Dabigatran Etexilate Versus Warfarin in the Treatment of Venous Thromboembolism.
Bibliographic record
Abstract
Abstract Abstract 1 Background. The direct oral thrombin inhibitor, dabigatran etexilate, has a predictable anticoagulant effect and may be an alternative to warfarin in patients with acute venous thromboembolism (VTE). Methods. In a randomized, double-blind, trial of 2539 patients with acute VTE, treated with low molecular weight or unfractionated heparin for 5 to 11 days, we compared oral dabigatran etexilate, 150 mg twice daily in a fixed-dose, with warfarin dose-adjusted to an International Normalized Ratio of 2.0 and 3.0, each given for 6 months. The primary outcome was symptomatic, objectively confirmed recurrent VTE or VTE-related death up to 6 months of treatment. Safety endpoints included bleeding events, acute coronary syndrome, liver function tests, vital signs and adverse events. Results. Of 1274 patients randomized to dabigatran etexilate, at 6 months 30 (2.4%) had recurrent VTE compared with 27 (2.2%) of 1265 patients randomized to warfarin; risk difference 0.4% [95 percent confidence interval, −0.8 to 1.5]; p<0.0001 for prespecified non-inferiority margin. During the planned study participation, through the end of the follow-up period, there were 34 vs. 32 patients who had recurrent VTE in the dabigatran etexilate vs. warfarin treated groups, respectively (hazard ratio 1.05 [95% confidence interval, 0.065 to 1.70]). Major bleeding occurred in 20 patients treated with dabigatran etexilate and 24 patients treated with warfarin (hazard ratio 0.82; 95 percent confidence interval, 0.45 to 1.48) and any bleeding occurred in 207 versus 280 patients, respectively (hazard ratio 0.71, 95 percent confidence interval, 0.59 to 0.85). Death, acute coronary syndromes, and liver function test abnormalities were infrequent and similar in the two groups. Conclusion: Fixed-dose dabigatran etexilate is as effective and safe as warfarin in the treatment of acute VTE. Disclosures: Schulman: GSK: Honorarium for Chairman of the IDMC; Bayer HealthCare: Honorarium for Chairman of the DSMB; Boehringer-Ingelheim: Honorarium for Chairman of the Steering Committee; Sanofi-Aventis: Honorarium for Chairman of the DSMB, Research Funding. Off Label Use: Dabigatran etexilate is an oral thrombin inhibitor under investigation for anticoagulant prophylaxis or treatment in venous and arterial thrombomebolism. Kakkar:Bayer HealthCare: Consultancy, Honoraria, Research Funding, Scientific Advisory Board; Sanofi-Aventis: Consultancy, Honoraria, Research Funding, Scientific Advisory Board; Boehringer Ingelheim: Consultancy, Honoraria, Research Funding, Scientific Advisory Board; Pfizer: Consultancy, Honoraria, Research Funding, Scientific Advisory Board; Bristol–Myers Squibb: Consultancy, Honoraria, Research Funding, Scientific Advisory Board; Eisai: Consultancy, Honoraria, Research Funding, Scientific Advisory Board; Aryx therapeutics: Consultancy; GSK: Honoraria. Schellong:Bayer HealthCare: Consultancy, Honoraria, Scientific Advisory Board; Sanofi-Aventis: Consultancy, Honoraria, Scientific Advisory Board; Boehringer Ingelheim: Consultancy, Honoraria, Scientific Advisory Board; Pfizer: Scientific Advisory Board; Bristol–Myers Squibb: Consultancy, Honoraria, Scientific Advisory Board; Esai: Consultancy, Honoraria, Scientific Advisory Board; Aryx therapeutics: Consultancy; GSK: Honoraria. Baanstra:Boehringer-Ingelheim: Employment. Schnee:Boehringer-Ingelheim: Employment.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".