Clinical Application of a Multimodal Electrophysiological Test Battery to predict Optimal Behavioral Levels in Cochlear Implantees
Raghunandhan Sampathkumar, Ravikumar A, Mohan Kameswaran, Kalyani Mandke, Ranjith R.
(Implant Otology, Madras ENT Research Foundation, Chennai, India)
JHS 2013; 3(4): OA31-48
Objectives: Indications for cochlear implantation have expanded today to include very young children and those with syndromes / multiple handicaps. Programming the implant based on behavioral responses may be tedious for audiologists in such cases, wherein matching an effective MAP and appropriate MAP becomes the key issue in the habilitation program. In ‘Difficult to MAP’ scenarios, objective measures become paramount to predict optimal current levels to be set in the MAP. We aimed, (a) to study the trends in multi-modal electrophysiological tests & 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 formulae for deriving optimal comfort levels (if unknown), using linear & multiple regression analysis.
Material and Methods: Methods: This prospective study included ten profoundly hearing impaired children aged between 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 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 & 12 months of implant use, in conjunction with behavioral Mapping. Trends in electrophysiological & behavioral responses were analyzed using paired t-test. By Karl Pearson’s correlation method, electrode-wise correlations were derived for NRI thresholds versus M-Levels and offset based (apical, mid-array & basal array) correlations for EABR & ESRT thresholds versus M-Levels were calculated over time. These were used to derive predictive formulae by linear & 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: Results: NRI, ESRT & 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 in proximity to the actual behavioral M-Levels recorded among this cohort and proved to be statistically reliable.
Conclusions: Conclusion: The study explores the trends & correlations between electrophysiological tests & behavioral responses, recorded over time among a cohort of cochlear implantees and 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, following a protocol of sequential behavioral programming, in conjunction with electrophysiological correlates will provide the best outcomes.
Keywords: cochlear implant, Impedance Telemetry , Evoked Compound Action Potential, Electrically Evoked Stapedial Response Telemetry, Electrically Evoked Auditory Brainstem Response, Most Comfortable Level