A Multicenter Prospective Cohort Study on the Use of Weight‐Adjusted Dalteparin in Patients Over 90 kg With Acute Cancer‐Associated Venous Thromboembolism—The <scp>WAVe</scp> Study
Bibliographic record
Abstract
Patients with cancer-associated thrombosis (CAT) are commonly treated with low-molecular-weight heparin (LMWH), but whether dose capping is needed in patients over 90 kg is unclear. We conducted the WAVe study, a multicenter prospective cohort study in adult patients (≥ 18 years) with acute CAT and a weight of over 90 kg starting anticoagulation. Patients received weight-adjusted dalteparin at 200 IU/kg per day (up to 33 000 IU) for 30 (± 4) days, after which anticoagulation was continued per clinician discretion and followed for 6 months. The primary outcome was major bleeding (MB) at 30 days. Secondary outcomes included objectively confirmed recurrent venous thromboembolism (VTE) at 30 days and trough anti-Xa levels. The cumulative incidences of outcomes were estimated by time-to-event analysis, with death as a competing risk. The study stopped early due to recruitment challenges after 91 patients. Median weight and daily dose of dalteparin were 107.5 kg and 22 500 IU, respectively. Three patients had a MB episode for a cumulative incidence of 5.3% (95% CI 1.1%-14.8%) at 30 days. One patient had recurrent VTE for a cumulative incidence of 1.2% (95% CI 0.1%-5.7%) at 30 days. No significant bioaccumulation noted up to Day 30 based on trough anti-Xa levels. The median Day 7 trough anti-Xa levels were higher in those with bleeding events within 30 days compared to those without (0.6 vs. 0.2 IU/mL, p = 0.01). Our results suggest that weight-adjusted dosing of dalteparin in patients over 90 kg is associated with acceptable rates of bleeding and thrombosis. Trial Registration: NCT03297359.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".