GALECTIN-3 AND LONG-TERM CARDIOVASCULAR RISK IN PATIENTS WITH MYOCARDIAL INFARCTION TREATED WITH PCI: A META-ANALYSIS OF 5,457 PATIENTS
Bibliographic record
Abstract
Novel Biomarkers Residual cardiovascular risk remains a challenge after successful percutaneous coronary intervention in patients with myocardial infarction (MI). Galectin-3, a biomarker of inflammation and fibrosis, has been proposed as a prognostic tool, but its predictive value for long-term cardiovascular events post-PCI is not well defined. We conducted a systematic review and meta-analysis to evaluate the association between Galectin-3 levels and major adverse cardiovascular events (MACE) in this population. We conducted a systematic review and meta-analysis following PRISMA guidelines. Pubmed, Embase, Web of Science, and CENTRAL were searched for prospective cohort studies reporting hazard ratios (HRs) for MACE in relation to Galectin-3 levels measured at baseline in post-PCI patients with MI. Only studies reporting multivariable-adjusted HRs were included. A random-effects model was used to calculate the pooled HR. Risk of bias was assessed using the Newcastle-Ottawa Scale. A total of five prospective cohort studies were included, involving 5,457 patients with myocardial infarction treated with PCI. In all studies, Galectin-3 was measured in close proximity to the index PCI, typically during hospitalization, and patients were stratified according to biomarker concentration (high vs. low). The primary outcome was major adverse cardiovascular events (MACE), consistently defined across studies as a composite of all-cause mortality, nonfatal myocardial infarction, stroke, and repeat revascularization. The pooled adjusted hazard ratio for elevated Galectin-3 levels was 1.75 (95% CI: 1.37–2.23; p < 0.00001), indicating a 75% increased relative risk of long-term MACE in patients with higher Galectin-3 levels. All included studies reported hazard ratios derived from multivariable Cox regression models, adjusted for major clinical covariates including age, sex, diabetes, hypertension, renal function, and left ventricular ejection fraction. Elevated Galectin-3 levels identify post-MI patients at increased risk of long-term adverse cardiovascular events, regardless of revascularization success. This biomarker may uncover residual biological risk not captured by conventional imaging or clinical scores. These findings support its integration into risk assessment models and suggest a potential role for Galectin-3 in advancing precision-based preventive strategies.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.046 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".