Cochlear Nerve Aplasia with Detectable Olivocochlear Efferent Function: A Distinct Presentation of Auditory Neuropathy Spectrum Disorder
Bibliographic record
Abstract
BACKGROUND: Cochlear nerve aplasia (CNA) may present with features of auditory neuropathy spectrum disorder (ANSD), having detectable otoacoustic emissions (OAE) but profound hearing loss. We propose that some children with CNA have a distinct form of afferent ANSD in which efferent cochlear nerve function can be detected using contralateral suppression of OAE. METHODS: Children were prospectively enrolled with MRI and auditory brainstem response evidence of unilateral CNA, a normal contralateral ear, and detectable OAE bilaterally. Distortion product OAE (DPOAE) levels were recorded in real time with default primary tone settings: frequency (f)2 = 4.5 kHz and f2/f1 = 1.22 kHz, with level (L)1 = 65 dB SPL and L2 = 55 dB SPL. Recordings were made over 2 min with simultaneous application of an intermittent contralateral broadband noise (CBBN) stimulus at 60 dB SPL. RESULTS: Three girls, aged 4.5, 7, and 8 years, participated. Suppression of DPOAE of 0.15-1.3 dB was detected in all 3 ears with CNA in response to CBBN stimulation. No response was detected in the normal ears. CONCLUSIONS: Children with unilateral ANSD can have normal efferent cochlear nerve function despite MRI evidence of ipsilateral CNA. The importance of these findings for newborn hearing screening and cochlear implantation is discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".