Evidence-Based Guidance on Venous Thromboembolism in Patients with Solid Tumours
Bibliographic record
Abstract
Venous thromboembolism (vte) is a serious, life-threatening complication of cancer. Anticoagulation therapy such as low molecular weight heparin (lmwh) has been shown to treat and prevent vte. Cancer therapy is often complex and ongoing, making the management of vte less straightforward in patients with cancer. There are no published Canadian guidelines available to suggest appropriate strategies for the management of vte in patients with solid tumours. We therefore aimed to develop a clear, evidence-based guideline on this topic. A systematic review of clinical trials and meta-analyses published between 2002 and 2013 in PubMed was conducted. Reference lists were hand-searched for additional publications. The National Guidelines Clearinghouse was searched for relevant guidelines. Recommendations were developed based on the best available evidence. In patients with solid tumours, lmwh is recommended for those with established vte and for those without established vte but with a high risk for developing vte. Options for lmwh include dalteparin, enoxaparin, and tinzaparin. No one agent can be recommended over another, but in the setting of renal insufficiency, tinzaparin is preferred. Unfractionated heparin can be used under select circumstances only (that is, when rapid clearance of the anticoagulant is desired). The most common adverse event is bleeding, but major events are rare, and with appropriate follow-up care, bleeding can be monitored and appropriately managed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".