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Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients
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-perceptio...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866505/ https://www.ncbi.nlm.nih.gov/pubmed/35197556 http://dx.doi.org/10.1038/s41598-022-07175-7 |
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author | Walia, Amit Shew, Matthew A. Kallogjeri, Dorina Wick, Cameron C. Durakovic, Nedim Lefler, Shannon M. Ortmann, Amanda J. Herzog, Jacques A. Buchman, Craig A. |
author_facet | Walia, Amit Shew, Matthew A. Kallogjeri, Dorina Wick, Cameron C. Durakovic, Nedim Lefler, Shannon M. Ortmann, Amanda J. Herzog, Jacques A. Buchman, Craig A. |
author_sort | Walia, Amit |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8866505 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88665052022-02-25 Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients Walia, Amit Shew, Matthew A. Kallogjeri, Dorina Wick, Cameron C. Durakovic, Nedim Lefler, Shannon M. Ortmann, Amanda J. Herzog, Jacques A. Buchman, Craig A. Sci Rep Article 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. Nature Publishing Group UK 2022-02-23 /pmc/articles/PMC8866505/ /pubmed/35197556 http://dx.doi.org/10.1038/s41598-022-07175-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Walia, Amit Shew, Matthew A. Kallogjeri, Dorina Wick, Cameron C. Durakovic, Nedim Lefler, Shannon M. Ortmann, Amanda J. Herzog, Jacques A. Buchman, Craig A. Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients |
title | Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients |
title_full | Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients |
title_fullStr | Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients |
title_full_unstemmed | Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients |
title_short | Electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients |
title_sort | electrocochleography and cognition are important predictors of speech perception outcomes in noise for cochlear implant recipients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866505/ https://www.ncbi.nlm.nih.gov/pubmed/35197556 http://dx.doi.org/10.1038/s41598-022-07175-7 |
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