Mapping Experienced Cochlear Implant (CI) Recipients using Nucleus Fitting Software (NFS) in Comparison to Custom Sound (CS)

Advances in cochlear implant (CI) technology together with expanded indications for implantation have led to increasing numbers of CI recipients. Years of experience have shown that successful outcomes and consistent use of a CI requires individual tailoring of the map`s characteristic features. Thus, programming requires clinical expertise and is a time-consuming process, imposing management challenges in the continuously growing CI programs worldwide. Addressing these issues, a new, simplified programming software was created by Cochlear Ltd. The aim of the current study was to assess whether the traditional Custom Sound (CS) fitting software and the new Nucleus Fitting Software (NFS) yield comparable outcomes, and self-reported quality of hearing and life, in experienced CI recipients. Participants: 15 postlingually deafened adults, 42 -75 years old, implanted with Cochlear Freedom or Profile implants. Studied variables: Aided thresholds, speech reception thresholds, monosyllabic word scores in quiet, sentences recognition scores in noise, and results of the Speech, Spatial, and Quality questionnaire. Each CI recipient underwent three programming sessions, at four weeks intervals, performed by experienced clinicians. At the first and second sessions one of the two fitting software were used for programming followed by four weeks of implant use. At the third session both maps were loaded on the processor and the recipient was instructed to use both and choose the preferred map. Performance outcomes and self- reported measures were collected prior to each programming session. Four weeks after the third session participants reported the preferred map by phone or mail. While data collection is still in progress, results indicated comparable speech perception outcomes using both fitting software, however, patients` preferences were not uniform. NFS programming duration was shorter by ~ 30% (ranging from 4 to 12 minutes in 91% of the sessions). Further conclusions will be based on the complete dataset.