Aortic valve stenosis is associated with reduced myocardial perfusion as assessed by videodensitometry in coronary angiograms
Bibliographic record
Abstract
UNLABELLED: Aortic valve stenosis may be accompanied by angina despite coronary arteries free of significant stenosis due to microvascular abnormalities. AIMS: The aim of the current study was to test whether densitometry-derived myocardial perfusion on coronary angiogram is reduced in patients with aortic valve stenosis. METHODS: The study comprised 20 patients with aortic valve stenosis (mean transvalvular gradient: 47.4±15.2 mm Hg) and 30 control subjects without significant epicardial coronary artery stenosis. A quantitative parameter of myocardial perfusion was calculated by the ratio of maximal density (Gmax) and time to reach maximum density (Tmax) on time-density curves in regions of interest of each coronary artery on coronary angiograms. RESULTS: Mean three-vessel Gmax/Tmax proved to be significantly lower in patients with aortic valve stenosis compared to control subjects (2.55±1.02 1/sec vs. 3.39±1.09 1/sec, p<0.01). CONCLUSIONS: Reduced Gmax/Tmax values indicative of myocardial perfusion abnormalities as measured by densitometry on coronary angiograms could be demonstrated in patients with aortic valve stenosis compared to controls.
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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 | 0.001 | 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".