Diastolic Dysfunction in Women With Signs and Symptoms of Ischemia in the Absence of Obstructive Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Angina, in the absence of obstructive coronary artery disease, is more common in women, is associated with adverse cardiovascular morbidity and mortality, and is a major burden to the healthcare system. Although advancements have been made to understand the mechanistic underpinning of this disease, the functional consequence remains unclear. METHODS AND RESULTS: Cardiac magnetic resonance imaging was performed to assess left ventricular function in 20 women with signs and symptoms of ischemia, but no obstructive coronary artery disease (cases), and 15 age- and body mass index-matched reference controls. Functional imaging included standard cinematic imaging to assess left ventricular morphology and global function, along with tissue tagging to assess left ventricular tissue deformation. Systolic function was preserved in both cases and controls, with no differences in ejection fraction (mean±SE: 63.1±8% versus 65±2%), circumferential strain (-20.7±0.6% versus -21.9±0.5%), or systolic circumferential strain rate (-105.9±6.1% versus -109.0±3.8% per second). In contrast, we observed significant differences between cases and controls in diastolic function, as demonstrated by reductions in both diastolic circumferential strain rate (153.8±8.9% versus 191.4±8.9% per second; P<0.05) and peak rate of left ventricular untwisting (-99.4±8.0° versus -129.4±12.8° per second; P<0.05). CONCLUSIONS: Diastolic function is impaired in women with signs and symptoms of ischemia in the absence of coronary artery disease, as assessed by cardiac magnetic resonance tissue tagging. These results are hypothesis-generating. Larger studies are needed to define the exact mechanism(s) responsible and to establish viable treatment strategies.
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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 | 0.002 |
| 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 | 0.001 | 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".