Otolaryngology - Head and Neck Surgery, Ear and Hearing, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands.
Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Ear Hear. 2020 Jul/Aug;41(4):935-947. doi: 10.1097/AUD.0000000000000814.
The objective of this study was to identify parameters which are related to speech recognition in quiet and in noise of cochlear implant (CI) users. These parameters may be important to improve current fitting practices.
Adult CI users who visited the Amsterdam UMC, location VUmc, for their annual follow-up between January 2015 and December 2017 were retrospectively identified. After applying inclusion criteria, the final study population consisted of 138 postlingually deaf adult Cochlear CI users. Prediction models were built with speech recognition in quiet and in noise as the outcome measures, and aided sound field thresholds, and parameters related to fitting (i.e., T and C levels, dynamic range [DR]), evoked compound action potential thresholds and impedances as the independent variables. A total of 33 parameters were considered. Separate analyses were performed for postlingually deafened CI users with late onset (LO) and CI users with early onset (EO) of severe hearing impairment.
Speech recognition in quiet was not significantly different between the LO and EO groups. Speech recognition in noise was better for the LO group compared with the EO group. For CI users in the LO group, mean aided thresholds, mean electrical DR, and measures to express the impedance profile across the electrode array were identified as predictors of speech recognition in quiet and in noise. For CI users in the EO group, the mean T level appeared to be a significant predictor in the models for speech recognition in quiet and in noise, such that CI users with elevated T levels had worse speech recognition in quiet and in noise.
Significant parameters related to speech recognition in quiet and in noise were identified: aided thresholds, electrical DR, T levels, and impedance profiles. The results of this study are consistent with previous study findings and may guide audiologists in their fitting practices to improve the performance of CI users. The best performance was found for CI users with aided thresholds around the target level of 25 dB HL, and an electrical DR between 40 and 60 CL. However, adjustments of T and/or C levels to obtain aided thresholds around the target level and the preferred DR may not always be acceptable for individual CI users. Finally, clinicians should pay attention to profiles of impedances other than a flat profile with mild variations.
本研究旨在确定与人工耳蜗（CI）使用者在安静环境和噪声环境中的言语识别相关的参数。这些参数可能对改进当前的拟合实践很重要。
回顾性地确定了 2015 年 1 月至 2017 年 12 月期间在阿姆斯特丹 UMC（VUmc 校区）进行年度随访的成年 CI 用户。应用纳入标准后，最终研究人群包括 138 名后天聋的成年 Cochlear CI 用户。使用言语识别在安静环境和噪声环境中的结果作为因变量，使用辅助声场阈值以及与拟合相关的参数（即 T 和 C 水平、动态范围[DR]）、诱发复合动作电位阈值和阻抗作为自变量，建立预测模型。共考虑了 33 个参数。分别对后天聋的 CI 用户（迟发性发病[LO]）和先天性重度听力障碍的 CI 用户（早发性发病[EO]）进行了分析。
在 LO 和 EO 组之间，言语识别在安静环境中的差异无统计学意义。与 EO 组相比，LO 组的噪声环境言语识别能力更好。对于 LO 组的 CI 用户，平均辅助阈值、平均电 DR 和表示电极阵列上阻抗分布的测量值被确定为言语识别在安静环境和噪声环境中的预测因子。对于 EO 组的 CI 用户，平均 T 水平似乎是言语识别在安静环境和噪声环境中的模型中的一个显著预测因子，即 T 水平较高的 CI 用户的安静环境和噪声环境中的言语识别能力较差。
确定了与言语识别在安静环境和噪声环境中相关的重要参数：辅助阈值、电 DR、T 水平和阻抗分布。本研究结果与以往研究结果一致，可为听力学家的拟合实践提供指导，以提高 CI 用户的性能。CI 用户的辅助阈值接近 25dB HL 的目标水平，电 DR 在 40 到 60CL 之间时，性能最佳。然而，为了获得接近目标水平和首选 DR 的辅助阈值，调整 T 和/或 C 水平可能并不总是被个别 CI 用户接受。最后，临床医生应注意除了轻度变化的平坦分布外，其他阻抗分布。
