Dose Escalation of Low Molecular Weight Heparin to Manage VTE Treatment Failure in Cancer Patients
Bibliographic record
Abstract
Abstract Introduction: Cancer patients with venous thromboembolism (VTE) are at high risk of treatment failures (i.e. recurrent VTE while on therapeutic anticoagulants). Management of these treatment failures is controversial/poorly studied. Whereas some clinicians recommend inferior vena cava (IVC) filter insertion, others do not. We sought to assess the efficacy and safety of escalating the dose of low-molecular weight heparin (LMWH) in the management of treatment failure recurrent VTE in cancer patients. Methods: Retrospective cohort study of outpatients with cancer and treatment failure recurrent VTE seen at the Ottawa Hospital Thrombosis Unit from January 2007 to June 2008. Patients were followed for three months following the treatment failure event. Results: Thirty cancer patients had recurrent VTE despite ongoing anticoagulation. The mean age was 60.7 years. Twenty two patients (73.3%) were on LMWH treatment at the time of the recurrent event. Of these 22 patients, 4 (18.2%) were on full (100%) therapeutic doses, 15 (68.2%) on 75% of therapeutic doses and 3 (13.6%) on prophylactic doses of LMWH. All 4 patients on full therapeutic dose were treated by increasing the weight-adjusted dose of LMWH by 20% for 6 weeks. Patients on 75% of therapeutic doses were treated by increasing the weight-adjusted LMWH by 25% for 6 weeks (4/15 patients) or 3 months (11/15 patients). All three patients on prophylactic doses were treated with one month of full therapeutic doses of LMWH followed by 75% thereafter. No patients had an IVC filter inserted or a major bleeding episode. One patient had a minor bleeding episode (4.5%; 95% CI: 1.1–21.9%), 2 patients died (9.1%; 95% CI: 2.8–28.0) (no VTE-related death) and one patient (4.5%; 95% CI: 1.1–21.9%) had a second treatment failure event during the three-month follow-up period while on full therapeutic doses of LMWH. Eight patients (26.7%) were on vitamin-K antagonist at the time of the recurrent VTE due to treatment failure. Five (62.5) patients had a therapeutic INR on the day of the recurrent VTE. All patients were treated with LMWH at full doses for a month followed by 75% thereafter. One patient (12.5%; 95%CI 2.8–48.3) had a minor bleeding episode during follow-up. Conclusion: Escalading the dose of LMWH following a recurrent VTE due to treatment failure seems to be a safe and effective method to prevent further recurrence in cancer patients. Our data challenges the concept of using IVC filters in this setting.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".