Family planning, sexual activity and contraception in hereditary hemorrhagic telangiectasia: a European survey study
Bibliographic record
Abstract
BACKGROUND: Hereditary hemorrhagic telangiectasia (HHT) can influence the quality of life and social relationships, mostly due to epistaxis, but the topics of family planning, sexual activity and contraception have not been investigated to date. This study aimed to gain more insight: what is the influence of HHT on family planning, sexual activity and contraception? METHODS: This multi-language European survey study included a patient's and partners' version of a questionnaire designed specifically for this study. HHT patients were informed about the study through HHT expert centres, social media and websites of patient associations. Data collection took place between March- May 2023. RESULTS: The survey was completed by 572 patients with a definite HHT diagnosis, based on genetic confirmation or ≥ 3 Curaçao criteria. In most patients, HHT did not affect relationship decisions (n = 353, 62%), decisions concerning pregnancy and children (n = 287, 50%) and sexual activity (n = 315, 57%). However, 28% of HHT patients (n = 157) did experience effect on sexual activity and may benefit from improved epistaxis management and better awareness of their partners. CONCLUSIONS: HHT did not affect family planning decisions and sexual activity in most patients, but approximately a quarter of patients experienced effect on sexual activity caused by epistaxis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".