Coronary morphological features in women with non-ST-segment elevation MINOCA and MI-CAD as assessed by optical coherence tomography
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Bibliographic record
Abstract
Aims: We aimed to use optical coherence tomography (OCT) to identify differences in atherosclerotic culprit lesion morphology in women with myocardial infarction (MI) with non-obstructive coronary arteries (MINOCA) compared with MI with obstructive coronary artery disease (MI-CAD). Methods and results: Women with an OCT-determined atherosclerotic aetiology of non-ST segment elevation (NSTE)-MINOCA (angiographic diameter stenosis <50%) who were enrolled in the multicentre Women's Heart Attack Research Program (HARP) study were compared with a consecutive series of women with NSTE-MI-CAD who underwent OCT prior to coronary intervention at a single institution. Atherosclerotic pathologies identified by OCT included plaque rupture, plaque erosion, intraplaque haemorrhage (IPH, a region of low signal intensity with minimum attenuation adjacent to a lipidic plaque without fibrous cap disruption), layered plaque (superficial layer with clear demarcation from the underlying plaque indicating early thrombus healing), or eruptive calcified nodule.We analysed 58 women with NSTE-MINOCA and 52 women with NSTE-MI-CAD. Optical coherence tomography features of underlying vulnerable plaque (thin-cap fibroatheroma) were less common in MINOCA (3 vs. 35%) than in MI-CAD. Intraplaque haemorrhage (47 vs. 2%) and layered plaque (31 vs. 12%) were more common in MINOCA than MI-CAD, whereas plaque rupture (14 vs. 67%), plaque erosion (8 vs. 14%), and calcified nodule (0 vs. 6%) were less common in MINOCA. The angle of ruptured cavity was smaller and thrombus burden was lower in MINOCA. Conclusion: The prevalence of atherothrombotic culprit lesion subtype varied substantially between MINOCA and MI-CAD. A majority of culprit lesions in MINOCA had the appearance of IPH or layered plaque. Clinical Trial Registration Information: : https://clinicaltrials.gov/ct2/show/NCT02905357.
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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 | 0.001 | 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 | 0.001 |
| 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 it