Fundamental relationships between arterial baroreflex sensitivity and dynamic cerebral autoregulation in humans
Bibliographic record
Abstract
The functional relationship between dynamic cerebral autoregulation (CA) and arterial baroreflex sensitivity (BRS) in humans is unknown. Given that adequate cerebral perfusion during normal physiological challenges requires the integrated control of CA and the arterial baroreflex, we hypothesized that between-individual variability in dynamic CA would be related to BRS in humans. We measured R-R interval, blood pressure, and cerebral blood flow velocity (transcranial Doppler) in 19 volunteers. BRS was estimated with the modified Oxford method (nitroprusside-phenylephrine injections) and spontaneous low-frequency (0.04-0.15) alpha-index. Dynamic CA was quantified using the rate of regulation (RoR) and autoregulatory index (ARI) derived from the thigh-cuff release technique and transfer function analysis of spontaneous oscillations in blood pressure and mean cerebral blood flow velocity. Results show that RoR and ARI were inversely related to nitroprusside BRS [R=-0.72, confidence interval (CI) -0.89 to -0.40, P=0.0005 vs. RoR; R=-0.69, CI -0.88 to -0.35, P=0.001 vs. ARI], phenylephrine BRS (R=-0.66, CI -0.86 to -0.29, P=0.0002 vs. RoR; R=-0.71, CI -0.89 to -0.38, P=0.0001 vs. ARI), and alpha-index (R=-0.70, CI -0.89 to -0.40, P=0.0008 vs. RoR; R=-0.62, CI -0.84 to -0.24, P=0.005 vs. ARI). Transfer function gain was positively related to nitroprusside BRS (R=0.62, CI 0.24-0.84, P=0.0042), phenylephrine BRS (R=0.52, CI 0.10-0.79, P=0.021), and alpha-index (R=0.69, CI 0.35-0.88, P=0.001). These findings indicate that individuals with an attenuated dynamic CA have greater BRS (and vice versa), suggesting the presence of possible compensatory interactions between blood pressure and mechanisms of cerebral blood flow control in humans. Such compensatory adjustments may account for the divergent changes in dynamic CA and BRS seen, for example, in chronic hypotension and spontaneous hypertension.
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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".