Are familial risks of myocardial infarction with non-obstructive coronary arteries shared with obstructive coronary artery disease?
Bibliographic record
Abstract
This editorial refers to ‘Familial risk of myocardial infarction with non-obstructive and obstructive coronary arteries: a nation-wide cohort study’, by F.H.K. Hakansson et al., https://doi.org/10.1093/eurjpc/zwae313. Myocardial infarction (MI) with non-obstructive coronary arteries (MINOCA) is an increasingly recognized clinical entity that is found in ∼6–10% of patients presenting with a clinical MI.1,2 The definition of MINOCA is contingent upon meeting the Fourth Universal Definition of MI, as well as the absence of epicardial coronary artery stenosis ≥ 50% on coronary angiography and no other overt cause for the clinical presentation. In the contemporary era, the diagnosis of MINOCA should be used exclusively to indicate an ischaemic cause for the presentation.2 Practically, many patients are initially given a working diagnosis of MINOCA based on clinical presentation and angiographic findings. They may later be found to have alternative diagnoses that mimic MINOCA, such as myocarditis and Takotsubo syndrome that do not qualify as true MINOCA. We have learned from the seminal Heart Attack Research Program (HARP) study that the majority of patients with MINOCA have an underlying atherosclerotic cause that was not readily detected on coronary angiography.3 When optimal coherence tomography was performed in combination with cardiac magnetic resonance imaging (CMR), potential mechanism of MI was identified in 84.5% of women. The majority of these patients had an ischaemic cause of MI (75.5%), with the most common aetiology being missed plaque rupture, intraplaque cavity, or layered plaque. Subsequent cardiac MRI studies have confirmed this.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.012 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".