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利用iPhone健康应用程序数据以及耳蜗和脑干对快速点击率的电生理反应来研究噪声性耳蜗突触病变的特征。

Examining the Profile of Noise-Induced Cochlear Synaptopathy Using iPhone Health App Data and Cochlear and Brainstem Electrophysiological Responses to Fast Clicks Rates.

作者信息

Kaf Wafaa A, Turntine Madison, Jamos Abdullah, Smurzynski Jacek

机构信息

Department of Communication Sciences and Disorders, Missouri State University, Springfield, Missouri.

Department of Audiology and Speech-Language Pathology, East Tennessee State University, Johnson City, Tennessee.

出版信息

Semin Hear. 2022 Oct 26;43(3):197-222. doi: 10.1055/s-0042-1756164. eCollection 2022 Aug.

Abstract

Little is known about objective classifying of noise exposure risk levels in personal listening device (PLD) users and electrophysiologic evidence of cochlear synaptopathy at very fast click rates. The aim of the study was to objectively classify noise exposure risk using iPhone Health app and identify signs of cochlear synaptopathy using behavioral and electrophysiologic measures. Thirty normal-hearing females (aged 18-26 years) were grouped based on their iPhone Health app's 6-month listening level and noise exposure data into low-risk and high-risk groups. They were assessed using a questionnaire, extended high-frequency (EHF) audiometry, QuickSIN test, distortion-product otoacoustic emission (DPOAE), and simultaneous recording of electrocochleography (ECochG) and auditory brainstem response (ABR) at three click rates (19.5/s, 97.7/s, 234.4/s). A series of ANOVAs and independent samples -test were conducted for group comparison. Both groups had within-normal EHF hearing thresholds and DPOAEs. However, the high-risk participants were over twice as likely to suffer from tinnitus, had abnormally large summating potential to action potential amplitude and area ratios at fast rates, and had slightly smaller waves I and V amplitudes. The high-risk group demonstrated a profile of behavioral and objective signs of cochlear synaptopathy based on ECochG and ABR recordings at fast click rates. The findings in this study suggest that the iPhone Health app may be a useful tool for further investigation into cochlear synaptopathy in PLD users.

摘要

对于个人听力设备(PLD)使用者的噪声暴露风险水平的客观分类以及在非常快的点击速率下耳蜗突触病变的电生理证据,人们了解甚少。本研究的目的是使用iPhone健康应用程序客观地分类噪声暴露风险,并使用行为和电生理测量方法识别耳蜗突触病变的迹象。30名听力正常的女性(年龄在18 - 26岁之间)根据其iPhone健康应用程序的6个月听力水平和噪声暴露数据分为低风险组和高风险组。使用问卷调查、扩展高频(EHF)听力测定、QuickSIN测试、畸变产物耳声发射(DPOAE)以及在三种点击速率(19.5/s、97.7/s、234.4/s)下同时记录耳蜗电图(ECochG)和听觉脑干反应(ABR)对她们进行评估。进行了一系列方差分析和独立样本t检验以进行组间比较。两组的EHF听力阈值和DPOAE均在正常范围内。然而,高风险参与者患耳鸣的可能性是低风险参与者的两倍多,在快速点击速率下,其总和电位与动作电位幅度和面积的比值异常大,并且I波和V波幅度略小。基于快速点击速率下的ECochG和ABR记录,高风险组表现出耳蜗突触病变的行为和客观迹象。本研究的结果表明,iPhone健康应用程序可能是进一步研究PLD使用者耳蜗突触病变的有用工具。

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