Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing
Abstract
Background & aim: The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but the extent that they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The study aims to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches.
Patients and methods: The study included 105 adult subjects with normal hearing and hearing loss that underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developped to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of the each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves curves and to estimate the areas under the curves in order to compare different multivariate analyses.
Results: Each of the three multivariate analyses provides high values of the area under the curves. Each otoacoustic emission test presents small differences for the value of the area under the curve, but transient otoacoustic emissions seems to be the most powerful predictive for the hearing level for the right ear and distorsion products for the left ear. Adding demographic variables, the value of the area under the curve is similar for both ears, but we found out that tinnitus is a strong predictive variable only for the left ear. Our multivariate analyses revealed that age is a predictor factor of the auditory status for both ears. In our study, gender had no predictive value for hearing level in any of the multivariate analyses. Our study also confirms that the combination of age and distorsion products can better predict hearing level than distorsion products alone. We have found out that the otoacoustic emissions tests have improved performance for both ears when using the multivariate analysis which combines transient otoacoustic emissions and distortion products data.
Conclusion: Like any other audiological test, using otoacoustic emissions to identify hearing loss is not without error. Even when applying multivariate analysis, perfect test performance is never achieved. Although most studies demonstrated the benefit of using the multivariate analysis, it has not been incorporated into clinical decisions maybe because of the idiosyncratic nature of multivariate solutions or because of the lack of the validation studies.
Key words: otoacoustic emissions, multivariate analyses, logistic regression, hearing loss, receiver operating curves.