CC BY-NC-ND 4.0 · Laryngorhinootologie 2019; 98(S 02): S325-S326
DOI: 10.1055/s-0039-1686494

Identification of Predictors for Neuronal Health Status in Cochlear Implant Patients

V Scheper
1   HNO Klinik der MHH, Hannover
K Klötzer
1   HNO Klinik der MHH, Hannover
T Lenarz
1   HNO Klinik der MHH, Hannover
L Gärtner
1   HNO Klinik der MHH, Hannover
› Author Affiliations
Cluster of Exzellenz EXC 1077/1 "Hearing4All"


Cochlear implants (CI) are the treatment of choice in profoundly deaf patients. Measuring the electrically evoked compound action potential (eCAP) has become an important tool for verifying the vitality of the spiral ganglion neurons which are the target cells of the CI-stimulation determining, amongst others, the success achievable with the CI.

In this study we investigated possible correlations between the eCAP amplitude growth function (AGF) slope, the implant used, and the anamnestic parameters duration of hearing loss, age at implantation, and etiology, to identify possible predictors for SGN health status and therefor for CI-outcome.


The retrospective study included 184 patients being implanted with MED-EL CIs of various array lengths. Correlation analysis was performed for the mean AGF slope of one implant (electrode 1 to 12), for separate electrodes, as well as for grouped electrodes (electrodes 1 – 3, 4 – 9, 10 – 12).


The mean eCAP AGF slope is not correlated to the cochlear implant array length used. It is negatively correlated to the duration of hearing loss (p = 0.002) and the age at implantation (p < 0.001) and positively correlated to the etiology (p = 0.016).


Since the eCAP slope, as a functional measure of neural health in the inner ear, correlates significantly negatively with age at cochlear implantation and duration of deafness, early implantation of a CI is recommended for sensorineural hearing loss.

Publication History

Publication Date:
23 April 2019 (online)

© 2019. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (

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