2389Survival after myocardial infarction with non-obstructive coronary arteries (MINOCA) - A comprehensive systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Introduction Myocardial Infarction (MI) with Non-Obstructive Coronary Arteries (MINOCA) is now a recognised MI subtype. A 2013 systematic review of MINOCA literature indicated that MINOCA prognosis is favourable compared to those with MI and obstructive coronary artery disease (MICAD), but healthy controls were not included. With the growth of recent literature and evaluation of MINOCA prognosis, we performed an in-depth analysis of MINOCA prognosis, in relation to 1-year all-cause mortality and 1-year re-infarction compared with MICAD patients and a healthy cohort. Methods An unrestricted literature search was conducted on the terms “MI”, “non-obstructive”, “angiography” and “prognosis” using PubMed and Embase. Publications with non-consecutive recruitment, less than 100 MINOCA patients or selection bias (i.e. restricted age group) were excluded. MINOCA & MICAD were defined as the presence of an MI (as per the universal criteria) in the absence & presence of CAD (i.e. epicardial vessel with a stenosis ≥50% on angiography), respectively. The healthy cohort was defined as those with no history of cardiovascular diseases. Unpublished data were accumulated via the MINOCA Global Collaboration. Data from the included studies were pooled and analysed using DerSimonian-Laird random-effects meta-analysis. Heterogeneity was assessed using Cochran's Q and I2 statistics. Odds ratios (ORs), mean differences and 95% confidence intervals (CI) were calculated for proportion and continuous data respectively. Results The search identified 2889 unique publications, of which 27 included prognosis data. Of the 563660 consecutive MI patients, the overall pooled prevalence of MINOCA wasat 8.7% (95% CI: 7.5%-9.9%). The 1-year mortality and 1-year re-infarction data by diagnosis are presented in the table. Prognosis comparison by diagnosis MINOCA (n=41658) MINOCA vs MICAD MINOCA vs Healthy % (95% CI) MINOCA (n=16642) MICAD (n=174461) Mean difference or OR 95% CI MINOCA (n=8465) Healthy (n=33074) Mean difference or OR 95% CI Years or % (95% CI) Years or % (95% CI) Years or % (95% CI) Years or % (95% CI) Age 61 (60–62) 61 (59–63) 64 (63–66) 3.2 (2.2–4.2) 62 (57–66) 60 (58–63) 1.6 (−5–8.6) Female 51 (48–53) 51 (48–55) 28 (26–30) 2.8 (2.5–3.1) 56 (48–64) 38 (24–52) 2.2 (1.3–3.7) 1 year mortality 3.4 (2.9–4) 3.4 (2.9–3.9) 5.5 (4.7–6.2) 0.6 (0.5–0.7) 2.6 (1.2–4) 0.7 (0.5–1) 3.7 (1.7–8.2) 1 year Re-MI 2.7 (2.1–3.3) 2.8 (1.8–3.7) 5.7 (3.9–7.5) 0.5 (0.4–0.7) 3.5 (0–7) 0.3 (0–0.6) 14.1 (9.5–21.2) Conclusions This pooled analysis shows that MINOCA accounts for almost one in ten MI presentations. The risks of re-infarction and death among MINOCA patients are much higher than in healthy controls, but lower than for MICAD patients. Efforts are needed to improve understanding of the optimal management and secondary prevention strategies in this unique and heterogeneous population.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".