Incidence, trends, characteristics, and outcomes in myocardial infarction with nonobstructive coronary artery disease (MINOCA) in Manitoba
Bibliographic record
Abstract
Abstract Introduction Myocardial infarction with nonobstructive coronary arteries (MINOCA) is a clinical condition characterized by acute myocardial infarction (MI) in the presence of normal or minimally obstructed (≤50% stenosis) coronary arteries. MINOCA accounts for 5-15% of acute coronary syndrome (ACS) presentations; however, it remains underdiagnosed. The condition has diverse etiologies, including coronary abnormalities such as spontaneous coronary artery dissection (SCAD) and noncoronary causes such as Takotsubo cardiomyopathy and myocarditis. A comprehensive diagnostic workup is essential to identify the underlying mechanism, as management strategies depend on the specific cause. Although coronary angiography is routinely performed, additional diagnostic tools such as intravascular imaging and cardiac magnetic resonance imaging (MRI) are underutilized. Accurate diagnosis is critical, given the variability in long-term prognosis based on etiology. Purpose The purpose of our study was to describe the demographic and clinical characteristics of MINOCA patients in Manitoba, evaluate common diagnostic methods, and assess in-hospital and one-year outcomes in these patients. Methods This retrospective cohort study included all ACS patients over 18 years old who underwent coronary angiography without stenting between January 2019-December 2020. The cardiac catheterization laboratory electronic system was used to generate a list of all the patients diagnosed with MINOCA. A chart review was performed to obtain all relevant data. Data was analyzed using Excel. Results A total of 511 patients were included. The median age was 63 years (54-74), with the majority being female (61%). The most common cardiovascular risk factors were hypertension (52%), previous/current smoking (33%), dyslipidemia (30%), and diabetes mellitus (21%). Chest pain was the leading presenting symptom (83%), followed by dyspnea (23%) and nausea/emesis (11%). Only 4% of patients had intravascular imaging performed and 10% had cardiac MRI. For patients that had additional diagnostic work up, an underlying cause for MINOCA was identified in over half of the patients (58% of patients had cardiac MRI and 53% had intravascular imaging). Over two-thirds of MINOCA cases (70%) did not have an identifiable etiology, of which only 8% of them had additional testing (cardiac MRI and/or intravascular imaging). One-year mortality was 9%, with other short-term complications being rare. Conclusions Intravascular imaging and cardiac MRI are underutilized in the diagnosis of MINOCA patients. Among the few patients who underwent further investigations, an underlying etiology was identified in over half of the cases. MINOCA patients are still at risk of adverse cardiovascular outcomes despite it being an uncommon cause of MI. Our results will help facilitate quality improvement initiatives to increase local awareness about the diagnostic workup and treatment modalities for MINOCA patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".