Predicting Matrix Test Effectiveness for Evaluating Auditory Performance in Noise Using Pure-Tone Audiometry and Speech Recognition in Quiet in Cochlear Implant Recipients

Abstract

Introduction: Auditory performance in noise of cochlear implant recipients can be assessed with the adaptive Matrix test (MT); however, when the speech-to-noise ratio (SNR) exceeds 15 dB, the background noise has any negative impact on the speech recognition. Here, we aim to evaluate the predictive power of aided pure-tone audiometry and speech recognition in quiet and establish cut-off values for both tests that indicate whether auditory performance in noise can be assessed using the Matrix sentence test in a diffuse noise environment. Methods: Here, we assessed the power of pure-tone audiometry and speech recognition in quiet to predict the response to the MT. Ninety-eight cochlear implant recipients were assessed using different sound processors from Advanced Bionics (n = 56) and CochlearTM (n = 42). Auditory tests were performed at least 1 year after cochlear implantation or upgrading the sound processor to ensure the best benefit of the implant. Auditory assessment of the implanted ear in free-field conditions included: pure-tone average (PTA), speech discrimination score (SDS) in quiet at 65 dB, and speech recognition threshold (SRT) in noise that is the SNR at which the patient can correctly recognize 50% of the words using the MT in a diffuse sound field. Results: The SRT in noise was determined in 60 patients (61%) and undetermined in 38 (39%) using the MT. When cut-off values for PTA 41% were used separately, they were able to predict a positive response to the MT in 83% of recipients; using both cut-off values together, the predictive value reached 92%. Discussion: As the pure-tone audiometry is standardized universally and the speech recognition in quiet could vary depending on the language used; we propose that the MT should be performed in recipients with PTA 36 dB, a list of Matrix sentences at a fixed SNR should be presented to determine the percentage of words understood. This approach should enable clinicians to obtain information about auditory performance in noise whenever possible.