Visual Vestibular Mismatch in Work-Related Vestibular Injury
Bibliographic record
Abstract
OBJECTIVE: To define and investigate the symptom set known as visual-vestibular mismatch and analyze its nature and occurrence in two groups of patients referred for dizziness. STUDY DESIGN: Prospective study of two groups of sequentially referred patients complaining of dizziness, imbalance, or both. SETTING: A tertiary and quaternary care ambulatory referral center. PATIENTS: Two groups of patients were studied. One was a group of patients who had suffered work-related head trauma and had subsequent complaints of dizziness and/or imbalance. The other was a group of patients referred for dizziness and/or imbalance who had no history of head trauma, work-related injury, or litigation procedures. INTERVENTIONS: Standard vestibular assessment including computerized dynamic posturography was carried out on all patients. A series of questions was designed to quantify patients' complaints of symptoms of visual-vestibular mismatch, and patients were scored according to their yes/no answers to the five questions. MAIN OUTCOME MEASURES: Results of traditional vestibular tests were correlated with the answers to the questions. Computerized dynamic posturography and electronystagmography results were compared between both symptomatic and nonsymptomatic patients and also between patients who had traumatic and nontraumatic causes of their symptoms. RESULTS: We found no correlation between test results and the presence of visual-vestibular mismatch symptomatology. There does seem to be a connection between the presence of motion sickness symptomatology and the development of visual-vestibular mismatch symptoms. CONCLUSION: Although visual-vestibular mismatch is of vestibular origin, it is discernible only after obtaining a careful history. It is a genuine symptom set of vestibular origin, and there is a certain group of patients who are more sensitive to this symptom set and who are often debilitated by its presence.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".