Examining the evidence: complementary adjunctive therapies for multiple sclerosis
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to provide a comprehensive overview of the most frequently encountered non-conventional approaches trialed for use in multiple sclerosis (MS). The efficacy and safety of non-conventional approaches ranging from bee venom therapy (BVT) to an array of vitamins and herbal products were discussed and evaluated. METHODS: Relevant English-language articles were identified through searches of MEDLINE (1990-2006), PubMed (1999-2006), Cochrane (1995-2006) and Toxnet (2000-2006). Classification of available literature was conducted according to the evidence based guidelines established by the American Academy of Neurology (AAN). However, due to the non-conventional nature of these treatment approaches, most available literature was derived from anecdotal reports and suboptimal clinical studies, lacking the rigor of evidence-based practice. RESULTS: There is presently only marginal supportive evidence for BVT in MS treatment. The inability to identify and quantify the active component of BVT combined with the associated risk of anaphylaxis has deterred its widespread use. The most promising evidence comes from prophylactic daily supplementation with vitamin D. Despite beneficial reports regarding non-herbal supplements such as alpha-lipoic acid (ALA), luteolin, evening primrose oil and vitamins such as B12, the lack of evidence does not support their prophylactic use. DISCUSSION: Based on available evidence, the prophylactic use of vitamin D is a viable option as an adjunct to conventional medicine. Although there is a lack of conclusive evidence to support the use of other non-conventional treatments, patients are still opting to trial and bare the risks of these products which are accessible without the intervention of a healthcare professional. Controlled, evidence-based trials are essential for healthcare professionals to competently intervene and recommend these products.
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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 | 0.012 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".