Safety and efficacy of chastetree (Vitex agnus-castus) during pregnancy and lactation.
Bibliographic record
Abstract
BACKGROUND: There is a lack of basic knowledge on the part of both clinicians and patients as to the indications for use and safety of herbs used during pregnancy and lactation. This is one article in a series that systematically reviews the evidence for herbs commonly used during pregnancy and lactation. OBJECTIVES: To systematically review the literature for evidence on the use, safety and pharmacology of chastetree, focusing on issues pertaining to pregnancy and lactation. METHODS: We searched 7 electronic databases and compiled data according to the grade of evidence found. RESULTS In pregnancy, there is poor evidence based on theoretical and expert opinion and in vitro studies that chastetree may have estrogenic and progesteronic activity, uterine stimulant activity, emmenagogue activity and prevent miscarriages. In lactation, theoretical and expert opinion conflict as to whether chastetree increases or decreases lactation. CONCLUSIONS: Given its relatively common use amongst women of childbearing age, it is likely that some women may consume chastetree while unknowingly pregnant. Complementary and alternative medicine, midwifery and medical practitioners should be aware of this fact when prescribing chastetree to women of childbearing age, particularly when the patient is planning a family. Key words: Chastetree, vitex agnus-castus, pregnancy, lactation, breastfeeding, systematic review.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".