The efficacy and safety of anticoagulation for the management of gonadal vein thrombosis: A systematic review and pooled analysis
Bibliographic record
Abstract
Gonadal vein thrombosis (GVT) is an uncommon condition that has been associated with different risk factors (e.g., post-partum period, cancer, recent pelvic surgery, etc.). The optimal management of GVT remains unclear. We sought to assess the efficacy and safety of anticoagulation therapy in adult patients with GVT. A systematic search of MEDLINE, EMBASE and PubMed, from inception to February 2023 was performed. The primary efficacy outcome was recurrent venous thromboembolism (VTE). Bleeding outcomes were assessed in the form of major and clinically relevant non-major bleeding (CRNMB) events. Incidence rates of the outcomes were pooled using the random effects model and expressed as event per 100 patient-years with its associated 95 % confidence intervals (CI) using R software. A total of 14 observational studies and one randomized controlled trial (1134 patients) with GVT met the inclusion criteria and were included in the review. Overall, 429 (37.8 %) patients were treated with anticoagulation. The rate of recurrent VTE was 3.1 per 100 patient-years (95 % CI, 1.6–6.3). The rate of major bleeding and CRNMB events were 1.0 (95 % CI; 0.2–4.5) and 9.9 (95 % CI; 2.6–37.8) per 100 patient-years, respectively. Gonadal vein thrombosis seems to be associated with a relatively low risk of recurrent VTE and bleeding complications. The risk benefit ratio of anticoagulant therapy remains unclear in this patient population.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.019 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".