How many squat-stand manoeuvres to assess 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.

Validity and reliability of deriving the autoregulatory plateau through projection pursuit regression from driven methods

To compare the construct validity and between-day reliability of projection pursuit regression (PPR) from oscillatory lower body negative pressure (OLBNP) and squat-stand maneuvers (SSMs). Nineteen participants completed 5 min of OLBNP and SSMs at driven frequencies of 0.05 and 0.10 Hz across two visits. Autoregulatory plateaus were derived at both point-estimates and across the cardiac cycle. Between-day reliability was assessed with intraclass correlation coefficients (ICCs), Bland-Altman plots with 95% limits of agreement (LOA), coefficient of variation (CoV), and smallest real differences. Construct validity between OLBNP-SSMs were quantified with Bland-Altman plots and Cohen's d. The expected autoregulatory curve with positive rising and negative falling slopes were present in only ~23% of the data. The between-day reliability for the ICCs were poor-to-good with the CoV estimates ranging from ~50% to 70%. The 95% LOA were very wide with an average spread of ~450% for OLBNP and ~350% for SSMs. Plateaus were larger from SSMs compared to OLBNPs (moderate-to-large effect sizes). The cerebral pressure-flow relationship is a complex regulatory process, and the "black-box" nature of this system can make it challenging to quantify. The current data reveals PPR analysis does not always elicit a clear-cut central plateau with distinctive rising/falling slopes.

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.

Effects of the number of sit-stand maneuver repetitions on baroreflex sensitivity and cardiovascular risk assessments

Sit-stand maneuvers (SSM) have increasingly been used for baroreflex sensitivity (BRS) measurement in physiological research, but it remains unknown as to how many SSM need to be performed to measure BRS and assess its relation with cardiovascular disease (CVD) risk. Therefore, this study aimed to determine 1) the effect of the number of SSM repetitions on BRS and 2) the association between BRS and CVD risk factors. Data were collected from 174 individuals during 5 minutes of spontaneous rest and 5 minutes of repeated SSM at 0.05 Hz (i.e., 15 cycles of 10-second sit and 10-second stand). During SSM, BRS was calculated from the incremental cycles of 3, 6, 9, 12, and 15 SSM using transfer function analysis of heart rate (HR) and systolic blood pressure (SBP). General CVD risk factors, carotid arterial stiffness, and cardiorespiratory fitness were measured. In result, HR and SBP increased during SSM (p<0.05). The BRS remained at a similar level during the resting and SSM conditions, while the coherence function reached its peak after 3 cycles of SSM. BRS with ≥6 cycles of SSM was strongly correlated with age (r=-0.721 to -0.740), carotid distensibility (r=0.625 to 0.629), and cardiorespiratory fitness (r=0.333 to 0.351) (all p<0.001). Multiple regression analysis demonstrated that BRS with ≥6 cycles of SSM explained >60% of the variance in CVD risk factors. Therefore, our findings suggest that repeated SSM significantly strengthens the association between BRS and CVD risk factors. Particularly, BRS with ≥6 cycles of SSM is strongly associated with CVD risk.

Prospective Pilot Clinical Study of Noninvasive Cerebrovascular Autoregulation Monitoring in Open-Angle Glaucoma Patients and Healthy Subjects

Purpose

To analyze the cerebrovascular autoregulation (CA) dynamics in patients with normal-tension glaucoma (NTG) and high-tension glaucoma (HTG) as well as healthy subjects using noninvasive ultrasound technologies for the first time.

Methods

The CA status of 10 patients with NTG, 8 patients with HTG, and 10 healthy subjects was assessed, using an innovative noninvasive ultrasonic technique, based on intracranial blood volume slow-wave measurements. Identified in each participant were intraocular pressure, ocular perfusion pressure, and CA-related parameter volumetric reactivity index (VRx), as well as the duration and doses of the longest cerebral autoregulation impairment (LCAI). In addition, we calculated the associations of these parameters with patients' diagnoses.

Results

The VRx value, the LCAI dose, and duration in healthy subjects were significantly lower than in patients with NTG (P < 0.05). However, no significant differences were noted in these parameters between healthy subjects and HTG and between NTG and HTG groups.

Conclusions

NTG is associated with the disturbed cerebral blood flow and could be diagnosed by performing noninvasive CA assessments.

Translational Relevance

The VRx monitoring method can be applied to a wider range of patient groups, especially patients with normal-tension glaucoma.

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.

The validity and reliability of an open source biosensing board to quantify heart rate variability

Background

Heart rate variability (HRV) is a popular tool to quantify autonomic function. However, this typically requires an expensive 3-12 lead electrocardiogram (ECG) and BioAmp system. This investigation sought to determine the validity and reliability of an OpenBCI cyton biosensing board (open source) for accurately quantifying HRV.

New method

A cyton board with a 3-lead ECG was employed to acquire heart rate waveform data, which was processed to obtain HRV within both time- and frequency-domains. The concurrent validity was compared to a simultaneous recording from an industry-standard 3-lead ECG (ADInstruments) (n = 15). The reliability of the cyton board was compared between three days within a 7-day timespan (n = 10). Upright quiet-stance short-term HRV metrics were quantified in time- and frequency-domains.

Results

The two devices displayed excellent limits of agreements (all log mean differences ±0.4) and very high between-device variable associations (all r ² > 0.98). Between the three time points in the same subjects, no differences were noted within time- (all p > 0.71) or frequency-domains (all p > 0.88) across testing points. Finally, all HRV metrics exhibited excellent levels of reliability through high Cronbach's Alpha (all ≥0.916) and intraclass correlation coefficients (all ≥0.930); and small standard error of the measurement (all ≤0.7) and typical error of the measurement (all ≤0.1) metrics.

Comparison with existing methods

The cyton board with 3-lead ECG was compared with an industry-standard ADInstruments ECG during HRV assessments. There were no significant differences between devices with respect to time- and frequency-domains. The cyton board displayed high-levels of between-day reliability and provided values harmonious to previous ECG literature highlighting the applicability for longitudinal studies.

Conclusion

With proper background knowledge regarding ECG principles and a small degree of set-up complexity, an open source cyton board can be created and employed to perform multimodal HRV assessments at a fraction of the cost (~4%) of an industry-standard ECG setup.

What recording duration is required to provide physiologically valid and reliable dynamic cerebral autoregulation transfer functional analysis estimates?

Objective. Currently, a recording of 300 s is recommended to obtain accurate dynamic cerebral autoregulation estimates using transfer function analysis (TFA). Therefore, this investigation sought to explore the concurrent validity and the within- and between-day reliability of TFA estimates derived from shorter recording durations from squat-stand maneuvers.Approach. Retrospective analyses were performed on 70 young, recreationally active or endurance-trained participants (17 females; age: 26 ± 5 years, [range: 20-39 years]; body mass index: 24 ± 3 kg m^-2). Participants performed 300 s of squat-stands at frequencies of 0.05 and 0.10 Hz, where shorter recordings of 60, 120, 180, and 240 s were extracted. Continuous transcranial Doppler ultrasound recordings were taken within the middle and posterior cerebral arteries. Coherence, phase, gain, and normalized gain metrics were derived. Bland-Altman plots with 95% limits of agreement (LOA), repeated measures ANOVA's, two-tailed paired t-tests, coefficient of variation, Cronbach's alpha, intraclass correlation coefficients, and linear regressions were conducted.Main results. When examining the concurrent validity across different recording durations, group differences were noted within coherence (F₍₄₁₅₅₎ > 11.6,p < 0.001) but not phase (F₍₄₁₅₅₎ < 0.27,p > 0.611), gain (F₍₄₁₅₅₎ < 0.61,p > 0.440), or normalized gain (F₍₄₁₅₅₎ < 0.85,p > 0.359) parameters. The Bland-Altman 95% LOA measuring the concurrent validity, trended to narrow as recording duration increased (60 s: < ±0.4, 120 s: < ±0.3, 180 s  < ±0.3, 240 s: < ±0.1). The validity of the 180 and 240 s recordings further increased when physiological covariates were included within regression models.Significance. Future studies examining autoregulation should seek to have participants perform 300 s of squat-stand maneuvers. However, valid and reliable TFA estimates can be drawn from 240 s or 180 s recordings if physiological covariates are controlled.

The validity and reliability of ultra-short-term heart rate variability parameters and the influence of physiological covariates

Ultra-short-term (UST) heart rate variability (HRV) metrics have increasingly been proposed as surrogates for short-term HRV metrics. However, the concurrent validity, within-day reliability, and between-day reliability of UST HRV have yet to be comprehensively documented. Thirty-six adults (18 males, age: 26 ± 5 yr, BMI: 24 ± 3 kg/m²) were recruited. Measures of HRV were quantified in a quiet-stance upright orthostatic position via three-lead electrocardiogram (ADInstruments, FE232 BioAmp). All short-term data recordings were 300 s in length and five UST time points (i.e., 30 s, 60 s, 120 s, 180 s, and 240 s) were extracted from the original 300-s recording. Bland-Altman plots with 95% limits of agreement, repeated measures ANOVA and two-tailed paired t tests demarcated differences between UST and short-term recordings. Linear regressions, coefficient of variation, intraclass correlation coefficients, and other tests examined the validity and reliability in both time- and frequency domains. No group differences were noted between all short-term and UST measures, for either time- (all P > 0.202) or frequency-domain metrics (all P > 0.086). A longer recording duration was associated with augmented validity and reliability, which was less impacted by confounding influences from physiological variables (e.g., respiration rate, carbon dioxide end-tidals, and blood pressure). Conclusively, heart rate, time-domain, and relative frequency-domain HRV metrics were acceptable with recordings greater or equal to 60 s, 240 s, and 300 s, respectively. Future studies employing UST HRV metrics should thoroughly understand the methodological requirements to obtain accurate results. Moreover, a conservative approach should be utilized regarding the minimum acceptable recording duration, which ensures valid/reliable HRV estimates are obtained.NEW & NOTEWORTHY A one size fits all methodological approach to quantify HRV metrics appears to be inappropriate, where study design considerations need to be conducted upon a variable-by-variable basis. The present results found 60 s (heart rate), 240 s (time-domain parameters), and 300 s (relative frequency-domain parameters) were required to obtain accurate and reproducible metrics. The lower validity/reliability of the ultra-short-term metrics was attributable to measurement error and/or confounding from extraneous physiological influences (i.e., respiratory and hemodynamic variables).

Temporal evolution of neurovascular coupling recovery following moderate- and high-intensity exercise

PURPOSE

Studies examining neurovascular coupling (NVC) require participants to refrain from exercise for 12-24 hours. However, there is a paucity of empirical evidence for this restriction. The objectives for this study were to delineate the time-course recovery of NVC metrics following exercise and establish the NVC within- and between-day reliability.

METHODS

Nine participants completed a complex visual search paradigm to assess NVC via transcranial Doppler ultrasound of the posterior cerebral artery blood velocity (PCA). Measurements were performed prior to and throughout the 8-hour recovery period following three randomized conditions: 45 minutes of moderate-intensity exercise (at 50% heart-rate reserve), 30 minutes high-intensity intervals (10, 1-minute intervals at 85% heart-rate reserve), and control (30 minutes quiet rest). In each condition, baseline measures were collected at 8:00am with serial follow-ups at hours zero, one, two, four, six, and eight.

RESULTS

Area-under-the-curve and time-to-peak PCA velocity during the visual search were attenuated at hour zero following high-intensity intervals (all p < 0.05); however, these NVC metrics recovered at hour one (all p > 0.13). Conversely, baseline PCA velocity, peak PCA velocity, and the relative percent increase were not different following high-intensity intervals compared to baseline (all p > 0.26). No NVC metrics differed from baseline following both moderate exercise and control conditions (all p > 0.24). The majority of the NVC parameters demonstrated high levels of reliability (intraclass correlation coefficient: >0.90).

CONCLUSION

Future NVC assessments can take place a minimum of one hour following exercise. Moreover, all metrics did not change across the control condition, therefore future studies using this methodology can reliably quantify NVC between 8:00am and 7:00 pm.

Does depth of squat-stand maneuver affect estimates of dynamic cerebral autoregulation?

Repeated squat-stand maneuvers (SSM) are an effective way of measuring dynamic cerebral autoregulation (dCA), but the depth of SSM required to improve dCA estimations has never been studied. We compared beat-to-beat cerebral hemodynamic parameters between maximal depth SSM (SSMD ) and a shallower alternative (SSMS ) in two age groups (younger [20-34 years] vs. older [50-71 years]) at a frequency of 0.05 Hz. Cerebral blood flow velocity, continuous blood pressure (BP) and end-tidal CO2 (EtCO2 ) were measured using transcranial Doppler ultrasound, the Finometer device, and capnography, respectively. Coherence (at 0.05 Hz) was significantly higher in both SSM recordings compared to spontaneous BP oscillations at baseline standing (BS ). Median (IQR) autoregulation index (ARI) was reduced during SSMD (4.46 [4.03-5.22], p < .01) compared to SSMS (5.96 [5.40-6.69]) and BS (6.03 [5.20-6.49], p < .01) with similar relative differences also observed for phase (at 0.05 Hz). End-tidal CO2 was increased in SSMD (38.3 ± 3.7 mmHg, p < .01) compared to both SSMS (36.6 ± 3.6 mmHg) and BS (35.5 ± 3.2 mmHg). The older group demonstrated significantly lower ARI and phase estimates during SSM and found SSMS more effortful than SSMD . In conclusion, both SSMD and SSMS are effective at estimating dCA, and dCA appears to be less efficient during maximal depth SSM compared to baseline rest or a shallower alternative.