Pathophysiology of Myocardial Infarction With Nonobstructive Coronary Artery Disease: A Contemporary Systematic Review
Bibliographic record
Abstract
Background: Myocardial infarction with nonobstructive coronary artery disease (MINOCA) is defined as acute myocardial infarction (AMI) with angiographically nonobstructive coronary artery disease. MINOCA represents 6% of all AMI cases and is associated with increased mortality and morbidity. However, the wide array of pathophysiological factors and causes associated with MINOCA presents a diagnostic conundrum. Therefore, we conducted a contemporary systematic review of the pathophysiology of MINOCA. Methods: A comprehensive systematic review of MINOCA was carried out through the utilization of the PubMed database. All systematic reviews, meta-analyses, randomized controlled trials, and cohort studies available in English or French that reported on the pathophysiology of MINOCA published after January 1, 2013 were retained. Results: Of the 600 identified records, 80 records were retained. Central to the concept of MINOCA is the definition of AMI, characterized by the presence of myocardial damage reflected by elevated cardiac biomarkers in the setting of acute myocardial ischemia. As a result, a structured approach should be adopted to thoroughly assess and address clinically overlooked obstructive coronary artery disease, and cardiac and extracardiac mechanisms of myocyte injury. Once these options have been ruled out, a diagnosis of MINOCA can be established, and the appropriate multimodal assessment can be conducted to determine its specific underlying cause (plaque disruption, epicardial coronary vasospasm, coronary microvascular dysfunction, and coronary embolism and/or spontaneous coronary dissection or supply-demand mismatch). Conclusions: Integrating a suitable definition of AMI and understanding the pathophysiological mechanisms of MINOCA are crucial to ensure an effective multimodal diagnostic evaluation and the provision of adequate tailored therapies.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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 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".