Progressive epicardial coronary blood flow reduction fails to produce ST-segment depression at normal heart rates
Bibliographic record
Abstract
ST-segment depression is commonly seen in patients with acute coronary syndromes. Most authors have attributed it to transient reductions in coronary blood flow due to nonocclusive thrombus formation on a disrupted atherosclerotic plaque and dynamic focal vasospasm at the site of coronary artery stenosis. However, ST-segment depression was never reproduced in classic animal models of coronary stenosis without the presence of tachycardia. We hypothesized that ST-segment depression occurring during acute coronary syndromes is not entirely explained by changes in epicardial coronary artery resistance and thus evaluated the effect of a slow, progressive epicardial coronary artery occlusion on the ECG and regional myocardial blood flow in anesthetized pigs. Slow, progressive occlusion over 72 min (SD 27) of the left anterior descending coronary artery in 20 anesthetized pigs led to a 90% decrease in coronary blood flow and the development of ST-segment elevation associated with homogeneous and transmural myocardial blood flow reductions, confirmed by microspheres and myocardial contrast echocardiography. ST-segment depression was not observed in any ECG lead before the development of ST-segment elevation. At normal heart rates, progressive epicardial stenosis of a coronary artery results in myocardial ischemia associated with homogeneous, transmural reduction in regional myocardial blood flow and ST-segment elevation, without preceding ST-segment depression. Thus, in coronary syndromes with ST-segment depression and predominant subendocardial ischemia, factors other than mere increases in epicardial coronary resistance must be invoked to explain the heterogeneous parietal distribution of flow and associated ECG changes.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".