Omega-3 Fatty Acids and Markers of Thrombosis in Patients with Atrial Fibrillation
Bibliographic record
Abstract
Omega-3 fatty acids (n-3 FAs) are associated with a lower risk of ischemic stroke in patients with atrial fibrillation (AF). Antithrombotic mechanisms may in part explain this observation. Therefore, we examined the association of n-3 FAs with D-dimer and beta-thromboglobulin (BTG), markers for activated coagulation and platelets, respectively. The n-3 FAs eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), docosapentaenoic acid (DPA) and alpha-linolenic acid (ALA) were determined via gas chromatography in the whole blood of 2373 patients with AF from the Swiss Atrial Fibrillation cohort study (ClinicalTrials.gov Identifier: NCT02105844). In a cross-sectional analysis, we examined the association of total n-3 FAs (EPA + DHA + DPA + ALA) and the association of individual fatty acids with D-dimer in patients with detectable D-dimer values (n = 1096) as well as with BTG (n = 2371) using multiple linear regression models adjusted for confounders. Median D-dimer and BTG levels were 0.340 ug/mL and 448 ng/mL, respectively. Higher total n-3 FAs correlated with lower D-dimer levels (coefficient 0.94, 95% confidence interval (Cl) 0.90–0.98, p = 0.004) and lower BTG levels (coefficient 0.97, Cl 0.95–0.99, p = 0.003). Likewise, the individual n-3 FAs EPA, DHA, DPA and ALA showed an inverse association with D-dimer. Higher levels of DHA, DPA and ALA correlated with lower BTG levels, whereas EPA showed a positive association with BTG. In patients with AF, higher levels of n-3 FAs were associated with lower levels of D-dimer and BTG, markers for activated coagulation and platelets, respectively. These findings suggest that n-3 FAs may exert antithrombotic properties in patients with AF.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".