Cognitive Assessment in Elderly Cochlear Implant Recipients: Long‐Term Analysis
Bibliographic record
Abstract
OBJECTIVES: To examine long-term speech and cognition outcomes in older adult cochlear implant (CI) recipients. First, by evaluating if CI performance was maintained over an extended follow-up period regardless of preoperative cognitive status. Secondly, by evaluating if there was a difference in the rate of cognitive decline between preoperative mild and normal cognition following CI over an extended period of time. STUDY DESIGN AND SETTING: Retrospective cohort study. METHODS: CI recipients ≥65 years of age implanted between 2009 and 2014 with 4+ years follow up. Pre- and postoperative audiometric and speech outcome assessments were collected. Cognitive status was measured using the mini mental status examination (MMSE) at numerous time points. RESULTS: Fifty-three patients met inclusion. Patients were divided into two groups based on preoperative MMSE with scores considered normal (28-30) and those with mildly impaired cognition (MIC, scores 25-27). Audiometric and speech performance improved significantly at one-year post implantation and this was maintained without significant change at 4+ years, regardless of cognitive status. Mixed modeling analysis controlling for age demonstrated no significant difference in the rate of cognitive decline at 4+ years post implantation between the normal cognition cohort (1.74; 95%CI 0.89-2.6) and MIC (2.9; 95%1.91-3.88). CONCLUSION: Speech performance was significantly improved and sustained after CI in both normal cognition and MIC patients. The rate of cognitive decline in older adult CI patients appears to be similar regardless of preoperative cognitive status. Although results demonstrate rates of cognitive decline following CI did not differ between cognition groups over 4+ years, future studies will need to further investigate this over extended time periods with a more comprehensive cognitive testing battery. LEVEL OF EVIDENCE: 4 Laryngoscope, 133:2379-2387, 2023.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".