Bilateral Cochlear Implantation: An Evidence‐Based Medicine Evaluation
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: The aim of this study was to evaluate the extent and quality of evidence reported on the outcomes of bilateral cochlear implantation and thereby to inform opinion about future patient management. STUDY DESIGN: Retrospective literature review. METHODS: A detailed search of the medical literature was performed using the Medline, Embase, and CINAHL databases starting from the date of their conception. The quality of evidence in each article was assessed according to the categories of evidence as defined by the Oxford Centre for Evidence-based Medicine, Levels of Evidence (May 2001). RESULTS: A total of 37 studies were included; 28 (76%) investigated adult participants only, 7 (19%) investigated child participants, and 2 (5%) contained both groups. Of the studies presented, 9 (24%) studies contained level 2b evidence, 2 (6%) level 3b, 16 (43%) level 4, and 10 (27%) level 5 evidence. No studies were identified as representing evidence level 1. Adult bilateral recipients demonstrated an increase in sentence recognition of 21% correct over their first implanted ear (P < .001) and mean bilateral localization errors of 24 degrees against a monaural error of 67 degrees (P < .005). CONCLUSIONS: The available evidence indicates that bilateral cochlear implantation confers material benefits not achievable with unilateral implantation, specifically in terms of sound localization and understanding of speech in noise. Well-designed prospective studies of sufficient size are now needed to precisely quantify these benefits, to validate outcome measures, especially in children, and to define the criteria for intervention.
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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 | 0.028 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".