assessed with the autoregulation index (ARI) obtained from CBV step responses estimated with an autoregressive moving-average model. Mean BP, HR, and CBV were different (all P < 0.001) between squat and stand, regardless of visits. ARI showed a strong interaction ( P < 0.001) of SSM with the progression of transients; in general, the mean ARI was higher for the squat phase compared with standing. The changes in ARI were partially explained by concomitant changes in CBV ( P = 0.023) and pulse pressure ( P < 0.001), but there was no evidence that ARI differed between visits ( P = 0.277). These results demonstrate that dynamic CA is dependent on the direction of BP change, but further work is needed to confirm if this finding can be generalized to other physiological conditions and also to assess its dependency on age, sex and pathology.

How many squat-stand manoeuvres to assess dynamic cerebral autoregulation?

Purpose

Squat–stand manoeuvres (SSMs) have been used to induce blood pressure (BP) changes for the reliable assessment of dynamic cerebral autoregulation. However, they are physically demanding and thus multiple manoeuvres can be challenging for older subjects. This study aimed to determine the minimum number of SSMs required to obtain satisfactory coherence, thus minimising the subjects’ workload.

Method

20 subjects performed SSMs at a frequency of 0.05 Hz. End-tidal CO₂, cerebral blood flow velocity, heart rate, continuous BP and the depth of the squat were measured. 11 subjects returned for a repeat visit. The time points at which subjects had performed 3, 6, 9, 12 and 15 SSMs were determined. Transfer function analysis was performed on files altered to the required length to obtain estimates of coherence and the autoregulation index (ARI).

Results

After three SSMs, coherence (0.05 Hz) was 0.93 ± 0.05, and peaked at 0.95 ± 0.02 after 12 manoeuvres. ARI decreased consecutively with more manoeuvres. ARI was comparable across the two visits (p = 0.92), but coherence was significantly enhanced during the second visit (p < 0.01). The intra-subject coefficients of variation (CoV) for ARI remained comparable as the number of manoeuvres varied.

Conclusions

This analysis can aid those designing SSM protocols, especially where participants are unable to tolerate a standard 5-min protocol or when a shorter protocol is needed to accommodate additional tests. We emphasise that fewer manoeuvres should only be used in exceptional circumstances, and where possible a full set of manoeuvres should be performed. Furthermore, these results need replicating at 0.10 Hz to ensure their applicability to different protocols.