Effectiveness of hormones in postmenopausal pelvic floor dysfunction—International Urogynecological Association research and development—committee opinion
Bibliographic record
Abstract
INTRODUCTION AND HYPOTHESIS: There is clear evidence of the presence of estradiol receptors (ERs) in the female lower urinary and genital tract. Furthermore, it is a fact that estrogen deficiency after menopause may cause atrophic changes of the urogenital tract as well as various urinary symptoms. Moreover, the effect of hormone replacement therapy (HRT) on urinary incontinence (UI) symptoms as well as pelvic organ prolapse (POP), anal incontinence (AI) and vulvovaginal symptoms (VVS) is still a matter of debate. This committee opinion paper summarizes the best evidence on influence of sex steroids as well as hormonal treatment (local and systemic) in postmenopausal women with pelvic floor disorders. METHODS: A working subcommittee from the International Urogynecology Association (IUGA) Research and Development Committee was formed. A thorough literature search was conducted and an opinion statement expressed. The literature regarding hormones and pelvic floor disorders was reviewed independently and summarized by the individual members of the sub-committee. RESULTS: The majority of studies reported that vaginal estrogen treatment when compared with placebo has more beneficial effects on symptoms and signs of vaginal atrophy including sensation of burning, dyspareunia and UI symptoms. Definitive evidence on local estrogen application and prolapse treatment or prevention is lacking. A statistically significant increase in risk of worsening of UI as well as development of de novo incontinence was observed with estrogen-only or combination systemic HRT. CONCLUSIONS: In summary, local estrogen seems to be safe and effective in the treatment of VVS and can also improve urinary symptoms in postmenopausal patients with UI, but most of these recommendations correspond to evidence level 2C. The evidence in POP is still scarce but not in favor of benefit. Finally, the duration of local estrogen treatment (LET), optimal dosage, long-term effects and cost-effectiveness compared with current practice are still unknown.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.051 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.014 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".