Abnormal Timing Delays in Auditory Brainstem Responses Evoked by Bilateral Cochlear Implant Use in Children
Bibliographic record
Abstract
HYPOTHESIS: A period of unilateral implant use before bilateral implantation affects timing of brainstem processes measured by the electrically evoked auditory brainstem response (EABR). BACKGROUND: EABR latencies decrease with unilateral implant use potentially disrupting binaural timing cues important in auditory brainstem processing of bilateral input. METHODS: EABRs were evoked by electrical pulses from the left, right, and both implants simultaneously in 3 groups of children. All were initially implanted at ages younger than 3 years and had the following: 1) a long delay (>2 yr [n = 16]), 2) a short delay (<1 yr [n = 15]), or 3) no delay (n = 15) between left and right ear implantation. Responses were recorded on the first day of bilateral implant use and 3 and 9 months thereafter. RESULTS: Relative to responses evoked in the experienced ear, the naive ear showed prolonged latency in both the EABR peaks and the binaural difference response. After 3 and 9 months of bilateral implant use, the relative prolongation decreased in the long and short delay groups, but significant differences persisted in the former. No clear differences in latencies evoked by the left versus right implant were found at any time point in children receiving bilateral implants simultaneously. CONCLUSION: Results suggest potential disruptions to binaural brainstem processing based on timing cues in children receiving a second cochlear implant after more than 2 years of unilateral implant use that persist through at least the first 9 months of bilateral implant use.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".