P1665: USE OF DOACS IN THE MANAGEMENT OF UPPER EXTREMITY DEEP VENOUS THROMBOSIS; A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Topic: 34. Thrombosis and vascular biology - Biology & Translational Research Background: Upper extremity deep venous thrombosis (UEDVT) is increasing in prevalence and often provoked by unique risk factors determining its incidence and recurrence. While direct oral anticoagulants (DOACs) remain the cornerstone of lower extremity DVT management, its efficacy and safety in UEDVT remain unclear as such events were excluded from clinical trials leading to DOAC approval. Aims: To synthesize primary evidence on the clinical efficacy and safety profile of DOACs in UEDVT. Methods: We conducted a search of MEDLINE, Embase, Scopus, conference proceedings and clinical trial registers from inception to October 2022. We included randomized controlled trials (RCTs) and cohort studies of DOACs compared with conventional treatment. Two reviewers screened and extracted data at title/abstract and full-text levels individually and in duplicate. The relative risk of recurrent VTE and bleeding events were then estimated using a fixed effect meta-analysis. Results: Of the 2224 articles screened, 3 retrospective and 2 prospective cohort studies including 451 patients were selected. The included DOACs are rivaroxaban, apixaban and edoxaban; conventional treatment consisted of low molecular weight heparin and vitamin K antagonists. There was no statistically significant difference between DOACs and conventional treatment for the risk of recurrent VTE (RR 0.95, 95% CI 0.35-2.57), major bleeding (RR 0.5, 95% CI 0.12-2.13), and clinically relevant non-major bleeding (RR 0.94, 95% CI 0.36-2.44). DOACs may reduce the risk of major bleeding in comparison with conventional treatment. No heterogeneity was found across trials. Summary/Conclusion: DOACs seem as effective as conventional treatment in the management of UEDVT and there is a trend towards decreased major bleeding. Use of DOAC in patients with UEDVT may be favored given their ease of administration and fewer monitoring requirements. RCTs in this area are needed given the limited evidence available.Keywords: Anticoagulation, DVT
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".