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The auditory brainstem response is an evoked potential that can be clinically used to estimate hearing sensitivity and to identify auditory nervous system pathology. Recently, there has been an increase in the implementation of the CE-Chirp stimulus in AABR equipment for neonatal hearing screening. The purpose of this study is to evaluate the diagnostic accuracy of the LS CE-Chirp-evoked ABR compared to the traditionally used click-evoked ABR for the identification of different degrees and configurations of sensorineural (SNHL) hearing loss. An exploratory within-subject comparative research design was used. 49 ears with mild to moderate sensorineural hearing loss were assessed. Participants were assessed in a single session. Audiometric pure tone thresholds were obtained at 125-8000 Hz and ABR thresholds were measured using the click and LS CE-Chirp stimuli respectively. Click- and LS CE-Chirp-evoked thresholds were compared with each other and with behavioural pure tone average (PTA), high frequency average (HFA) and low frequency average (LFA). Diagnostic accuracy of the two ABR stimuli was also compared by using ROC curves. Differences between click- and LS CE Chirp-evoked ABR, and behavioural thresholds were not statistically significant (p>0.05). The strongest significant correlation for ABR using clicks to behavioural thresholds was found at 2000 and 4000 Hz, whereas, the strongest correlation for LS CE-Chirp ABRs to behavioural thresholds was found at 1000, 2000 and 4000 Hz (r>0.7, p<0.001). A very strong, positive correlation was found between both click (r=0.805) and LS CE-Chirp (r=0.825) and the behavioural PTA (p<0.001). The mean differences for LS CE-Chirp were smaller than those of the click for PTA and low frequency range. ROC curves indicated better AUC values for the LS CE-Chirp at LFA and HFA compared to the click, also showing a narrower confidence interval and less variance than the click. The predictive accuracy of the LS CE-Chirp-evoked ABR was slightly better than that of the click with reference to PTA, HFA and LFA thresholds; furthermore, it is less variable and more accurate than the click-evoked ABR with reference to HFA. Thus, the LS CE-Chirp is an accurate stimulus for estimation of hearing sensitivity using ABR when compared to the gold standard click stimulus for the purpose of identification of different configurations of SNHL. / Dissertation (MA Audiology) University of Pretoria, 2019. / Speech-Language Pathology and Audiology / MA (Audiology) / Unrestricted

Background The noise-exposed population in the mining industry in South Africa poses unique problems to the occupational audiologist working in this environment, due to the broad linguistic and cultural diversity in the audiology and mining environment. Unfortunately, the problems are also exacerbated by a high incidence of pseudohypacusis within this population who are incentivised by compensation for NIHL. A solution to these specific problems would be the reliable and valid use of an objective test of function such as the DPOAE. The rationale for the study therefore was to extend the body of knowledge about the use of DPOAEs in the noise-exposed mining population. Methodology The current study was divided into two phases: phase one’s objectives entailed the investigation of the characteristics of DPOAEs in a noise-exposed mining population; phase two aimed to develop a multivariate regression model that would facilitate the prediction of the hearing threshold levels from the DPOAE levels in this population. Objectives The objectives in phase one of the study were to investigate the bivariate correlations between DPOAE levels and air-conduction hearing threshold levels in noise-exposed gold miners, for the three stimulus procedures. The study also aimed to investigate the bivariate correlations between various pure-tone averages (PTA) and the DPOAE averages of f2 frequencies closest to those pure-tone frequencies. Similarly, the Speech Recognition Thresholds (SRT) were correlated with DPOAE averages of f2 frequencies closest to the PTA. xx The study further aimed to investigate the characteristics of DPOAEs in noiseexposed gold miners by comparing the average DPOAE levels for different age category groups, different ethnic groups and for different occupation types. Finally, phase one aimed to describe the characteristics of emission level and noise floor differences (DP-NF) in a DPOAE database of a noise-exposed gold mining population. Phase two of the study had the objective of developing a multivariate prediction model using stepwise regression analysis to identify which of the DPOAE frequencies produced the best prediction of the audiogram frequencies when multivariate inputs were used for each stimulus procedure. The objective was also to evaluate the use of the predicted audiograms’ calculated percentage loss of hearing (PLH) with that of the actual PLH. This retrospective record review used an audiological database from a mine in the North West province of South Africa that contained 4800 records. The required sample size to be representative of the population was statistically determined. The records were randomly selected resulting a sample size for the FB2-S group of 161, for the FB1-S group of 177 and the FB1-S group of 155 respectively. The hearing loss characteristics in the samples ranged from normal to profound losses with the majority being mild to moderate hearing losses. Results The findings of phase one showed negative correlations ranging from -0.327 to -0.573 for Frequency Band 1- Replicated (FB1-R) between DPOAE levels and air conduction hearing threshold levels. Similarly, Frequency Band 1-Single (FB1-S) and Frequency Band 2-Single (FB2-S) also showed negative correlations (ranging from -0.203 to -0.609 and -0.274 to -0.738 respectively). These correlation strengths have been confirmed previously by other published studies. xxi Correlations between groups of frequencies on an audiogram and averaged match groups of DPOAE frequencies by intensity levels, both for PTA and SRT, ranged between -0.323 and -0.661. No statistically significant differences were found between the DPOAE measurements and ethnic groups of African and Caucasian (Sample size of 175 for FB1-S, 137 for FB1-R and 161 for FB2-S). No differences were found between the DPOAE levels and the occupation types of mining team members, stopers and drillers. There was, however, a relational finding of a progressive decrement of DPOAE intensity levels by decade of age increase (Sample size of 37 for FB1-S, 45 for FB1-R and 155 for FB2-S). Mean DP levels in this population ranged from 1.5 to -14 dB SPL, and mean NF levels in the sample ranged from 0.1 to -16.8 dB SPL with the mean DP-NF difference ranges form 0.4 to 9.3 dBSPL. More than 60% of the data collected resulted in a DP-NF of less than 10 dB SPL. The simple correlation relationship between hearing threshold levels and DPOAEs did not sufficiently explain the variance within the sample and due to the fact that a number of the independent variables in the sample were highly correlated, there was a call to use a method that allows for multicolinearity (i.e. stepwise regression analysis) in order to develop a prediction model. Consequently, phase two of the study was able to compare actual air-conduction hearing threshold levels with those calculated with the prediction model, and then calculate predicted percentage loss of hearing (PLH) with actual PLH found in the noise-exposed gold miners. In phase two, with the use of the predictive models, the predicted hearing threshold levels were found to differ from the actual thresholds by no more than 7dB HL across all frequencies (average of 5 dB HL for FB1-R, 2 dB HL for FB1-S and 3 dB HL for FB2-S). The differences for each audiogram frequency between the actual and the predicted thresholds are represented on scatter plots in phase two of the thesis. The PLH of the predicted audiograms was calculated using the weighted xxii tables prescribed by the Compensation for Occupational Diseases and Injuries Act (COIDA). A comparison of the predicted PLH with the actual PLH indicated that the predicted PLH ranged between minus 1.3% PLH and plus 6.7% PLH of the actual PLH. Results of the study are discussed with regards to the clinical implications, and the implications for training occupational audiologists in South Africa. The results of this study will improve and inform practice in the mining environment and in the field of compensation for NIHL. By developing a reliable prediction tool which is implemented on an objective test proven to document the extent of damage incurred from noise-exposure, a clinician will gain greater confidence in an accurate diagnosis, thereby further safeguarding a vulnerable population. The results from this study are highly relevant to the mining industry and will add value to the industrial development of South Africa by informing the policy on hearing conservation and compensation, thereby increasing the awareness of the need for improved occupational health and safety conditions and sustainable development in the mining industry.

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In the evaluation of special populations, such as neonates, infants and malingerers, audiologist often have to rely heavily on objective measurements to assess hearing ability. Current objective audiological procedures such as tympanometry, the acoustic reflex, auditory brainstem response and transient evoked otoacoustic emissions, however, have certain limitations, contributing to the need of an objective, non¬invasive, rapid, economic test of hearing that evaluate hearing ability in a wide range of frequencies. The purpose of this study was to investigate distortion product otoacoustic emissions (DPOAEs) as an objective test of hearing. The main aim was to attempt to predict hearing ability at 500 Hz, 1000 Hz, 2000 Hz and 4000 Hz with DPOAEs and artificial neural networks (ANNs) in normal and hearing-impaired ears. Other studies that attempted to predict hearing ability with DPOAEs and conventional statistical methods were only able to distinguish between normal and impaired hearing. Back propagation neural networks were trained with the pattern of all present and absent DPOAE responses of 11 DPOAE frequencies of eight DP Grams and pure tone thresholds at 500 Hz, 1000 Hz, 2000 Hz and 4000 Hz. The neural network used the learned correlation between these two data sets to predict hearing ability at 500 Hz, 1000 Hz, 2000 Hz and 4000 Hz. Hearing ability was not predicted as a decibel value, but into one of several categories spanning 10-15dB. Results indicated that prediction accuracy of normal hearing was 92% at 500 Hz, 87% at 1000 Hz, 84% at 2000 Hz and 91% at 4000 Hz. The prediction of hearing-impaired categories was less satisfactory, due to insufficient data for the ANNs to train on. The variables age and gender were included in some of the neural network runs to determine their effect on the distortion product. Gender had only a minor positive effect on prediction accuracy, but age affected prediction accuracy considerably in a positive way. The effect of the amount of data that the neural network had to train on was also investigated. A prediction versus ear count correlation strongly suggested that the inaccurate predictions of hearing-impaired categories is not a result of an inability of DPOAEs to predict pure tone thresholds in hearing impaired ears, but a result of insufficient data for the neural network to train on. This research concluded that DPOAEs and ANNs can be used to accurately predict hearing ability within 10dB in normal and hearing-impaired ears from 500 Hz to 4000 Hz for hearing losses of up to 65dB HL. / Dissertation (MCommunication Pathology)--University of Pretoria, 2009. / Speech-Language Pathology and Audiology / unrestricted

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