Improved Cochlear Implant Performance Estimation Using Tonotopic-Based Electrocochleography
Bibliographic record
Abstract
Importance: Cochlear implantation produces remarkable results in postlingual deafness, although auditory outcomes vary. Electrocochleography (ECochG) has emerged as a valuable tool for assessing the cochlear-neural substrate and evaluating patient prognosis. Objective: To assess whether ECochG-total response (ECochG-TR) recorded at the best-frequency electrode (BF-ECochG-TR) correlates more strongly with speech perception performance than ECochG-TR measured at the round window (RW-ECochG-TR). Design, Setting, and Participants: This single-center cross-sectional study recruited 142 patients from July 1, 2021, to April 30, 2022, with 1-year follow-up. Exclusions included perilymph suctioning, crimped sound delivery tubes, non-native English speakers, inner ear malformations, nonpatent external auditory canals, or cochlear implantation revision surgery. Exposures: Cochlear implantation. Main Outcomes and Measures: Speech perception testing, including the consonant-nucleus-consonant (CNC) words test, AzBio sentences in quiet, and AzBio sentences in noise plus 10-dB signal to noise ratio (with low scores indicating poor performance and high scores indicating excellent performance on all tests), at 6 months postoperatively; and RW-ECochG-TR and BF-ECochG-TR (measured for 250, 500, 1000, and 2000 Hz). Results: A total of 109 of the 142 eligible postlingual adults (mean [SD] age, 68.7 [15.8] years; 67 [61.5%] male) were included in the study. Both BF-ECochG-TR and RW-ECochG-TR were correlated with 6-month CNC scores (BF-ECochG-TR: r = 0.74; 95% CI, 0.62-0.82; RW-ECochG-TR: r = 0.67; 95% CI, 0.54-0.76). A multivariate model incorporating age, duration of hearing loss, and angular insertion depth did not outperform BF-ECochG-TR or RW-ECochG-TR alone. The BF-ECochG-TR correlation with CNC scores was significantly stronger than the RW-ECochG-TR correlation (r difference = -0.18; 95% CI, -0.31 to -0.01; z = -2.02). More moderate correlations existed between 6-month AzBio scores in noise, Montreal Cognitive Assessment (MoCA) scores (r = 0.46; 95% CI, 0.29-0.60), and BF-ECochG-TR (r = 0.42; 95% CI, 0.22-0.58). MoCA and the interaction between BF-ECochG-TR and MoCA accounted for a substantial proportion of variability in AzBio scores in noise at 6 months (R2 = 0.50; 95% CI, 0.36-0.61). Conclusions and Relevance: In this case series, BF-ECochG-TR was identified as having a stronger correlation with cochlear implantation performance than RW-ECochG-TR, although both measures highlight the critical role of the cochlear-neural substrate on outcomes. Demographic, audiologic, and surgical factors demonstrated weak correlations with cochlear implantation performance, and performance in noise was found to require a robust cochlear-neural substrate (BF-ECochG-TR) as well as sufficient cognitive capacity (MoCA). Future cochlear implantation studies should consider these variables when assessing performance and related interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".