Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients

Amit Walia,Shannon M Lefler,Jacques A Herzog,Dorina Kallogjeri,Amanda J Ortmann,Cameron C Wick,Matthew A Shew,Craig A Buchman,Nedim Durakovic

doi:10.1038/s41598-022-07175-7

Amit Walia, Shannon M Lefler + Show 7 more

Open Access

https://doi.org/10.1038/s41598-022-07175-7

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Journal: Scientific Reports	Publication Date: Feb 23, 2022
Citations: 23	License type: open-access

Affiliation: Washington University in St. Louis

Abstract

Although significant progress has been made in understanding outcomes following cochlear implantation, predicting performance remains a challenge. Duration of hearing loss, age at implantation, and electrode positioning within the cochlea together explain ~ 25% of the variability in speech-perception scores in quiet using the cochlear implant (CI). Electrocochleography (ECochG) responses, prior to implantation, account for 47% of the variance in the same speech-perception measures. No study to date has explored CI performance in noise, a more realistic measure of natural listening. This study aimed to (1) validate ECochG total response (ECochG-TR) as a predictor of performance in quiet and (2) evaluate whether ECochG-TR explained variability in noise performance. Thirty-five adult CI recipients were enrolled with outcomes assessed at 3-months post-implantation. The results confirm previous studies showing a strong correlation of ECochG-TR with speech-perception in quiet (r = 0.77). ECochG-TR independently explained 34% of the variability in noise performance. Multivariate modeling using ECochG-TR and Montreal Cognitive Assessment (MoCA) scores explained 60% of the variability in speech-perception in noise. Thus, ECochG-TR, a measure of the cochlear substrate prior to implantation, is necessary but not sufficient for explaining performance in noise. Rather, a cognitive measure is also needed to improve prediction of noise performance.

Highlights

Significant progress has been made in understanding outcomes following cochlear implantation, predicting performance remains a challenge
Hair cell function can be extrapolated from the cochlear microphonic (CM) and summating potential (SP), where the outer hair cells generate the CM potential[8] and the inner hair cells contribute more to the SP9
The neural function can be measured from the compound action potential (CAP), which is representative of synchronous action potential across numerous fibers in response to an acoustic stimulus

Summary

Introduction

Significant progress has been made in understanding outcomes following cochlear implantation, predicting performance remains a challenge. Age at implantation, and electrode positioning within the cochlea together explain ~ 25% of the variability in speech-perception scores in quiet using the cochlear implant (CI). When a similar study was repeated in 2013, these two variables accounted for less than ~ 20% of the variance in CI performance[4,5] This was thought to be due to a shift in the patient population over the last 2 decades, where patients are undergoing implantation with shorter durations of deafness. Another factor more recently shown to be correlated with CI performance is electrode positioning within the cochlea. The auditory nerve neurophonic (ANN) is the phase-locked neural firing throughout the duration of a tone; this can only be visualized when alternating polarity tones are used and is a sinusoidal wave of twice the stimulus frequency[10]

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