Canadian consensus recommendations on the management of venous thromboembolism in patients with cancer. Part 2: treatment
Bibliographic record
Abstract
Patients with cancer are at increased risk of venous thromboembolism (vte). Anticoagulation therapy is used to treat vte; however, patients with cancer have unique clinical circumstances that can often make decisions surrounding the administration of therapeutic anticoagulation complicated. No national Canadian guidelines on the management of established cancer-associated thrombosis have been published. We therefore aimed to develop a consensus-based, evidence-informed guideline on the topic.PubMed was searched for clinical trials and meta-analyses published between 2002 and 2013. Reference lists of key articles were hand-searched for additional publications. Content experts from across Canada were assembled to review the evidence and make recommendations.Low molecular weight heparin is the treatment of choice for cancer patients with established vte. Direct oral anticoagulants are not recommended for the treatment of vte at this time. Specific clinical scenarios, including the presence of an indwelling venous catheter, renal insufficiency, and thrombocytopenia, warrant modifications in the therapeutic administration of anticoagulation therapy. Patients with recurrent vte should receive extended (>3 months) anticoagulant therapy. Incidental vte should generally be treated in the same manner as symptomatic vte. There is no evidence to support the monitoring of anti–factor Xa levels in clinically stable cancer patients receiving prophylactic anticoagulation; however, levels of anti–factor Xa could be checked at baseline and periodically thereafter in patients with renal insufficiency. Follow-up and education about the signs and symptoms of vte are important components of ongoing patient care.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".