Method of limits: Female genital stretch perception thresholds
Bibliographic record
Abstract
INTRODUCTION: Women with pelvic organ prolapse describe vaginal laxity and poor sensation of vaginal tone that does not correlate with anatomical findings. This discrepancy could be explained by altered vaginal sensation and a test that could measure sensation of vaginal tone, transmitted via Aα and Aβ nerve fibers, would further our understanding of the pathophysiology of vaginal laxity. OBJECTIVE: To develop quantitative sensory testing (QST) for vaginal tone using genital stretch perception thresholds (PT), assess reproducibility, and the association with age and parity. STUDY DESIGN: Prospective observational cohort study of healthy women (Canadian task force classification II-2) who underwent QST method of limits at the vagina and introitus for sensation of first awareness and stretch using a modified anorectal physiology protocol. RESULTS: Forty women underwent repeatability testing. Intra- and inter-rater repeatability using intraclass correlation coefficients (ICC) was good to excellent for both first awareness and stretch at the vagina and introitus (intra-rater ICC = 0.93, 0.95, 0.81, and 0.88, respectively; inter-rater ICC = 0.83, 0.93, 0.71, and 0.86 respectively). Normative data were collected from 100 women. Log-linear regression found a significant association between age and PT for first awareness and stretch at the vagina and introitus (P = .020, .008, .002, and <.001, respectively). There was no association with parity and PT. Nomograms were calculated using the 95% confidence limits around the regression line. CONCLUSIONS: Stretch QST is clinically feasible, valid, and reproducible. The test can be used as a tool to measure sensation in women presenting with symptoms of vaginal laxity.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".