Cochlear Implantation Outcomes in Older Adults, Ages 80–90+
Bibliographic record
Abstract
OBJECTIVE: To assess whether postoperative speech recognition after cochlear implantation (CI) differ between age groups of 80 to 89 and 90+. STUDY DESIGN: Retrospective cohort study. SETTING: Tertiary academic referral center. PATIENTS: Older adult (80+ years old) bilateral sensorineural hearing loss patients undergoing CI. INTERVENTIONS: Therapeutic, CI. MAIN OUTCOME MEASURES: Speech testing battery at 3, 6, and 12 months postoperatively. Self-reported balance and vertigo symptoms were also assessed. RESULTS: A total of 221 patients were included in this study, with 171 cases ages 80 to 89 and 50 cases ≥90 years old. A total of 60.3% had an abnormal preoperative cognitive screen based on either Montreal Cognitive Assessment or Mini Mental State Examination. No major demographic or clinical variables were noted across age groups. Mean 1 year postoperative speech scores were as follows for ages 80 to 89 versus 90+, respectively: CNC 50% (±21%) versus 47% (±18%), AzBio Quiet 54% (±26%) versus 50% (±25%), and AzBio +10SNR 28% (±21%) versus 21% (±17%). Age, abnormal cognitive screen, duration of hearing loss, and comorbidity measures such as BMI, Adult Comorbidity Evaluation-27, and American Society of Anesthesiology physical status class were not correlated with any speech measure. Overall rates of persistent self-reported balance symptoms at activation were 22.7%, decreasing to 7.5% at 1 year. Datalogging was >11 hours use on average for both age groups. CONCLUSIONS: CI speech recognition in the 80 to 89 and 90+ age range significantly improved from preoperative scores. No major speech recognition differences were identified between age groups. Age at implantation, abnormal cognitive screening, and comorbidity status did not influence speech perception, which suggests that candidacy in older adult CI patients should not be withheld strictly due to these parameters.
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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 | 0.001 | 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".