Recurrent venous thromboembolism and abnormal uterine bleeding with anticoagulant and hormone therapy use
Bibliographic record
Abstract
Women receiving vitamin K antagonists (VKAs) require adequate contraception because of the potential for fetal complications. It is unknown whether the use of hormonal therapy, especially those containing estrogens, is associated with recurrent venous thromboembolism (VTE) during anticoagulation. Despite the absence of data, World Health Organization guidelines state that use of estrogen-containing contraceptives confers an "unacceptable health risk" during established anticoagulation for VTE. We compared the incidences of recurrent VTE and abnormal uterine bleeding with and without concomitant hormonal therapy in women aged <60 years who were receiving anticoagulation with rivaroxaban or enoxaparin/VKA for confirmed VTE. Incidence densities in percentage per year were computed for the on and off estrogen-containing or progestin-only therapy periods. Cox regression models were fitted, with hormonal therapy (on vs off) as a time-dependent variable to derive the hazard ratio (HR) for the effects on recurrent VTE and abnormal uterine bleeding. In total, 1888 women were included. VTE incidence densities on and off hormonal therapy were 3.7%/year and 4.7%/year (adjusted HR, 0.56; 95% confidence interval [CI], 0.23-1.39), respectively, and were 3.7%/year and 3.8%/year, respectively, for estrogen-containing and progestin-only therapy. The adjusted HR for all abnormal uterine bleeding (on vs off hormonal therapy) was 1.02 (95% CI, 0.66-1.57). Abnormal uterine bleeding occurred more frequently with rivaroxaban than with enoxaparin/VKA (HR, 2.13; 95% CI, 1.57-2.89). Hormonal therapy was not associated with an increased risk of recurrent VTE in women receiving therapeutic anticoagulation. The observed increased risk of abnormal uterine bleeding with rivaroxaban needs further exploration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".