Circulating miRNAs Related to Long-term Adverse Cardiovascular Events in STEMI Patients: A Nested Case-Control Study
Bibliographic record
Abstract
BACKGROUND: Long-term morbidity and mortality of patients with ST-segment-elevation myocardial infarction (STEMI) after primary percutaneous coronary intervention (PCI) remain substantial. Circulating microRNAs (miRNAs) play an important role in cardiovascular disease development. We aimed to identify circulating miRNAs associated with adverse cardiovascular events after acute myocardial infarction (AMI). METHODS: We performed a prospective, nested, case-control study of 932 patients with STEMI who underwent primary PCI. A 3-phase approach was conducted to screen candidate circulating miRNAs in 70 patients who subsequently experienced cardiac death, hospitalization for heart failure, or recurrent AMI (major adverse cardiovascular events [MACE] group) and in 140 patients matched for age, sex, time from symptom onset to blood collection and dual-antiplatelet therapy who did not report adverse cardiovascular events during 2-year follow-up (non-MACE group). RESULTS: We found that miR-26a-5p, miR-21-5p, and miR-191-5p levels were lower in the MACE group than in the non-MACE group (all P < 0.001). Multivariate conditional logistic regression analysis revealed that miR-26a-5p, miR-21-5p, and miR-191-5p levels were significantly inversely associated with incident primary composite outcomes (all adjusted P < 0.01). Importantly, the combination of these 3 miRNAs plus B-type natriuretic peptide clearly improved the risk scores recommended in the current guidelines, as determined with the use of C-statistics, net reclassification, and integrated discrimination. CONCLUSIONS: Our study provides proof-of-concept in humans that circulating miRNAs are associated with increased rates of distinct cardiovascular events, suggesting that they can serve as effective prognostic biomarkers and therapeutic targets for patients with AMI.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".