How variation in cochlear implant performance relates to differences in MAP parameters

Enrico Migliorini1,2, Bastiaan Van Dijk1, Birgit Philips1, Emmanuel Mylanus2, Wendy Huinck2

1 Cochlear CTC, Mechelen, BE; 2 Radboud university medical center, Nijmegen, NL

Background: Cochlear Implants are effective devices for the restoration of hearing capabilities in profoundly deaf people. However, CI recipients with similar age, aetiology, clinical history, implanted device and residual hearing may have vastly different speech perception outcomes. The objective of this study is to investigate the relation between this unexplained variability and mapping levels through a retrospective analysis of the fitting data from the ENT department of Radboud university medical center Nijmegen.

Methods: The anonymized database contains both CVC speech audiometry tests (NVA) collected from CI recipients with a Nucleus™ CI and corresponding mapping information from the CustomSound™ fitting software. First a principal component analysis (PCA) was performed to reduce the dimensionality of the MAP dataset, and the subjects were split into tertiles based on performance (lowest tertile;<66% phoneme score, highest tertile; >87% phoneme score).  Consequently two test were performed on the data: 1) Differences in the PCA components between subjects in the highest and lowest tertile was checked with the Mann-Whitney-Wilcoxon’s u test; 2) Spearman’s and Pearson’s correlation coefficients were calculated in order to find correlations between performance and the maps’ components.

Results: We found statistically significant differences between the average maps of subjects in the highest and lowest tertile.

Conclusion: We found clinically significant differences between the populations, with an effect size large enough to potentially allow to develop a fitting intervention to address poor speech recognition. In this conference contribution we will discuss the results, the interpretation and suggest follow-up work.

Migliorini et al
Graphic representation of how differences in PCA components are reflected in MAPs.