A Randomized Clinical Trial of the Impact of Local Estrogen on Postoperative Tissue Quality After Vaginal Reconstructive Surgery
Bibliographic record
Abstract
OBJECTIVE: To evaluate the use and effect of early administration of vaginal estrogen via a continuous low-dose estradiol vaginal ring placed immediately after pelvic reconstructive surgery. METHODS: This was a randomized controlled trial of 65 postmenopausal women undergoing vaginal reconstructive surgery. The subjects were randomly assigned to receive an estradiol-releasing vaginal ring, placebo vaginal ring, or control without vaginal ring for 12 weeks immediately after vaginal reconstructive surgery. The primary outcome was tissue quality based on vaginal maturation 3 months postoperatively. Secondary outcome measures were subjective and objective signs of atrophy; vaginal pH; the presence of granulation tissue, microscopic inflammation, and major healing abnormalities; and the ability to tolerate an intravaginal ring. RESULTS: At 12 weeks, the estradiol ring group had a significantly improved maturation value (P<0.01) and objective atrophy assessment (P<0.01) compared with the placebo ring and control arms. Granulation tissue was increased in the placebo ring arm (P<0.01). Subjective atrophy scores did not differ among the groups (P=0.39). CONCLUSIONS: Early administration of vaginal estrogen after vaginal surgery via an estradiol-releasing ring is feasible and results in improved markers of tissue quality postoperatively compared to placebo and controls.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".