Galectin‐3 and risk of atrial fibrillation: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Galectin-3 is an inflammatory marker that is raised in myocardial fibrosis and inflammation. Recent studies have explored its role in predicting atrial fibrillation (AF) outcomes. The aim of this systematic review and meta-analysis is to examine the association between serum concentration of galectin-3 and AF. METHODS: PubMed, EMBASE, and the Cochrane Database were searched. A total of 280 studies were identified, of which 28 studies involving 10 830 patients were included in our meta-analysis. RESULTS: Galectin-3 is present at higher concentrations in patients with AF than those in sinus rhythm (mean difference [MD] = -0.68 ng/mL, 95% CI: -0.92, -0.44, Z = 5.61, P < .00001). Galectin-3 levels were significantly higher in the persistent AF than in the paroxysmal AF group (MD = -0.94 ng/mL, 95% CI: -1.85, -0.03, Z = 2.04, P = .04). Higher galectin-3 levels were associated with a 45% increase in the odds of developing AF (odds ratio [OR] = 1.45, 95% CI: 1.15, 1.83, Z = 3.11, P = .002) and risk of AF recurrence (hazard ratio [HR] =1.17, 95% CI: 1.06, 1.29, Z = 3.12, P = .002). CONCLUSIONS: Our meta-analysis found that galectin-3 is significantly higher in patients with persistent AF than in those with paroxysmal AF, and can predict both AF development and recurrence after treatment.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.030 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".