Hormone replacement therapy and risk for venous thromboembolism: what??s new and how do these findings influence clinical practice?
Bibliographic record
Abstract
PURPOSE OF REVIEW: Although an association between hormone replacement therapy and venous thromboembolism has been established, several unanswered questions remain. This review will address additional questions relating to hormone replacement therapy and venous thromboembolism. Does the risk for venous thromboembolism differ according to the type of hormone replacement therapy? Does the presence of thrombophilia influence the risk for venous thromboembolism in hormone replacement therapy users? Should hormone replacement therapy be temporarily interrupted around the time of surgery? RECENT FINDINGS: The risk for venous thromboembolism seems to be less in users of estrogen-only hormone replacement therapy (odds ratio = 1.2; 95% confidence interval: 0.6-2.6) than in users of estrogen-progestin hormone replacement therapy (odds ratio = 2.7; 95% confidence interval: 1.4-5.1), and there may be no increased risk for venous thromboembolism with transdermal hormone replacement therapy (odds ratio = 1.0; 95% confidence interval: 0.3-3.3). The presence of a prothrombotic blood abnormality, such as the factor V Leiden mutation, seems to further increase the risk for venous thromboembolism in hormone replacement therapy users (odds ratio = 17.1; 95% confidence interval: 3.7-78). Continued use of hormone replacement therapy in the perioperative period does not seem to have an impact on the overall risk for postoperative venous thromboembolism (odds ratio = 0.66; 95% confidence interval: 0.35-1.18). SUMMARY: Recent studies have extended our understanding regarding the association between hormone replacement therapy and venous thromboembolism. The implications of these findings on clinical practice are discussed.
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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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".