A Comparison of Postcochlear Implantation Speech Scores in an Adult Population
Bibliographic record
Abstract
OBJECTIVES: The vast majority of cochlear implant recipients realize significant improvement in speech perception. However, there continue to be a small group that does not realize such a benefit. In an effort to identify possible predictors for this, we have compared pre- and postimplant audiologic data using Hearing In Noise Test (HINT), City University of New York (CUNY), or Central Institute for the Deaf (CID) scores for 445 consecutive English-speaking adult patients followed for a minimum of 1 year postimplantation in two distinct groups, poor versus excellent performers. STUDY DESIGN: Retrospective. METHODS: Poor performers were those who realized a worsening, no improvement, or an improvement of less than 10%. This group numbered 58 (13%). High performers consisted of a cadre of 194 (44%) patients who scored between 91 and 100% postimplantation. Demographic data relating to onset of deafness, education exposure, etiology, etc., were evaluated. RESULTS: Of the poor performers, 33 (57%) were pre-/perilingually deafened. Of these, 79% had not received any auditory/oral training in childhood. On the other hand, a total of 109 implant recipients were individuals who were pre-/perilingually deafened. Of these, 24 were in the excellent performer category. All were identified early and were recipients of a strong auditory/oral education. Of the high performers, 170 (88%) were deafened late. Other findings such as preoperative electronystagmography with caloric testing, hearing aid use, device type, and high-resolution computed tomography scan of the temporal bone will be discussed for both groups. CONCLUSIONS: A high preimplant speech score, auditory verbal therapy, and postlingual deafness statistically correlate with higher postimplant speech scores 1 year after cochlear implantation. Device type, caloric response and hearing aid use preimplantation, age at surgery, and sex do not statistically correlate with either poor or excellent speech discrimination scores postcochlear implantation.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".