Clinical application of a multimodal
electrophysiological test battery to predict
optimal behavioral levels in cochlear implantees
Authors: Sampathkumar Raghunandhan , Ravikumar A. , Kameswaran Mohan , Mandke Kalyani , Ranjith R. 
Published: May 2021

Objectives

Indications for cochlear implantation have expanded to include very young children and those with syndromes or
multiple handicaps. In such cases programming the implant based on behavioral responses may be tedious, wherein matching effective and appropriate measurable auditory percepts (maps) and becomes the key issue in the rehabilitation program.
In ‘difficult to map’ scenarios, objective measures become paramount for predicting optimal current levels to be set in the
map. We aimed (a) to study the trends in multi-modal electrophysiological tests and behavioral responses sequentially over
the first year of implant use, (b) to generate normative data from the above, (c) to correlate the multi-modal electrophysiological thresholds levels with behavioral comfort levels, and (d) to create predictive formulas for deriving optimal comfort levels
(if unknown), using linear and multiple regression analysis.

Materials and Methods

This prospective study included 10 profoundly hearing impaired children aged 2 to 7 years with normal inner ear anatomy and no additional handicaps. They received the Advanced Bionics HiRes 90K implant with Harmony speech processor and used the HiRes-P with Fidelity 120 strategy. They underwent impedance telemetry, neural response
imaging, electrically evoked stapedial response telemetry, and electrically evoked auditory brainstem response tests at 1, 4,
8, and 12 months of implant use, in conjunction with behavioral mapping. Trends in electrophysiological and behavioral responses were analysed using paired t-tests. Using Pearson’s correlation method, electrode-wise correlations were derived for
NRI thresholds versus M-levels, and offset-based (apical, mid-array, and basal array) correlations for EABR and ESRT thresholds versus M-Levels were calculated over time. These were used to derive predictive formulae by linear and multiple regression analysis. Such statistically predicted M-levels were compared with the behaviorally recorded M-levels among the cohort,
using Cronbach’s alpha reliability test method for confirming the efficacy of this method.

Results

NRI, ESRT, and EABR thresholds showed statistically significant positive correlations with behavioral M-levels, which
improved with implant use over time. These correlations were used to derive predicted M-levels using regression analysis.
Such predicted M-levels were found to be close to the actual behavioral M-levels recorded among this cohort and proved to
be statistically reliable.

Conclusions

The study has explored the trends and correlations between electrophysiological tests and behavioral responses, recorded over time among a cohort of cochlear implantees. It provides a statistical method which may be used as a guideline to predict optimal behavioral levels in difficult situations among future implantees. In ‘difficult to map’ scenarios, the best
outcomes will come from following a protocol of sequential behavioral programming in conjunction with electrophysiological correlates.