Cochlear Implantation in Neurofibromatosis Type 2: Experience From the UK Neurofibromatosis Type 2 Service
Bibliographic record
Abstract
Objective: To review the outcomes of cochlear implants (CI) in patients with neurofibromatosis type 2 (NF2) in a large cohort, and identify factors associated with poor hearing benefit. Study Design: Fifteen-year retrospective national observational case series. Setting: United Kingdom regional NF2 multidisciplinary teams. Patients: Consecutive patients with NF2 receiving a CI. Interventions: CI for hearing rehabilitation. Main outcome measures: 1) Audiometric performance at 9 to 12 months after implantation using City University of New York (CUNY) sentence recognition score, and Bamford- Kowal-Bench (BKB) word recognition score in quiet (BKBq), and in noise (BKBn). 2) CI use at most recent review. Results: Sixty four consecutive patients, median age 43 years, were included. Nine to 12 months mean audiometric scores were: CUNY 60.9%, BKBq 45.8%, BKBn 41.6%. There was no difference in audiometric outcomes between VS treatment modalities. At most recent review (median 3.6 years from implantation), 84.9% with device in situ/available data were full or part-time users. Between 9 and 12 months and most recent review there was an interval reduction in mean audiometric scores: CUNY −12.9%, BKBq −3.3%, BKBn −4.9%. Larger tumor size and shorter duration of profound hearing loss were the only variables associated with poorer audiometric scores. Tumor growth at the time of surgery was the only variable associated with CI non-use. Individual patient response was highly variable. Conclusions: CI can provide significant and sustained auditory benefits to patients with NF2 independent of tumor treatment modality, with the majority of those implanted becoming at least part-time users. Larger datasets are required to reliably assess the role of independent variables.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".