Prophylaxis of migraine headaches with riboflavin: A systematic review
Bibliographic record
Abstract
WHAT IS KNOWN AND OBJECTIVE: Migraine headache is a relatively common, debilitating condition that costs our healthcare system over 78 billion dollars per year. Riboflavin has been advocated as a safe, effective prophylactic therapy for the prevention of migraines. The purpose of this study was to provide a systematic review of the current role of riboflavin in the prophylaxis of migraine headache. METHODS: A MEDLINE literature search inclusive of the dates 1966-2016 was performed using the search terms: riboflavin and migraine disorders. Excerpta Medica was searched from 1980 to 2016 using the search terms: riboflavin and migraine. Additionally, Web of Science was searched using the terms riboflavin and migraine inclusive of 1945-2016. Bibliographies of all relevant papers were reviewed for additional citations. We utilized the PRISMA guidelines to select English language, human, clinical trials of riboflavin as a single entity or in combination, review articles, and supporting pharmacokinetic and pharmacogenomic data assessing the efficacy and mechanism of riboflavin therapy in the prophylactic treatment of migraine headache. RESULTS AND DISCUSSION: A total of 11 clinical trials reveal a mixed effect of riboflavin in the prophylaxis of migraine headache. Five clinical trials show a consistent positive therapeutic effect in adults; four clinical trials show a mixed effect in paediatric and adolescent patients, and two clinical trials of combination therapy have not shown benefit. Adverse reactions with riboflavin have generally been mild. WHAT IS NEW AND CONCLUSION: Riboflavin is well tolerated, inexpensive and has demonstrated efficacy in the reduction of adult patient's migraine headache frequency. Additional data are needed, however, to resolve questions involving pharmacokinetic issues and pharmacogenomic implications of therapy.
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.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".