Dabigatran versus Warfarin for Acute Venous Thromboembolism in Elderly or Impaired Renal Function Patients: Pooled Analysis of RE-COVER and RE-COVER II
Bibliographic record
Abstract
Abstract Management of acute venous thromboembolism (VTE) with anticoagulants in elderly patients and those with chronic kidney disease poses special challenges. The RE-COVER and RE-COVER II trials showed that dabigatran 150 mg twice daily was as effective as warfarin over 6 months in preventing recurrent VTE, with a lower bleeding risk. We now assess the effects of old age and renal impairment (RI) on pooled trial outcomes in 5,107 patients: 4,504 aged <75 years and 603 aged ≥75 years. The primary efficacy outcome was symptomatic VTE/VTE-related death. Safety outcomes were centrally adjudicated major bleeding events (MBEs), MBEs or clinically relevant non-major bleeding events (MBEs/CRBEs) and any bleeds. Baseline renal function was categorized as normal, mild RI or moderate RI. A total of 3,698 had normal renal function and 1,100 and 237 had mild and moderate RI, respectively (23 patients with severe RI and 49 with missing creatinine clearance data were not included). For dabigatran, VTE/VTE-related death decreased from 3.1% (normal renal function) to 1.9% for mild RI and to 0.0% for moderate RI. For warfarin, the event rates were 2.6, 1.6 and 4.1%, respectively. Overall, major bleeding increased with increasing RI (p = 0.0037) and with age (p = 0.4350), with no apparent difference between the dabigatran and warfarin patients. Dabigatran shows better efficacy than warfarin in RI and in the elderly patients, probably because of an increase in the concentration of dabigatran. However, bleeding risk increases with both dabigatran and warfarin in the presence of RI.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.023 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".