Walia A, Shew MA, Varghese J, Ioerger P, Lefler SM, Ortmann AJ, Herzog JA, Buchman CA. Improved Cochlear Implant Performance Estimation Using Tonotopic-Based Electrocochleography.
JAMA Otolaryngol Head Neck Surg 2023;
149:1120-1129. [PMID:
37856099 PMCID:
PMC10587831 DOI:
10.1001/jamaoto.2023.2988]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 08/04/2023] [Indexed: 10/20/2023]
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.
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