Herbs, vitamins and minerals in the treatment of premenstrual syndrome: a systematic review.
Bibliographic record
Abstract
BACKGROUND: As many women experiencing symptoms of premenstrual syndrome (PMS) seek relief from natural products (NP), health care providers should have quality information available to aid women in making evidence-based decisions regarding use of these products. OBJECTIVE: To identify herbs, vitamins and minerals advocated for the treatment of PMS and/or PMDD and to systematically review evidence from randomized controlled trials (RCTs) to determine their efficacy in reducing severity of PMS/PMDD symptoms. METHODS: Searches were conducted from inception to April 2008 in Clinical Evidence, The Cochrane Library, Embase, IBID, IPA, Mayoclinic, Medscape, MEDLINE Plus, Natural Medicines Comprehensive Database and the Internet to identify RCTs of herbs, vitamins or minerals advocated for PMS. Bibliographies of articles were also examined. Included studies were published in English or French. Studies were excluded if patient satisfaction was the sole outcome measure or if the comparator was not placebo or recognized therapy. RESULTS: Sixty-two herbs, vitamins and minerals were identified for which claims of benefit for PMS were made, with RCT evidence found for only 10. Heterogeneity of length of trials, specific products and doses, and outcome measures precluded meta-analysis for any NP. Data supports the use of calcium for PMS, and suggests that chasteberry and vitamin B6 may be effective. Preliminary data shows some benefit with ginkgo, magnesium pyrrolidone, saffron, St. John's Wort, soy and vitamin E. No evidence of benefit with evening primrose oil or magnesium oxide was found. CONCLUSION: Only calcium had good quality evidence to support its use in PMS. Further research is needed, using RCTs of adequate length, sufficient sample size, well-characterized products and measuring the effect on severity of individual PMS 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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".