Spoken Language Benefits of Extending Cochlear Implant Candidacy Below 12 Months of Age
Bibliographic record
Abstract
OBJECTIVE: To test the hypothesis that cochlear implantation surgery before 12 months of age yields better spoken language results than surgery between 12 and 18 months of age. STUDY DESIGN: Language testing administered to children at 4.5 years of age (± 2 mo). SETTING: Schools, speech-language therapy offices, and cochlear implant (CI) centers in the United States and Canada. PARTICIPANTS: Sixty-nine children who received a cochlear implant between ages 6 and 18 months of age. All children were learning to communicate via listening and spoken language in English-speaking families. MAIN OUTCOME MEASURE: Standard scores on receptive vocabulary, expressive, and receptive language (includes grammar). RESULTS: Children with CI surgery at 6 to 11 months (n = 27) achieved higher scores on all measures as compared with those with surgery at 12 to 18 months (n = 42). Regression analysis revealed a linear relationship between age of implantation and language outcomes throughout the 6- to 18-month surgery-age range. CONCLUSION: For children in intervention programs emphasizing listening and spoken language, cochlear implantation before 12 months of age seems to provide a significant advantage for spoken language achievement observed at 4.5 years of age.
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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 | 0.003 |
| 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) | 0.002 | 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".