The combination of vestibular impairment and congenital sensorineural hearing loss predisposes patients to ocular anomalies, including Usher syndrome
Bibliographic record
Abstract
The co-occurrence of hearing impairment and visual dysfunction is devastating. Most deaf-blind etiologies are genetically determined, the commonest being Usher syndrome (USH). While studies of the congenitally deaf population reveal a variable degree of visual problems, there are no effective ophthalmic screening guidelines. We hypothesized that children with congenital sensorineural hearing loss (SNHL) and vestibular impairment were at an increased risk of having USH. A retrospective chart review of 33 cochlear implants recipients for severe to profound SNHL and measured vestibular dysfunction was performed to determine the ocular phenotype. All the cases had undergone ocular examination and electroretinogram (ERG). Patients with an abnormal ERG underwent genetic testing for USH. We found an underlying ocular abnormality in 81.81% (27/33) of cases; of which 75% had refractive errors, and 50% of those patients showed visual improvement with refractive correction. A total of 14 cases (42.42%; 14/33) had generalized rod-cone dysfunction on ERG suggestive of Usher syndrome type 1, confirmed by mutational analysis. This work shows that adding vestibular impairment as a criterion for requesting an eye exam and adding the ERG to detect USH increases the chances of detecting ocular anomalies, when compared with previous literature focusing only on congenital SNHL.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".