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Updated: Jul 16, 2025

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Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
Published on: March 24, 2023
417
Factors Affecting Performance in Adults With Cochlear Implants: A Role for Cognition and Residual Cochlear Function
Amit Walia1, Matthew A Shew, Shannon M Lefler
1Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine in St. Louis, St. Louis, Missouri.
Summary
Electrocochleography-total response (ECochG-TR) effectively measures cochlear health for cochlear implant (CI) suitability. While ECochG-TR is key for speech perception, performance in noise also depends on cognitive function.
Area of Science:
- Audiology
- Neurosurgery
- Biomedical Engineering
Background:
- Cochlear implant (CI) surgery offers significant hearing restoration for adults with severe to profound sensorineural hearing loss.
- Predicting post-operative CI performance remains challenging, with limited understanding of the interplay between cochlear health, cognitive function, and surgical factors.
- Identifying reliable biomarkers for CI outcomes is crucial for patient selection and surgical planning.
Purpose of the Study:
- To evaluate the impact of preoperative and perioperative factors on postlinguistic adult cochlear implant (CI) performance.
- To develop a multivariate prediction model for CI outcomes.
- To validate electrocochleography-total response (ECochG-TR) as a measure of cochlear health relevant to CI stimulation.
Main Methods:
- Prospective cohort study involving 239 postlinguistic adult CI recipients at a tertiary referral center.
- Speech-perception testing (CNC word recognition, AzBio in noise) at 3, 6, and 12 months postoperatively.
- Electrocochleography-total response (ECochG-TR) measured at the round window before electrode insertion.
Main Results:
- ECochG-TR strongly correlated with consonant-nucleus-consonant (CNC) word scores at 6 months (r = 0.71, p < 0.0001).
- A multivariate model including age, hearing loss duration, insertion depth, and ECochG-TR did not significantly improve CNC prediction over ECochG-TR alone.
- AzBio in noise scores showed moderate correlations with Montreal Cognitive Assessment (MoCA; r = 0.38) and ECochG-TR (r = 0.42), with ECochG-TR and MoCA explaining 45.1% of the variability.
Conclusions:
- ECochG-TR is validated as a measure of cochlear health and suitability for CI stimulation.
- The cochlear neural substrate, as indicated by ECochG-TR, is a primary driver of speech perception performance after CI.
- Auditory performance in noise is complex, influenced by both cochlear function (ECochG-TR) and cognitive abilities (MoCA).
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