The effects of head‐up and head‐down tilt on cerebrovascular CO2 reactivity in anterior and posterior cerebral circulations
Bibliographic record
Abstract
Cerebral autoregulation is a protective feature of the cerebrovasculature that maintains relatively constant cerebral perfusion in the face of static and dynamic fluctuations in mean arterial pressure (MAP). However, gravity‐dependent shifts in blood volume distribution during head‐up and head‐down tilt (HUT, HDT) have profound effects on venous return, cardiac output and MAP. Further, cerebral blood flow (CBF) is highly sensitive to the influence of changes in arterial CO 2 (PaCO 2 ) on arteriolar diameter. We tested the effects of steady‐state tilt on cerebral blood velocity (CBV) and CO 2 reactivity in the middle and posterior cerebral arteries (MCA, PCA) using hyperoxic rebreathing and transcranial Doppler ultrasound in various positions on a tilt table. Following initial testing in supine position, subjects were positioned randomly and tested in each of four positions: 90° HDT, 45° HDT, 45° HUT and 90° HUT. There were no differences in steady‐state MCA or PCA CBV across positions. Absolute and relative CO 2 reactivity slopes were calculated for the MCA and PCA using linear regression. Absolute reactivity was greater in the MCA than the PCA in all 5 positions, but there was no interaction between reactivity and tilt. Our data demonstrate that CBF is maintained through cerebral autoregulation in the face of superimposed steady‐state orthostatic stress and dynamic changes in PaCO 2 .
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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 | 0.000 | 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".