Results With Cochlear Implantation in Adults With Speech Recognition Scores Exceeding Current Criteria
Bibliographic record
Abstract
OBJECTIVES: The primary purpose of this study was to evaluate a group of postlingually deafened adults, whose aided speech recognition exceeded commonly accepted candidacy criteria for implantation. The study aimed to define performance and qualitative outcomes of cochlear implants in these individuals compared with their optimally fitted hearing aid(s). STUDY DESIGN: Retrospective case series. SETTING: Tertiary referral center. PATIENTS: All postlingually deafened subjects (N = 27), who were unsuccessful hearing aid users implanted between 2000 and 2010 with a preimplantation Hearing in Noise Test (HINT) score of 60% or more were included. INTERVENTION: We compared patients' preoperative performance (HINT score) with hearing aids to postoperative performance with the cochlear implant after 12 months of device use. In addition, the Hearing Handicap Inventory questionnaire was used to quantify the hearing-related handicap change perceived after the implantation. RESULTS: The study group demonstrated significant postoperative improvement on all outcome measures; most notably, the mean HINT score improved from 68.4% (standard deviation, 8.3) to 91.9% (standard deviation, 9.7). Additionally, there was a significant improvement in hearing-related handicap perceived by all patients. CONCLUSION: The envelope of implantation candidacy criteria continues to expand as shown by this study's cohort. Patient satisfaction and speech recognition results are very encouraging in support of treating those who currently perform at a level above the conventional candidacy threshold but struggle with optimally fitted hearing aids.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".