Anticoagulation in the Treatment of Established Venous Thromboembolism in Patients With Cancer
Bibliographic record
Abstract
Cancer-associated thrombosis is a frequent and costly complication in patients with cancer. Significant morbidity and mortality not only result from thrombotic events, but may also occur as a result of the therapeutic interventions. The established treatment for cancer-associated thrombosis is anticoagulant therapy. Of the few options available, low molecular weight heparin (LMWH) is the preferred agent because of its efficacy, safety, and convenience. Alternatives to LMWH have undesirable limitations and have demonstrated poorer efficacy and safety in the oncology population. Treatment of recurrent thrombosis, patients with concurrent bleeding issues, role of vena cava filter insertion, and duration of therapy are all areas in need of urgent research. Treatment of cancer-associated thrombosis remains a challenging task and is limited by the paucity of evidence-based data. Research is urgently needed to advance current practice and improve patient care.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".