An Umbrella Review of Cochlear Implant Outcomes in Children With Auditory Neuropathy
Bibliographic record
Abstract
PURPOSE: The objective of this overview of systematic reviews (SRs; umbrella review) was to systematically summarize and critically appraise current evidence of cochlear implant (CI) outcomes in children with auditory neuropathy spectrum disorder (ANSD). METHOD: This study was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement. The methodological quality and the risk of bias in the included SRs were assessed using A MeaSurement Tool to Assess systematic Reviews 2 checklist and the Risk of Bias in Systematic Reviews tool, respectively. RESULTS: According to eight included SRs, children with ANSD achieve CI outcomes (speech perception performance) similar to their peers with sensorineural hearing loss. In children with postsynaptic ANSD (cochlear nerve deficiency), cochlear nerve hypoplasia is associated with better speech recognition outcomes compared with cochlear nerve aplasia, especially in the absence of additional disabilities. Except for one study, the overall quality of the included SRs was critically low, and except for three studies, evidence of a high risk of bias was identified in other included SRs. CONCLUSIONS: Current evidence supports CI benefits for children with ANSD. To improve the quality of evidence, well-designed, prospective studies with appropriate sample sizes, using valid outcome measures, clarifying matching criteria, and taking into account the role of confounding factors are essential.
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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 | 0.039 | 0.143 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.025 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".