Fundamental relationships between blood pressure and cerebral blood flow in humans
Bibliographic record
Abstract
Cerebral blood flow responses to transient blood pressure challenges are frequently attributed to cerebral autoregulation (CA), yet accumulating evidence indicates vascular properties like compliance are also influential. We hypothesized that middle cerebral blood velocity (MCAv) dynamics during or following a transient blood pressure perturbation can be accurately explained by the windkessel mechanism. Eighteen volunteers underwent blood pressure manipulations, including bilateral thigh-cuff deflation and sit-to-stand maneuvers under normocapnic and hypercapnic (5% CO2) conditions. Pressure-flow recordings were analyzed using a windkessel analysis approach that partitions the frequency-dependent resistance and compliance contributions to MCAv dynamics. The windkessel was typically able to explain more than 50% of the MCAv variance, as indicated by R(2) values for both the flow recovery and postrecovery phase. The most consistent predictors of MCAv dynamics under the control condition were the windkessel capacitive gain and high-frequency resistive gain. However, there were significant interindividual variations in the composition of windkessel predictors. Hypercapnia consistently reduced the capacitive gain and enhanced the low-frequency (0.04-0.20 Hz) resistive gain for both thigh-cuff deflation and sit-to-stand trials. These findings indicate that 1) MCAv dynamics during acute transient hypotension challenges are dominated by cerebrovascular windkessel properties independent of CA; 2) there is significant heterogeneity in windkessel properties between individuals; and 3) hemodynamic effects of hypercapnia during transient blood pressure challenges primarily reflect changes in windkessel properties rather than pure CA impairment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".