Coronary atheroma burden predicts flow reserve in women with ischemia and nonobstructive coronary artery disease
Bibliographic record
Abstract
Women with signs and symptoms of ischemia and no obstructive coronary artery disease often have coronary microvascular dysfunction (CMD) with reduced coronary flow reserve (CFR), and compensatory coronary remodeling. Angiographic measurements of epicardial coronary anatomy (AMCA) may improve understanding of relations between CFR and atherosclerosis. We investigated AMCA and CFR in women evaluated for CMD. Women consecutively enrolled in the Women's Ischemia Syndrome Evaluation CVD Continuation (NCT00832702) were included. All underwent clinically indicated coronary function testing measuring CFR. AMCA included coronary angiographic atheroma burden (AB), percent diameter stenosis (PDS), and tapering reference diameter Z score (RDZ), derived for the left main and left anterior descending coronary epicardial segments. The 51 women were aged 55.8 ± 10.8 years, with 19(38%) hypertensive, 10(20.4%) hyperlipidemic, 4(7.8%) diabetic, 13(25.5%) prior smokers, and mean CFR 3.0 ± 0.8. Both average and maximal AB negatively correlated with CFR (r = −0.30 and −0.31, with p = 0.04 for both), as did average and maximal PDS (r = −0.38 and −0.41 with p = 0.009 and p = 0.005) while average RDZ was directly related (r = 0.37, p = 0.01). Multiple linear regression analyses revealed that both average PDS (Units of CFR −0.03 95% CI: −0.06, −0.002, p = 0.023) and maximal PDS (−0.04 95% CI −0.07, −0.01, p = 0.007) were negatively related to CFR. Measures of epicardial coronary atheroma burden, size and tapering are related to CFR, suggesting that atherosclerotic anatomical findings may contribute to or be a consequence of CMD, with further work is needed to investigate these measures as treatment targets.
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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 | 0.001 | 0.002 |
| 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".