Flament Jonathan, De Seta Daniele, Russo Francesca Yoshie, Bestel Julie, Sterkers Olivier, Ferrary Evelyne, Nguyen Yann, Mosnier Isabelle, Torres Renato
Unité Fonctionnelle Implants Auditifs, Service Oto-Rhino-Laryngologie, GHU Pitié-Salpêtrière, AP-HP/ Sorbonne Université, Paris, France.
Centre Audition LEA Audika, Paris, France.
Audiol Neurootol. 2024;29(5):408-417. doi: 10.1159/000535622. Epub 2024 Apr 10.
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.
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.
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%.
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.
可通过自适应矩阵测试（MT）评估人工耳蜗植入者在噪声环境中的听觉表现；然而，当信噪比（SNR）超过15 dB时，背景噪声会对言语识别产生负面影响。在此，我们旨在评估助听纯音听力测定以及安静环境下言语识别的预测能力，并确定这两项测试的临界值，以表明在扩散噪声环境中是否可以使用矩阵句子测试来评估噪声环境下的听觉表现。
在此，我们评估了纯音听力测定以及安静环境下言语识别预测MT反应的能力。使用来自先进生物科技公司（n = 56）和科利耳公司（n = 42）的不同声音处理器对98名人工耳蜗植入者进行了评估。在人工耳蜗植入或升级声音处理器至少1年后进行听觉测试，以确保植入设备能发挥最佳效果。在自由声场条件下对植入耳进行的听觉评估包括：纯音平均听阈（PTA）、65 dB安静环境下的言语辨别得分（SDS），以及噪声环境下的言语识别阈值（SRT），即患者在扩散声场中使用MT能够正确识别50%单词时的信噪比。
使用MT测定出60名患者（61%）的噪声环境下言语识别阈值，38名患者（39%）未测定出该阈值。当分别使用PTA < 36 dB和SDS > 41%的临界值时，它们能够预测83%的受试者对MT有阳性反应；同时使用这两个临界值时，预测值达到92%。
由于纯音听力测定是普遍标准化的，而安静环境下的言语识别可能因所用语言而异；我们建议，对于PTA < 36 dB的受试者应进行MT测试，对于PTA > 36 dB的受试者，应呈现固定信噪比的一系列矩阵句子，以确定理解的单词百分比。这种方法应能使临床医生尽可能获取有关噪声环境下听觉表现的信息。
