Over-the-counter anti-oxidant therapies for use in multiple sclerosis: A systematic review
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: Anti-oxidant compounds that are found in over-the-counter (OTC) supplements and foods are gaining interest as treatments for multiple sclerosis (MS). They are widely used by patients, sometimes without a clear evidence base. OBJECTIVE: We conducted a systematic review of animal and clinical research to determine the evidence for the benefits of OTC anti-oxidants in MS. METHODS: Using predefined criteria, we searched key databases. Two authors scrutinized all studies against inclusion/exclusion criteria, assessed study risk-of-bias and extracted results. RESULTS: Of the 3507 titles, 145 met criteria and included compounds, α(alpha)-lipoic acid (ALA), anti-oxidant vitamins, Ginkgo biloba, quercetin, resveratrol and epigallocatechin-3-gallate (ECGC). The strongest evidence to support OTC anti-oxidants was for compounds EGCG and ALA in animal models; both consistently showed anti-inflammatory/anti-oxidant effects and reduced neurological impairment. Only vitamin E, Ginkgo biloba and ALA were examined for efficacy in pilot clinical trials with either conflicting evidence or evidence of no benefit. CONCLUSION: OTC anti-oxidants EGCG and ALA show the most consistent benefit, however only in preclinical studies. There is no evidence that they alter MS relapses or progression. Future work should focus on testing more of these therapies for clinical efficacy before recommending them to MS patients.
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.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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