Bibliographic record
Abstract
Purpose The focus of this Scholarly Practice Advancement Research project was to examine the evidence regarding the use of intravenous mega-dose vitamins for the specific conditions of interest for this project; fibromyalgia, chronic fatigue, cancer and asthma. These conditions were chosen because they are most frequently advertised by CAM providers as conditions wherein mega-doses of intravenous vitamins could be beneficial. Proponents have also made claims of research supporting intravenous mega-dose vitamin therapy, the Myers’ Cocktail and mega-doses of vitamin C and magnesium. Aims The aims of this project was to (a) conduct a Rapid Evidence Assessment (REA) to identify whether there is quality scientific evidence to support the use of intravenous mega dose m therapy as an effective therapeutic intervention for individuals with fibromyalgia, chronic fatigue, cancer, and asthma; (b) to evaluate the quality of published research available on the use of IVMM therapy for individuals with fibromyalgia, cancer, asthma and chronic fatigue. Methods A Rapid Evidence Assessment was utilized to explore the quality of scientific evidence available in supporting the use of intravenous mega-dose multivitamin therapy. The databases CINAHL, PubMed Central, Medline, Google Scholar and ClinicalTrials.gov were utilized in gathering studies for this project. Eleven articles were selected for this paper which identified the use of the Myers’ Cocktail, mega-doses of intravenous vitamin C, or mega-doses of magnesium. Results Adverse events were minimal within all studies evaluated, however no patient experienced an objective tumor response, no complete or lasting effect on pain or fatigue and for asthma, conventional therapy was required along with intravenous therapy. Some patient’s symptoms also worsened before they became better, and the effect of the interventions were strongest in subjects with lower baseline levels of the vitamins or in conjunction with conventional treatments. Conclusion Intravenous mega-doses of multivitamins, vitamin C and magnesium are well tolerated with minimal side effects, however available research fails to provide enough evidence to support the continued use of this complementary therapy. The use of intravenous therapy in conjunction with conventional therapies may have some benefit, however further clinical trials are required.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".