Cochlear nerve aplasia detected through kindergarten hearing screening.
Bibliographic record
Abstract
OBJECTIVES: To describe the importance of imaging with the use of magnetic resonance (MR) or computed tomography (CT) during the diagnostic workup of a patient with sensorineural hearing loss to determine the status of the cochlear nerve. DESIGN: Retrospective review. SETTING: Tertiary care academic institution. METHODS: A pediatric database was used to find patients with diagnoses of absent cochlear nerve. A retrospective chart review was performed from July 1999 to July 2004 to evaluate the route to diagnosis and any concomitant factors. Patients who had presented at kindergarten screening were included. Review was made of the audiologic investigations undertaken: routine audiometry, auditory brainstem response (ABR), and distortion product otoacoustic emission (OAE). Radiologic investigations were also reviewed consisting of CT and/or MR scans. RESULTS: The database yielded 12 cases of cochlear agenesis. Four patients were excluded because they had absence of the entire inner ear structures ipsilateral to the aplastic cochlear nerve (two cases) and because they had multiple congenital anomalies (two cases). There were equal numbers of males and females. There was a slight left-sided preponderance (5:3), and ages ranged from 5 through 7 years. All children had failed the initial screening audiogram. Follow-up audiologic evaluation revealed either profound loss or dead ear or a failed ABR in the presence of normal OAE testing. All patients had internal auditory canals less than 1.4 mm or MR-compatible findings. CONCLUSIONS: Agenesis of the cochlear nerve may be more common than previously thought, especially in an otherwise healthy, nonsyndromic, school-aged child. Although audiometric evaluation alone usually strongly suggests the diagnosis, definitive evaluation with MR remains the gold standard.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".