Validation of a clinical tool for vestibular trophism in postmenopausal women
Bibliographic record
Abstract
OBJECTIVE: This study aimed to develop and validate a clinical tool to assess vestibular trophism in women with genitourinary syndrome of menopause (GSM). METHODS: In this cross-sectional study, the principal investigator's center and three external reviewers assessed the vestibular images of postmenopausal women using a multi-item tool defined as vestibular trophic health (VeTH), which assessed five criteria: petechiae, pallor, thinning, dryness and redness. Dryness, dyspareunia, vulvar pain and the Vaginal Health Index (VHI) were also evaluated. RESULTS: Analysis of the intraclass correlation coefficient (0.76; confidence interval 0.62-0.82) and Cronbach's alpha coefficient (0.78; confidence interval 0.64) indicated an inter-rater reliability and reproducibility of VeTH in the 70 women enrolled in the study. The observed covariance between a high VeTH score and the symptom severity demonstrated a significant correlation, which was not evident between VeTH and the total VHI score. CONCLUSIONS: The vulvar vestibule is the main location of genital tenderness, primarily responsible for burning/pain and entry dyspareunia because of its capacity to develop an excess of nociceptors upon sexual hormone deprivation. Our study indicated that VeTH can be a reproducible tool for the morphological classification of vestibular trophism and bears a significant correlation with the severity of the symptoms.
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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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".