Anatomical and Dermatologic Manifestations of Estrogen Deficiency in Postmenopausal Women: A Systematic Review
Bibliographic record
Abstract
Estrogen deficiency after menopause contributes to structural and symptomatic changes in genital, cutaneous, and adnexal tissues, yet available evidence remains scattered across clinical and imaging disciplines. Objectives: To summarize contemporary evidence on anatomical and dermatologic manifestations of estrogen deficiency in postmenopausal women and to evaluate the effects of local hormonal and device-based treatments. Methods: A systematic review following PRISMA 2020 guidelines. PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar were searched for English-language studies from 1 January 2017 to 31 December 2024. Eligible designs included randomized controlled trials, observational and cross-sectional studies, imaging investigations, and pilot interventions involving naturally or surgically postmenopausal women. Outcomes included clinical signs, symptom scores, imaging parameters, and dermatologic manifestations. Risk of bias was assessed using the Cochrane RoB-2 tool for randomized trials and the Newcastle–Ottawa Scale for observational and imaging studies. Results: Eighteen studies met the inclusion criteria. Randomized trials of low-dose vaginal estradiol and selective estrogen receptor modulators improved vaginal pH, Vaginal Health Index, Vaginal Maturation Index, dryness, and dyspareunia with minimal systemic absorption. Dermatology-focused cohorts commonly reported xerosis, pruritus, dermatoses, nail fragility, and female-pattern hair loss. Imaging studies demonstrated reduced dermal and vaginal wall thickness and altered echogenicity. Evidence for fractional CO₂ laser and radiofrequency remained limited to small pilot studies with short follow-up. Conclusions: Estrogen deficiency is consistently associated with measurable structural and symptomatic changes in genital and cutaneous tissues. Local estrogen therapy offers reliable short-term benefits, whereas device-based interventions remain investigational and require larger controlled trials.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".