Critical closing pressure is the primary modulator of cerebrovascular resistance in older adults
Bibliographic record
Abstract
Rationale Cerebrovascular resistance (CVR), calculated from mean cerebral blood flow (CBF) and mean arterial blood pressure (ABP), can be further characterized by two independent parameters: critical closing pressure (CrCP) and resistance area product (RAP). These parameters are believed to reflect differences in the metabolic and myogenic control of CVR, respectively. The objective of this study was to assess how CVR, CrCP and RAP interrelate in a healthy aging population and how they adapt to postural change. Methods Sixty‐three older adults (36 women, 74 ± 5 years) were categorized in tertiles according to CVR determined from bilateral internal carotid artery blood flow and mean ABP. Apparent CrCP and RAP were estimated from continuous middle cerebral artery blood flow velocity and ABP in supine, sitting and standing postures. Results Individuals in the highest tertile for CVR had both higher ABP ( P < 0.001) and lower CBF ( P < 0.001) than the lowest tertile. Lying supine, CVR was directly related to CrCP (r = 0.43, P < 0.001), but not RAP ( P = 0.697). CrCP was reduced ( P < 0.001) and RAP was slightly increased ( P = 0.010) in upright posture. Conclusion High CVR in aging was primarily related to CrCP which might reflect structural changes leading to lower CBF in these individuals. Reduced CrCP with upright posture protects the brain from hypoperfusion during sitting and standing. Funded by CIHR, HSF, NSERC
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".