Effects of Age and Coronary Artery Disease on Cerebrovascular Reactivity to Carbon Dioxide in Humans
Bibliographic record
Abstract
Alterations in cerebrovascular reactivity to CO2, an index of cerebrovascular function, have been associated with increased risk of stroke. We hypothesised that cerebrovascular reactivity is impaired with increasing age and in patients with symptomatic coronary artery disease (CAD). Cerebrovascular and cardiovascular reactivity to CO2 was assessed at rest and during hypercapnia (5% CO2) and hypocapnia (hyperventilation) in subjects with symptomatic CAD (n=13) and age-matched old (n=9) and young (n=20) controls without CAD. Independent of CAD, reductions in middle cerebral artery blood velocity (transcranial Doppler) and cerebral oxygenation (near-infrared spectroscopy) were correlated with increasing age (r = -0.68, r = -0.51, respectively, P < 0.01). In CAD patients, at rest and during hypercapnia, cerebral oxygenation was lower (P < 0.05 vs. young). Although middle cerebral artery blood velocity reactivity was unaltered in the hypercapnic range, middle cerebral artery blood velocity reactivity to hypocapnia was elevated in the CAD and age-matched controls (P < 0.01 vs. young), and was associated with age (r = 0.62, P < 0.01). Transient drops in arterial PCO2 occur in a range of physiological and pathophysiological situations, therefore, the elevated middle cerebral artery blood velocity reactivity to hypocapnia combined with reductions in middle cerebral artery blood velocity may be important mechanisms underlying neurological risk with aging. In CAD patients, additional reductions in cerebral oxygenation may place them at additional risk of cerebral ischaemia.
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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".