Accuracy and variability in clinical predictions of speech recognition outcomes for cochlear implant users.

Abstract

Objectives: An improvement in speech perception is a major well-documented benefit of cochlear implantation (CI), which is commonly discussed with CI candidates to set expectations. However, a large variability exists in speech perception outcomes. We evaluated the accuracy of clinical predictions of post-CI speech perception scores.

Design: In an online survey, clinicians involved in CI care were asked to predict 6-month performance on AzBio sentences and CNC words for 15 anonymised CI patients based on demographic, medical, and audiological data, and preoperative speech recognition scores.

Study sample: Sixty-five participants (72% audiologists, 14% neurotologists, 14% speech-language pathologists, and CI researchers) provided predictions for two or more cases, and 43 provided predictions for all 15 CI cases.

Results: Clinical predictions had low accuracy and high variability (i.e. median interclass correlation coefficients [ICC] 0.11-0.13). No relationship was observed between clinicians' confidence and prediction accuracy.

Conclusions: The present findings are consistent with previous research and indicate a concerning discrepancy between clinical predictions and actual speech perception outcomes for adult post-lingual CI users. Future research may explore incorporating predictions based on statistical models into speech outcome prognostication to reduce variance and improve counselling and expectations setting for individual CI candidates.