Bilateral cochlear implants should be the standard for children with bilateral sensorineural deafness
Bibliographic record
Abstract
PURPOSE OF REVIEW: Bilateral cochlear implants are provided to children in an attempt to establish binaural processing and allow hearing with greater ease. Arguments against implantation, which prevailed for many years, are countered by some of the findings reported over the past 1-2 years. RECENT FINDINGS: Behavioral and electrophysiological outcomes in children receiving cochlear implants suggest that two issues are most important when considering bilateral cochlear implants for any child: the duration of deafness prior to the first implantation affecting development of oral speech and language skills and the inter-stage interval (between implantation of the first and second ears) likely affecting development of binaural processing. SUMMARY: Based on the data reported to date, both the interval between onset of deafness and cochlear implantation and the interval between implantation of the first and second ears should be narrow in children. We recommend that simultaneous bilateral implantation be provided when possible and, if not, the inter-stage interval should be limited. We further recommend continued exploration of outcomes in children with longer inter-stage intervals with a view to defining a point at which bilateral cochlear implantation provides so little benefit that it is not cost-effective.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".