Positive horizontal-canal head impulse test is not a benign sign for acute vestibular syndrome with hearing loss
Bibliographic record
Abstract
Background Diagnosis of acute vestibular syndrome (AVS) with hearing loss is challenging because the leading vascular cause—AICA territory stroke—can appear benign on head impulse testing. We evaluated the diagnostic utility of various bedside oculomotor tests to discriminate imaging-positive and imaging-negative cases of AVS plus hearing loss. Method We reviewed 13 consecutive inpatients with AVS and acute unilateral hearing loss. We compared neurologic findings, bedside and video head impulse testing (bHIT, vHIT), and other vestibular signs (including nystagmus, skew deviation, and positional testing) between MRI+ and MRI– cases. Results Five of thirteen patients had a lateral pontine lesion (i.e., MRI+); eight did not (i.e., MRI–). Horizontal-canal head impulse test showed ipsilateral vestibular loss in all five MRI+ patients but only in three MRI– patients. The ipsilesional VOR gains of horizontal-canal vHIT were significantly lower in the MRI+ than the MRI– group (0.56 ± 0.11 vs. 0.87 ± 0.24, p = 0.03). All 5 MRI+ patients had horizontal spontaneous nystagmus beating away from the lesion (5/5). One patient (1/5) had direction-changing nystagmus with gaze. Two had skew deviation (2/5). Among the 8 MRI– patients, one (1/8) presented as unilateral vestibulopathy, four (4/8) had positional nystagmus and three (3/8) had isolated posterior canal hypofunction. Conclusion The horizontal-canal head impulse test poorly discriminates central and peripheral lesions when hearing loss accompanies AVS. Paradoxically, a lateral pontine lesion usually mimics unilateral peripheral vestibulopathy. By contrast, patients with peripheral lesions usually present with positional nystagmus or isolated posterior canal impairment, risking misdiagnosis as central vestibulopathy.
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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".