Risk of recurrent venous thromboembolism after a first oestrogen-associated episode
Bibliographic record
Abstract
The use of exogenous oestrogen in women with otherwise unprovoked venous thromboembolism (VTE) could be considered sufficient explanation to classify VTE as provoked if the risk of recurrent VTE after 3-6 months of anticoagulant treatment is similar to the risk of recurrent VTE observed after a surgery or prolonged immobilisation. Our objective was to assess the risk of recurrent VTE in women after a first unprovoked episode on oestrogen. The REVERSE study is a cohort study of patients with a first unprovoked VTE treated with anticoagulant treatment for 5-7 months. The risk of recurrent VTE during follow-up was compared between women users and non users of oestrogen at the time of index VTE. Among the 646 patients included, 314 were women, of them 67 were current users of oestrogen at the time of their VTE: 49 were on oral contraceptives and 18 on post-menopausal hormone replacement therapy (HRT). No significant association was found between oestrogen exposure, either oral contraceptives or HRT, and a lower risk of recurrent VTE after adjustment for age, or analysis restricted to women in the same age range as oestrogen contraceptives and HRT users, respectively. The risk of recurrent VTE is low in women after a first otherwise unprovoked oestrogen-associated VTE. However, this risk is not significantly lower than in women whose VTE was not related to oestrogen use.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".