Stamate Mirela Cristina, Todor Nicolae, Cosgarea Marcel
Department of Otorhinolaryngology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.
Department of Medical Informatics and Biostatistics, Institute of Oncology I. Chiricuta, Cluj-Napoca, Romania.
Clujul Med. 2015;88(4):500-12. doi: 10.15386/cjmed-467. Epub 2015 Nov 15.
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 to what extent 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 aim of the study was 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.
The study included 105 adult subjects with normal hearing and hearing loss who 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 developed 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 each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses.
We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high values of area under the curve, suggesting that implementing a multivariate approach to evaluate the performances of each otoacoustic emission test would serve to increase the accuracy in identifying the normal and impaired ears. We encountered the highest area under the curve value for the combined multivariate analysis suggesting that both otoacoustic emission tests should be used in assessing hearing status. Our multivariate analyses revealed that age is a constant predictor factor of the auditory status for both ears, but the presence of tinnitus was the most important predictor for the hearing level, only for the left ear. Age presented similar coefficients, but tinnitus coefficients, by their high value, produced the highest variations of the logistic scores, only for the left ear group, thus increasing the risk of hearing loss. We did not find gender differences between ears for any otoacoustic emission tests, but studies still debate this question as the results are contradictory. Neither gender, nor environment origin had any predictive value for the hearing status, according to the results of our study.
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.
耳声发射作为一种用于耳蜗功能的无创客观检测方法,其临床效用已被长期研究。瞬态耳声发射和畸变产物均可用于识别听力损失,但它们在多大程度上可作为听力损失的预测指标仍存在争议。大多数研究认为,多变量分析比单变量分析具有更好的检测性能。本研究的目的是使用纯音听力图作为金标准程序和不同的多变量统计方法,确定瞬态耳声发射和畸变产物在识别正常听力和听力损失方面的性能。
本研究纳入了105名有正常听力和听力损失的成年受试者,他们接受了相同的测试组合:纯音听力测试、鼓室图测试、耳声发射测试。我们选择使用逻辑回归作为多变量统计技术。建立了三个逻辑回归模型,以表征不同风险因素(年龄、性别、耳鸣、人口统计学特征、由耳声发射定义的耳蜗状态)与由纯音听力测试定义的听力状态之间的关系。多变量分析允许计算逻辑得分,该得分是分析中由系数加权的输入的组合。使用受试者工作特征曲线分析评估每个模型的准确性。我们使用逻辑得分生成受试者工作曲线并估计曲线下面积,以便比较不同的多变量分析。
当使用多频率金标准时,我们针对每只耳朵使用三种不同的多变量分析比较了每种耳声发射(瞬态、畸变产物)的性能。我们证明,所有多变量分析均提供了较高的曲线下面积值,证明了耳声发射的性能。每项耳声发射测试均呈现出较高的曲线下面积值,这表明采用多变量方法评估每项耳声发射测试的性能将有助于提高识别正常和受损耳朵的准确性。我们在联合多变量分析中遇到了最高的曲线下面积值,这表明两种耳声发射测试均应用于评估听力状态。我们的多变量分析显示,年龄是双耳听觉状态的一个恒定预测因素,但耳鸣的存在是听力水平的最重要预测因素,仅适用于左耳。年龄呈现相似的系数,但耳鸣系数因其高值而仅在左耳组中产生了逻辑得分的最大变化,从而增加了听力损失的风险。对于任何耳声发射测试,我们均未发现双耳之间存在性别差异,但由于结果相互矛盾,该问题仍存在争议。根据我们的研究结果,性别和环境来源对听力状态均无任何预测价值。
与任何其他听力学测试一样,使用耳声发射识别听力损失并非没有误差。即使应用多变量分析,也永远无法实现完美的测试性能。尽管大多数研究证明了使用多变量分析的益处,但由于多变量解决方案的特质性或缺乏验证研究,它尚未纳入临床决策。