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

IF 1.6 4区 医学 Q2 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
Audiology and Neuro-Otology Pub Date : 2024-01-01 Epub Date: 2024-04-10 DOI:10.1159/000535622
Jonathan Flament, Daniele De Seta, Francesca Yoshie Russo, Julie Bestel, Olivier Sterkers, Evelyne Ferrary, Yann Nguyen, Isabelle Mosnier, Renato Torres
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引用次数: 0

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 <36 dB and SDS >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, and 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.

预测矩阵测试的有效性,以评估人工耳蜗植入者在噪声中使用纯音测听和在安静环境中进行语音识别的听觉表现。
前言人工耳蜗植入者在噪声中的听觉表现可通过自适应矩阵测试(MT)进行评估;然而,当语音噪声比(SNR)超过 15 dB 时,背景噪声会对语音识别产生负面影响。在此,我们旨在评估辅助纯音测听和安静环境下语音识别的预测能力,并为这两项测试确定临界值,以表明是否可以在弥散噪声环境下使用矩阵句子测试评估噪声中的听觉表现。方法:在此,我们评估了纯音测听和安静环境下语音识别预测 MT 反应的能力。我们使用 Advanced Bionics(56 人)和 Cochlear(42 人)的不同声音处理器对 98 名人工耳蜗植入者进行了评估。听觉测试在人工耳蜗植入或升级声音处理器至少一年后进行,以确保植入体的最佳效益。在自由声场条件下对植入耳进行的听觉评估包括:纯音平均值(PTA)、65 分贝安静环境下的言语辨别分数(SDS)和噪声中的言语识别阈值(SRT),即患者在弥散声场中使用 MT 能正确识别 50% 单词的信噪比:使用 MT 确定了 60 名患者(61%)的噪声 SRT,38 名患者(39%)的噪声 SRT 未确定。当分别使用 PTA 41% 的临界值时,它们能够预测 83% 的受试者对 MT 的积极反应;同时使用这两个临界值时,预测值达到 92%:由于纯音测听是普遍标准化的,而安静状态下的语音识别能力可能因使用的语言而异;因此我们建议在 PTA 为 36 dB 的受试者中进行 MT,在固定信噪比下呈现 Matrix 句子列表,以确定听懂单词的百分比。这种方法可使临床医生尽可能获得噪声中听觉表现的信息。
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来源期刊
Audiology and Neuro-Otology
Audiology and Neuro-Otology 医学-耳鼻喉科学
CiteScore
3.20
自引率
6.20%
发文量
35
审稿时长
>12 weeks
期刊介绍: ''Audiology and Neurotology'' provides a forum for the publication of the most-advanced and rigorous scientific research related to the basic science and clinical aspects of the auditory and vestibular system and diseases of the ear. This journal seeks submission of cutting edge research opening up new and innovative fields of study that may improve our understanding and treatment of patients with disorders of the auditory and vestibular systems, their central connections and their perception in the central nervous system. In addition to original papers the journal also offers invited review articles on current topics written by leading experts in the field. The journal is of primary importance for all scientists and practitioners interested in audiology, otology and neurotology, auditory neurosciences and related disciplines.
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