Breathing manoeuvre-dependent changes in myocardial oxygenation in healthy humans
Bibliographic record
Abstract
AIMS: CO₂ is an intrinsic vasodilator for cerebral and myocardial blood vessels. Myocardial vasodilation without a parallel increase of the oxygen demand leads to changes in myocardial oxygenation. Because apnoea and hyperventilation modify blood CO₂, we hypothesized that voluntary breathing manoeuvres induce changes in myocardial oxygenation that can be measured by oxygenation-sensitive cardiovascular magnetic resonance (CMR). METHODS AND RESULTS: Fourteen healthy volunteers were studied. Eight performed free long breath-hold as well as a 1- and 2-min hyperventilation, whereas six aquatic athletes were studied during a 60-s breath-hold and a free long breath-hold. Signal intensity (SI) changes in T₂*-weighted, steady-state free precession, gradient echo images at 1.5 T were monitored during breathing manoeuvres and compared with changes in capillary blood gases. Breath-holds lasted for 35, 58 and 117 s, and hyperventilation for 60 and 120 s. As expected, capillary pCO₂ decreased significantly during hyperventilation. Capillary pO₂ decreased significantly during the 117-s breath-hold. The breath-holds led to a SI decrease (deoxygenation) in the left ventricular blood pool, while the SI of the myocardium increased by 8.2% (P = 0.04), consistent with an increase in myocardial oxygenation. In contrast, hyperventilation for 120 s, however, resulted in a significant 7.5% decrease in myocardial SI/oxygenation (P = 0.02). Change in capillary pCO₂ was the only independently correlated variable predicting myocardial oxygenation changes during breathing manoeuvres (r = 0.58, P < 0.01). CONCLUSION: In healthy individuals, breathing manoeuvres lead to changes in myocardial oxygenation, which appear to be mediated by CO₂. These changes can be monitored in vivo by oxygenation-sensitive CMR and thus, may have value as a diagnostic tool.
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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".