Predictive Value of <i>GJB2</i> Mutation Status for Hearing Outcomes of Pediatric Cochlear Implantation
Bibliographic record
Abstract
Objective To systematically review and quantify current evidence regarding the association of GJB2 mutation status with outcomes of pediatric cochlear implantation. Data Sources PubMed, Embase, and the Cochrane Library were searched for "GJB2,""pediatric hearing loss," and "cochlear implantation" and their synonyms, with no language restrictions, until December 2, 2015. Review Methods Studies were included that investigated the status of GJB2 mutation and its predictive value for outcomes of pediatric cochlear implantation. Speech recognition scores, Infant-Toddler Meaningful Auditory Integration Scale, Speech Intelligibility Rating, and Categorized Auditory Performance were pooled using weighted mean differences, and a 95% confidence interval. Results Eighteen studies met the inclusion criteria. The differences between GJB2-related deafness and non- GJB2-related deafness due to unidentified causes and other types of genetic deafness without additional disabilities were not statistically significant ( P = .15 and P = .30, respectively); however, the difference between GJB2-related deafness and acquired hearing loss due to environmental etiologies was statistically significant and favored GJB2-related deafness ( P = .03). Conclusion GJB2-related deafness leads to significantly better cochlear implantation outcomes when compared with acquired deafness caused by environmental etiologies. However, GJB2 mutation is not associated with a significantly better prognosis when compared with those whose deafness results from either nonsyndromic hearing loss of unknown origin or other types of genetic mutations in the absence of other neurologic deficits.
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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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".