Determining the Impact of Combination Oral Contraceptives on Von Willebrand Factor and Factor VIII in Healthy Patients and Patients With Von Willebrand Disease: A Scoping Review and Meta‐Analysis
Bibliographic record
Abstract
INTRODUCTION: Von Willebrand disease (VWD) is a bleeding disorder characterized by a deficiency or dysfunction of Von Willebrand factor (VWF) and/or Factor VIII (FVIII), critical coagulation proteins. Individuals with VWD often use combination oral contraceptives (COCs) to manage heavy menstrual bleeding. However, the impact of COCs on VWF and FVIII levels and whether COC use affects VWD diagnosis is unclear. AIM: To review the literature and assess the impact of COCs on FVIII and VWF. METHODS: This scoping review used the OVID platform in the MEDLINE, EMBASE and Cochrane databases. Keywords "combination oral contraceptives," "von Willebrand Factor," "Factor VIII" and "von Willebrand Disease" were searched. Primary studies exploring the impact of COCs on VWF and/or FVIII in patients of reproductive age were included. Article titles and abstracts were screened, followed by full-text reviews, data extraction and a meta-analysis. RESULTS: Twenty-seven studies were included. In healthy patients, 11 studies reported no change in VWF levels, while three found changes in VWF levels. Nine studies reported no change in FVIII levels, while 10 studies observed an increase. In patients with VWD, two studies found no significant change in VWF or FVIII levels. Meta-analysis revealed there was no significant difference in VWF% (Estimate: 2.62 (95%CI -0.5905, 5.831); p value: 0.4033) or FVIII% (Estimate: 2.99 (95%CI -4.85, 10.82); p value: 0.4552) with COC use. CONCLUSION: The meta-analysis revealed no difference in VWD or FVIII levels between participants with and without COCs. The lack of observed differences suggests that COCs do not interfere with accurate VWD diagnosis.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".