Safety and Early Outcomes of Cochlear Implantation of Nucleus Devices in Infants: A Multi-Centre Study
Bibliographic record
Abstract
This multi-center study examined the safety and effectiveness of cochlear implantation of children between 9 and 11 months of age. The intended impact was to support practice regarding candidacy assessment and prognostic counseling of pediatric cochlear implant candidates. Data in the clinical chart of children implanted at 9-11 months of age with Cochlear Ltd devices at five cochlear implant centers in the United States and Canada were included in analyses. The study included data from two cohorts implanted with one or two Nucleus devices during the periods of January 1, 2012-December 31, 2017 (Cohort 1, n = 83) or between January 1, 2018 and May 15, 2020 (Cohort 2, n = 50). Major adverse events (requiring another procedure/hospitalization) and minor adverse events (managed with medication alone or underwent an expected course of treatment that did not require surgery or hospitalization) out to 2 years post-implant were monitored and outcomes measured by audiometric thresholds and parent-reports on the IT-MAIS and LittlEARS questionnaires were collected. Results revealed 60 adverse events in 41 children and 227 ears implanted (26%) of which 14 major events occurred in 11 children; all were transitory and resolved. Improved hearing with cochlear implant use was shown in all outcome measures. Findings reveal that the procedure is safe for infants and that they show clear benefits of cochlear implantation including increased audibility and hearing development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".