The clinical utility of search coil horizontal vestibulo-ocular reflex testing
Bibliographic record
Abstract
CONCLUSION: Testing of the horizontal vestibulo-ocular reflex (VOR) with head rotations (including head impulses) using the magnetic scleral search coil technique (SCT HHI) provides valuable additional diagnostic information in patients with persistent dizziness, oscillopsia or imbalance. It identifies high and low frequency/acceleration vestibular abnormalities that are frequently missed using other methods. OBJECTIVES: To evaluate the diagnostic utility of SCT measurement of the horizontal VOR in the multidisciplinary neurotology clinic of a tertiary referral centre. PATIENTS AND METHODS: The records of 127 consecutive patients referred for persistent dizziness, oscillopsia, imbalance, or with clinical findings suggestive of high frequency/acceleration vestibular dysfunction were reviewed. All had been tested with clinical head impulses, bithermal calorics and vestibular-evoked myogenic potentials. VOR gain (peak eye velocity/peak head velocity) had been measured both in response to sinusoidal oscillations in a rotating chair (0.1-11 Hz) and to manually delivered horizontal head rotations (peak head velocities 50-500 degrees/s) using SCT. RESULTS: Agreement between the different test modalities of horizontal semicircular canal function was moderate. Relative to SCT HHI, clinical HHI showed the highest sensitivity and the lowest specificity (both 70%). SCT HHI appeared to have the greatest diagnostic yield, when compared with calorics and SCT ROT (23% of all abnormalities shown were detected only by SCT HHI) and also allowed detection of significant asymmetries in patients with bilateral vestibular dysfunction.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".