Meniere’s Disease and Vestibular Migraine: Updates and Review of the Literature
Bibliographic record
Abstract
The diagnosis of Meniere's disease (MD) and vestibular migraine (VM) is primarily based on clinical criteria and their differentiation is often difficult. Currently, there are no known definitive diagnostic tests that can reliably distinguish the two conditions. Patients with MD and patients with VM are treated differently, therefore improving the diagnosis of these two pathologies should avoid errors in management. A systematic review was conducted according to PRISMA guidelines. Medline-Ovid and Embase databases were used to conduct a thorough search of English-language publications dating from 1948 to March 2016. The primary search objective was to identify all papers explicitly comparing MD and VM in order to clarify and validate the diagnosis of these two diseases. A total of 13 articles out of 831 were reviewed. Among other differences, MD showed later age of onset, more hearing loss, tinnitus, aural fullness, abnormal nystagmus, abnormal caloric testing results, abnormal vestibular evoked myogenic potential and endolymphatic hydrops. VM showed more headaches, photophobia, vomiting and aura. Even though differences were noted between the two diseases, only one study focused on assessing the differences between VM, MD and patients fulfilling both diagnostic criteria (MDVM). This study showed no difference between the three groups. Since the introduction of the new International Headache Society and Barany Society criteria for VM, no studies have focused on comparing these three groups. We strongly encourage authors to focus on comparing MD and VM from MDVM in future studies to help adequately distinguish the diagnosis of both diseases.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.022 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".