Altered blood gas tensions of oxygen and carbon dioxide confound coronary reactivity to apnea
Bibliographic record
Abstract
Purpose Arterial blood gases change frequently during anesthesia and intensive care. Apnea can occur during diagnostic exams and airway and surgical interventions. While the impact of blood gas levels on coronary blood flow is established, their confounding effect on coronary vasoreactivity in response to an apneic stimulus, especially in coronary artery disease, is not known. Methods Six anesthetized control swine and eleven swine with coronary artery stenosis were examined. Nine different blood gas levels from a combination of arterial partial pressure of oxygen (70, 100, and 300 mmHg) and carbon dioxide (30, 40, and 50 mmHg) were targeted. Apnea was induced by halting controlled positive pressure ventilation for 3–30s, while the left descending coronary artery flow was measured and reported relative to apnea duration, and at the adjusted mean (12s). Results At normoxemic-normocapnic blood gas levels, apnea increased coronary blood flow in proportion to the duration of apnea in the control (r = 0.533, p < 0.001) and stenosed groups (r = 0.566, p < 0.001). This culminated in a 42% (95% CI: 27–58) increase in controls ( p < 0.001) and, to a lesser extent, 27% (15–40) in the presence of coronary artery stenosis ( p < 0.001). Vasoreactivity was augmented by mild-hypoxemic levels [81% (65–97), and 66% (53–79) increase in flow respectively, p < 0.001 vs. normoxemia], but markedly reduced during hyperoxia (7.5% (−8.2–23) and 0.3% (−12–13), respectively, p < 0.001 vs. normoxemia). Conclusion Alterations of blood oxygen and carbon dioxide affect coronary vascular reactivity induced by apnea in swine, which was attenuated further in the presence of coronary stenosis. Especially hyperoxia significantly reduces coronary blood flow and blunts coronary vascular reactivity.
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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 | 0.000 |
| 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".