Management of single‐sided deafness with the bone‐anchored hearing aid
Bibliographic record
Abstract
OBJECTIVES: The benefits of the bone-anchored hearing aid (BAHA) for rehabilitation of conductive and mixed hearing loss are well established. Recently, the BAHA was used to rehabilitate patients with single-sided deafness (SSD). In this study, the benefits of the BAHA in SSD are presented. STUDY DESIGN: Case series with planned data collection. SETTING: Tertiary referral center. SUBJECTS AND METHODS: Twenty-one consecutive adult patients with SSD underwent single-stage BAHA implantation on the side of deafness. Testing in sound field was performed using the hearing-in-noise test (HINT) in both unaided and aided conditions. Speech and noise signals were delivered through two speakers oriented in two test paradigms. The outcomes were expressed as signal-to-noise (S/N) ratios. Subjective benefit analyses were determined through two questionnaires: the Abbreviated Profile of Hearing Aid Benefit (APHAB) and the Glasgow Hearing Aid Benefit Profile (GHABP). RESULTS: All subjects demonstrated significant improvement in speech reception thresholds with the HINT using the BAHA, especially with the 90/270 speaker paradigm, in which the mean improvement over the unaided condition was 5.5 dB SPL (range, 2.0-11.0 dB; P=0.00001). Qualitative subjective outcome measures demonstrated additional benefits. CONCLUSION: In SSD patients, the BAHA provides significant subjective benefits and improves speech understanding in noise.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".