Bibliographic record
Abstract
BACKGROUND: Menière's disease is characterised by attacks of hearing loss, tinnitus and disabling vertigo. Betahistine is used by many people to reduce the frequency and severity of these attacks but there is conflicting evidence relating to its effects. OBJECTIVES: The objective of this review was to assess the effects of betahistine in people with Menière's disease. SEARCH STRATEGY: We searched the Cochrane Controlled Trials Register (The Cochrane Library issue 4,1999), MEDLINE (January 1966 to December 1999), EMBASE (January 1985 to December 1999) and Index Medicus (1962 to 1966). We checked reference lists of articles and contacted pharmaceutical companies for further studies. SELECTION CRITERIA: Randomised controlled studies of betahistine versus placebo in Menière's disease. DATA COLLECTION AND ANALYSIS: Two reviewers independently assessed trial quality and extracted data. Study authors were contacted for further information. MAIN RESULTS: Six trials involving 162 patients were included. No trial met the highest quality standard set by the review because of inadequate diagnostic criteria or methods, and none assessed the effect of betahistine on vertigo adequately. Most trials suggested a reduction of vertigo with betahistine and some suggested a reduction in tinnitus but all these effects may have been caused by bias in the methods. One trial with good methods showed no effect of betahistine on tinnitus compared with placebo in 35 patients. None of the trials showed any effect of betahistine on hearing loss. No adverse effects were found with betahistine. REVIEWER'S CONCLUSIONS: There is insufficient evidence to say whether betahistine has any effect on Menière's disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".