Differential Effect of B-Vitamin Therapy by Antiplatelet Use on Risk of Recurrent Vascular Events After Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although several randomized controlled trials failed to show a benefit of B vitamin therapy on composite outcomes of cardiovascular death, myocardial infarction, and stroke among individuals with elevated homocysteine, recent post hoc analyses have suggested that several factors may interact with the effects of vitamin treatment. One post hoc analysis revealed an interaction between B vitamin therapy and antiplatelet use; however, those results have not been replicated in other studies or populations. METHODS: We conducted a post hoc analysis of the Vitamin Intervention for Stroke Prevention (VISP) trial, a randomized controlled trial evaluating treatment with high- versus low-dose B vitamin therapy for secondary prevention of vascular events among stroke survivors with elevated homocysteine. Cox regression models were used to assess primary (recurrent stroke) and secondary (stroke, myocardial infarction, or vascular death) outcomes among individuals on high- versus low-dose vitamin therapy, categorized by antiplatelet use, after adjusting for covariates. RESULTS: Among 3680 participants, 52% took antiplatelet medications. When compared with low-dose therapy, high-dose vitamin therapy was associated with higher stroke risk among individuals on antiplatelets (hazard ratio, 1.43; 95% confidence interval, 1.02-2.01), but trended toward lower risk among those not on antiplatelets (hazard ratio, 0.86; 95% confidence interval, 0.62-1.19). CONCLUSIONS: High-dose B vitamin therapy may be associated with a higher risk of recurrent stroke among stroke survivors taking antiplatelets, but does not have a significant effect on recurrent stroke risk in those who are not on antiplatelets. Future randomized controlled trials may consider evaluating the effect of homocysteine lowering among stroke survivors with elevated homocysteine who are not on antiplatelet therapy.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.002 | 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".