Dabigatran etexilate and reduction in serum apolipoprotein B
Bibliographic record
Abstract
OBJECTIVE: Carboxylesterases, which convert dabigatran etexilate to its active form, dabigatran, have also been shown to influence lipoprotein metabolism, although any pleotropic effects of the drug based on this possible mechanism has not been evaluated. We examined the effects of dabigatran etexilate on serum lipoprotein markers in the Randomized Evaluation of Long-Term Anticoagulation Therapy (RE-LY) study. METHODS: 2513 participants from the RE-LY randomised control trial with baseline and 3-month apolipoprotein B (ApoB) and apolipoprotein A1 (ApoA1) measurements were included. We prospectively compared the effects of dabigatran 110 mg twice daily, dabigatran 150 mg twice daily and warfarin on changes in ApoB and ApoA1 concentrations using a mixed model analysis. RESULTS: From baseline to 3 months, a significant reduction in ApoB concentration was observed with low-dose dabigatran (-0.057 (95% CI -0.069 to -0.044) g/L, p<0.001) and high-dose dabigatran (-0.065 (95% CI -0.078 to -0.053) g/L, p<0.001) but not warfarin (-0.006 g/L (95% CI -0.018 to 0.007) g/L, p=0.40). Compared with warfarin, ApoB reduction was significantly greater with both doses of dabigatran (p<0.001 for both groups). Reductions in ApoA1 concentrations did not statistically differ with either dose of dabigatran when compared with warfarin. CONCLUSIONS: Dabigatran is associated with a significant (∼7%) reduction in ApoB concentration, suggesting a novel effect of this drug on lipoprotein metabolism. Further studies are needed to determine the mechanism of this observed effect, and its impact on clinical outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".