Differential benefit risk assessment of DOACs in the treatment of venous thromboembolism: focus on dabigatran
Bibliographic record
Abstract
Venous thromboembolism includes deep vein thrombosis and pulmonary embolism and is a serious medical condition that requires anticoagulation as part of treatment. Currently, standard therapy consists of parenteral anticoagulation followed by a vitamin K antagonist (VKA). The pharmacokinetic and pharmacodynamic profiles of the direct oral anticoagulants (DOACs) differ from VKAs, which overcome some of the limitations of VKAs and have practical implications on their use in clinical situations. Dabigatran is a prodrug that undergoes primarily renal elimination and does not affect cytochrome P450 enzymes. Assays to quantify the degree of anticoagulation and the therapeutic level of DOAC are either unavailable for routine clinical use or require specific calibration. Routine monitoring of DOACs is not recommended at this time. Dabigatran, rivaroxaban, and apixaban are DOACs that have been studied for treatment of venous thromboembolism. Clinical trials comparing DOACs with standard therapy have shown them to be non-inferior for acute and extended therapy. Each DOAC has a unique benefit and harm profile that should be considered prior to use. The distinguishing characteristics of dabigatran include a requirement of parenteral anticoagulation prior to acute treatment, clinical trial results comparing it with a VKA for extended treatment, association with upper gastrointestinal adverse events, and increased risk of gastrointestinal bleed. Rivaroxaban is the only DOAC that has once-daily dosing while apixaban is the only DOAC that has lower risk of overall, major, and gastrointestinal bleeding compared with VKA. A common drawback of DOACs is the lack of an available reversal agent. Clinical trials of reversal agents are ongoing and one application for approval has been submitted to the US Food and Drug Administration. Selection of a DOAC for acute and extended therapy requires a shared decision-making approach that includes a comprehensive assessment of the benefits and harms of each individual DOAC.
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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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".