Benefits of Short Interimplant Delays in Children Receiving Bilateral Cochlear Implants
Bibliographic record
Abstract
OBJECTIVES: To examine speech perception skills in quiet and noise in children using bilateral cochlear implants and to assess the influence of duration of bilateral deafness and interimplant delay. STUDY DESIGN: Prospective repeated measures. SETTING: Tertiary academic referral center. METHODS: Speech perception was assessed in 58 children with early-onset deafness; 51 received their first implant after less than 3 years of bilateral deafness and their second implant simultaneously or after a long (>2 yr) or short (6-12 mo) interimplant delay. Another seven children had longer periods of bilateral deafness (>3 yr) before the first implant and received their second after a long (>2 yr) interimplant delay. Mean (standard deviation) of bilateral implant use was 12.5 (7.9) months ranging from 6 to 36 months. Repeated measures in quiet were completed in three quiet and two noise (no spatial separation) conditions. In quiet, children listened with their right implant alone, left implant alone, and with both implants. In noise, children wore one implant in the experienced (or right for simultaneous group) ear and both implants. RESULTS: Speech perception scores were poorer in noise than in quiet, but significant improvements were found when bilateral rather than unilateral implants were worn. Improvements were greatest for children who were implanted with a short duration of bilateral deafness and a limited interimplant interval. CONCLUSION: Benefits of bilateral implantation in the short term are clearest in children with limited delays between implantation.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".