Bioidentical Progesterone Cream for Menopause-Related Vasomotor Symptoms: Is it Effective?
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy of bioidentical progesterone cream in the treatment of menopause-related vasomotor symptoms. DATA SOURCES: A systematic search (from time of inception to September 2012) of PubMed, EMBASE, International Pharmaceutical Abstracts, International Journal of Pharmaceutical Compounding, Cochrane, and CINAHL was conducted using the terms progesterone, vasomotor symptoms, night sweats, hot flash or flush, and randomized controlled trials (RCTs). Hand-searching of citations from relevant articles was also performed. STUDY SELECTION AND DATA EXTRACTION: Articles selected for inclusion described RCTs evaluating the use of bioidentical progesterone cream for the treatment of menopause-related vasomotor symptoms. Studies included were placebo controlled and participants were postmenopausal women experiencing vasomotor symptoms. DATA SYNTHESIS: Searching identified 3 published RCTs. Only one study, which used a bioidentical progesterone cream specifically compounded for the trial, found that the bioidentical progesterone was more effective than placebo in relieving menopause-related vasomotor symptoms. The 2 studies using manufactured bioidentical progesterone creams found that the creams were no more effective than placebo. Vaginal bleeding and headaches were the most commonly reported adverse effects in the studies. CONCLUSIONS: Available evidence from RCTs does not support the efficacy of bioidentical progesterone cream for the management of menopause-related vasomotor symptoms. Adverse effects appear to be mild and self-limiting.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".