Surgical and Behavioral Treatments for Vestibulodynia
Bibliographic record
Abstract
OBJECTIVE: To estimate whether treatment gains for provoked vestibulodynia participants randomly assigned to vestibulectomy, biofeedback, and cognitive-behavioral therapy in a previous study would be maintained from the last assessment-a 6-month follow-up-to the present 2.5-year follow-up. Although all three treatments yielded significant improvements at 6-month follow-up, vestibulectomy resulted in approximately twice the pain reduction as compared with the two other treatments. A second goal of the present study was to identify predictors of outcome. METHODS: In a university hospital, 51 of the 78 women from the original study were reassessed 2.5 years after the end of their treatment. They completed 1) a gynecologic examination involving the cotton-swab test, 2) a structured interview, and 3) validated pain and sexual functioning measures. RESULTS: Results from the multivariate analysis of variance conducted on the pain measures showed a significant time main effect (P<.05) and a significant treatment main effect (P<.01), indicating that participants had less pain at the 2.5-year follow-up than at the previous 6-month follow-up. Results from the multivariate analysis of variance conducted on sexual functioning measures showed that participants remained unchanged between the 6-month and 2.5-year follow-up and that there were no group differences. Higher pretreatment pain intensity predicted poorer outcomes at the 2.5-year follow-up for vestibulectomy (P<.01), biofeedback (P<.05), and cognitive-behavioral therapy (P<.01). Erotophobia also predicted a poorer outcome for vestibulectomy (P<.001). CONCLUSION: Treatment gains were maintained at the 2.5-year follow-up. Outcome was predicted by pretreatment pain and psychosexual factors. LEVEL OF EVIDENCE: II.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.005 | 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".