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J Am Acad Audiol. 2021 Jun;32(6):339-346. doi: 10.1055/s-0041-1727273. Epub 2021 Jun 3.
2
Evidence of Cochlear Synaptopathy and the Effect of Systemic Steroid in Acute Idiopathic Tinnitus With Normal Hearing.耳蜗突触病的证据及全身类固醇治疗伴有正常听力的急性特发性耳鸣的效果。
Otol Neurotol. 2021 Aug 1;42(7):978-984. doi: 10.1097/MAO.0000000000003189.
3
Tinnitus Is Associated With Extended High-frequency Hearing Loss and Hidden High-frequency Damage in Young Patients.耳鸣与年轻患者的高频听力损失延长和高频隐匿性损伤有关。
Otol Neurotol. 2021 Mar 1;42(3):377-383. doi: 10.1097/MAO.0000000000002983.
4
Search for Electrophysiological Indices of Hidden Hearing Loss in Humans: Click Auditory Brainstem Response Across Sound Levels and in Background Noise.寻找人类隐匿性听力损失的电生理指标:不同声级及背景噪声下的短声听觉脑干反应
Ear Hear. 2021 Jan/Feb;42(1):53-67. doi: 10.1097/AUD.0000000000000905.
5
Assessment of Hidden Hearing Loss in Normal Hearing Individuals with and Without Tinnitus.评估有耳鸣和无耳鸣的正常听力个体的隐性听力损失。
J Int Adv Otol. 2020 Apr;16(1):87-92. doi: 10.5152/iao.2020.7062.
6
Risk of noise-induced hearing loss due to recreational sound: Review and recommendations.因娱乐性声音导致噪声性听力损失的风险:综述与建议。
J Acoust Soc Am. 2019 Nov;146(5):3911. doi: 10.1121/1.5132287.
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Middle Ear Muscle Reflex and Word Recognition in "Normal-Hearing" Adults: Evidence for Cochlear Synaptopathy?“听力正常”成年人的中耳肌肉反射与单词识别:蜗神经突触病变的证据?
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Translating animal models to human therapeutics in noise-induced and age-related hearing loss.将动物模型转化为噪声性和年龄相关性听力损失的人类治疗方法。
Hear Res. 2019 Jun;377:44-52. doi: 10.1016/j.heares.2019.03.003. Epub 2019 Mar 15.
9
Risk Assessment of Recreational Noise-Induced Hearing Loss from Exposure through a Personal Audio System-iPod Touch.通过个人音频系统-iPod Touch暴露导致的娱乐性噪声性听力损失的风险评估。
J Am Acad Audiol. 2019 Jul/Aug;30(7):619-633. doi: 10.3766/jaaa.17140. Epub 2018 Nov 1.
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Primary Neural Degeneration in the Human Cochlea: Evidence for Hidden Hearing Loss in the Aging Ear.人类耳蜗原发性神经退行性变:老年耳隐匿性听力损失的证据。
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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.

DOI:10.1055/s-0042-1756164
PMID:36313044
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9605806/
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。