Toxicology and teratology of the active ingredients of professional therapy MuscleCare products during pregnancy and lactation: a systematic review
Bibliographic record
Abstract
BACKGROUND: The rates of muscle aches, sprains, and inflammation are significantly increased during pregnancy. However, women are afraid to use systemic analgesics due to perceptions of fetal risks. Thus, topical products are important alternatives to consider for those women. Of interest, Professional Therapy MuscleCare (PTMC) has shown to be effective in alleviating the myofascial pain as reported in a randomized, placebo-controlled double-blinded comparative clinical study of five topical analgesics. However, to date, there is no complete review or long-term safety studies on the safety of these products during pregnancy and lactation. Thus, the aim of this article was to review toxicological, developmental, and reproductive effects associated with the use of PTMC products. METHODS: We performed a systematic review on safety of PTMC from all toxicological articles investigating the effects of PTMC's ingredients. This search was conducted through medical and toxicological databases including, Web of Science, EMBASE, Medline, and Micromedix. Both reported and theoretical adverse effects were extensively reviewed. RESULTS: Of the 1500 publications reviewed, 100 papers were retrieved and included in the review. Although some ingredients in PTMC products might cause adverse reproductive effects at high systemic doses, these doses are hundreds to thousands fold greater than those systemically available from topical use at the recommended maximum dose (i.e. 10 g/day). CONCLUSIONS: This study provides evidence that, when used as indicated, PTMC is apparently safe for pregnant women and their unborn babies as well as for breastfed infants.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".