Venous thromboembolism management: where do novel anticoagulants fit?
Bibliographic record
Abstract
OBJECTIVE: To review novel oral anticoagulant (NOAC) trials in the treatment of venous thromboembolism (VTE) and the possible use of risk-stratification tools to guide their use in practice. SCOPE: MEDLINE and Cochrane databases were searched to identify relevant journal articles published from January 1982 to February 2013. Additional references were obtained from articles extracted during the database search. FINDINGS: NOACs have been developed to optimize VTE management and overcome the limitations of heparin and vitamin K antagonists (VKA). The AMPLIFY and EINSTEIN trials of apixaban and rivaroxaban, respectively, investigated single-drug management of VTE, whereas the edoxaban Hokusai-VTE trial and dabigatran RE-COVER and RE-COVER II trials investigated the use of NOACs with a heparin lead-in. The AMPLIFY and Hokusai-VTE trials are ongoing but the EINSTEIN and RE-COVER trials have demonstrated that rivaroxaban and dabigatran, respectively, are non-inferior to parenteral anticoagulants and warfarin in the management of VTE. Differences in study design complicate the application of study results to clinical practice. There are multiple validated DVT protocols that effectively and safely treat patients in outpatient settings. The pulmonary embolism (PE) severity index (PESI), simplified PESI (sPESI), and other prognostic tools have been used to risk stratify patients with PE by estimating mortality risk to guide outpatient eligibility. CONCLUSIONS: NOACs provide physicians with new therapeutic options in the management of VTE. While heparin and VKAs compose the current standard treatment for VTE, their use will likely disappear as physicians grow comfortable with the adoption of NOACs. As studies have not clearly defined the efficacy of these agents in certain patient populations, further data in special patient populations and risk stratification through the use of VTE severity scores could potentially be adapted to guide anticoagulant management and outpatient treatment eligibility.
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".