Isolated Second Implant Adaptation Period in Sequential Cochlear Implantation in Adults
Bibliographic record
Abstract
OBJECTIVE: To determine if depriving the use of the first cochlear implant (CI1) impacts adaptation to a sequential implant (CI2). STUDY DESIGN: Prospective cohort. SETTING: Academic center. PATIENTS: Sixteen unilateral cochlear implant recipients undergoing contralateral implantation (sequential bilateral) were matched according to age, etiology, duration of deafness, device age, and delay between implants. INTERVENTION: During a 4-week adaptation period after CI2 activation, patients underwent deprivation of CI1 or were permitted continued use of it. MAIN OUTCOME MEASURES: Speech perception scores and subjective quality of life outcomes before CI2 and at 1, 3, 6, and 12-months following activation. RESULTS: Maximal CI2 speech perception scores in quiet were achieved by 1-month postactivation for the "deprivation" group (71.3% for hearing in noise test [HINT], p = 0.767 for change beyond 1-mo) compared with 6-months for the "continued use" group (67.9% for HINT, p = 0.064 for change beyond 6-mo). The "deprivation" group experienced a temporary drop in CI1 scores (67.9% for HINT in quiet at 1-mo versus 78.4% pre-CI2, p = 0.009) recovering to 77.3% by 3-months; unchanged from baseline levels (p = 1.0). A binaural advantage over the better hearing ear was present for HINT sentences with noise (72.4% versus 58.8% for "deprivation", p = 0.001; 71.5% versus 52.7% for "continued use," p = 0.01). Missing data precluded a meaningful analysis of subjective quality of life outcome scales. CONCLUSION: Bilateral cochlear implantation improves speech perception compared with one implant. A period of deprivation from CI1 shortens time to maximum speech perception by CI2 without long-term consequences on the performance of CI1.
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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) | 0.000 | 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".