Pharmacological and Therapeutic Potential of Chamomile in Lowering Blood Triglyceride Levels: A Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Hypertriglyceridemia is a major risk factor for cardiovascular and metabolic disorders. Matricaria chamomilla (Chamomile), a widely used medicinal herb, possesses antioxidant, anti-inflammatory, and lipid-modulating properties. Its specific effects on serum triglyceride levels, however, remain to be systematically evaluated. Objective: This systematic review aims to comprehensively assess the pharmacological and therapeutic effects of Matricaria chamomilla on serum triglyceride levels across human, animal, and in vitro studies. Methods: A structured literature search was conducted in PubMed, Scopus, and Web of Science up to 2025. Studies evaluating Chamomile’s impact on triglyceride levels were included. Data extraction and quality assessment were independently performed by two reviewers using Cochrane Risk of Bias and Newcastle–Ottawa Scale tools. Findings were synthesized qualitatively, and meta-analysis was performed where appropriate. Results: Ten studies met inclusion criteria, including 4 human clinical trials, 4 animal studies, and 2 in vitro investigations. Chamomile consistently reduced serum triglyceride levels in animal models and showed moderate lipid-lowering effects in humans. Mechanistic evidence indicates its effects are mediated through antioxidant activity, modulation of lipid-metabolizing enzymes, and anti-inflammatory pathways. Reported adverse effects were minimal and mild. Conclusion: Current evidence supports Matricaria chamomilla as a potential adjunct therapy for hypertriglyceridemia. High-quality randomized controlled trials are needed to establish optimal dosing, treatment duration, and long-term safety.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it