Objective: To evaluate the impact of preoperative and perioperative factors on postlinguistic adult cochlear implant (CI) performance and design a multivariate prediction model.
Study design: Prospective cohort study.
Setting: Tertiary referral center.
Patients and interventions: Two hundred thirty-nine postlinguistic adult CI recipients.
Main outcome measures: Speech-perception testing (consonant-nucleus-consonant [CNC], AzBio in noise +10-dB signal-to-noise ratio) at 3, 6, and 12 months postoperatively; electrocochleography-total response (ECochG-TR) at the round window before electrode insertion.
Results: ECochG-TR strongly correlated with CNC word score at 6 months ( r = 0.71, p < 0.0001). A multivariable linear regression model including age, duration of hearing loss, angular insertion depth, and ECochG-TR did not perform significantly better than ECochG-TR alone in explaining the variability in CNC. AzBio in noise at 6 months had moderate linear correlations with Montreal Cognitive Assessment (MoCA; r = 0.38, p < 0.0001) and ECochG-TR ( r = 0.42, p < 0.0001). ECochG-TR and MoCA and their interaction explained 45.1% of the variability in AzBio in noise scores.
Conclusions: This study uses the most comprehensive data set to date to validate ECochG-TR as a measure of cochlear health as it relates to suitability for CI stimulation, and it further underlies the importance of the cochlear neural substrate as the main driver in speech perception performance. Performance in noise is more complex and requires both good residual cochlear function (ECochG-TR) and cognition (MoCA). Other demographic, audiologic, and surgical variables are poorly correlated with CI performance suggesting that these are poor surrogates for the integrity of the auditory substrate.
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