Cochlear Implantation in Far Advanced Otosclerosis: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate speech outcomes and facial nerve stimulation (FNS) rates in patients with far advanced otosclerosis (FAO) after cochlear implantation. METHODS: A systematic review was performed using standardized methodology of Medline, EMBASE, PubMed, Cochrane, and Web of Science databases. Studies were included if adults with FAO underwent cochlear implantation. Exclusion criteria included concurrent otologic history (e.g., Meniere's disease, superior canal dehiscence), non-English-speaking implant users, case reports, abstracts, and letters/commentaries. Bias was assessed using the Newcastle-Ottawa Scale for cohort studies and the National Institute of Health Scale for case series. The primary outcome measure was speech discrimination and the secondary outcomes were rates of partial insertion and FNS. RESULTS: Twenty-seven studies evaluated cochlear implantation in FAO. Due to the heterogeneity of testing methods, statistical pooling of speech discrimination was not feasible, but qualitative synthesis indicated a positive effect of implantation. Pooled rates of FNS were 18% (95% confidence interval, CI 12%-27%) and the rate of partial insertion was 10% (95% CI 7%-15%). CONCLUSION: Cochlear implantation in FAO demonstrates significant gains in speech discrimination scores with higher rates of FNS and partial insertion. Laryngoscope, 133:1288-1296, 2023.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.018 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".