PDF(Pubmed)
Abstract：
For decades, monosyllabic word-recognition in quiet (WRQ) has been the default test of speech recognition in routine audiologic assessment. The continued use of WRQ scores is noteworthy in part because difficulties understanding speech in noise (SIN) is perhaps the most common complaint of individuals with hearing loss. The easiest way to integrate SIN measures into routine clinical practice would be for SIN to replace WRQ assessment as the primary test of speech perception. To facilitate this goal, we predicted classifications of WRQ scores from the QuickSIN signal to noise ratio (SNR) loss and hearing thresholds.
We examined data from 5808 patients who underwent audiometric assessment at the Stanford Ear Institute. All individuals completed pure-tone audiometry, and speech assessment consisting of monaural WRQ, and monaural QuickSIN. We then performed multiple-logistic regression to determine whether classification of WRQ scores could be predicted from pure-tone thresholds and QuickSIN SNR losses.
Many patients displayed significant challenges on the QuickSIN despite having excellent WRQ scores. Performance on both measures decreased with hearing loss. However, decrements in performance were observed with less hearing loss for the QuickSIN than for WRQ. Most important, we demonstrate that classification of good or excellent word-recognition scores in quiet can be predicted with high accuracy by the high-frequency pure-tone average and the QuickSIN SNR loss.
Taken together, these data suggest that SIN measures provide more information than WRQ. More important, the predictive power of our model suggests that SIN can replace WRQ in most instances, by providing guidelines as to when performance in quiet is likely to be excellent and does not need to be measured. Making this subtle, but profound shift to clinical practice would enable routine audiometric testing to be more sensitive to patient concerns, and may benefit both clinicians and researchers.
We examined data from 5808 patients who underwent audiometric assessment at the Stanford Ear Institute. All individuals completed pure-tone audiometry, and speech assessment consisting of monaural WRQ, and monaural QuickSIN. We then performed multiple-logistic regression to determine whether classification of WRQ scores could be predicted from pure-tone thresholds and QuickSIN SNR losses.
Many patients displayed significant challenges on the QuickSIN despite having excellent WRQ scores. Performance on both measures decreased with hearing loss. However, decrements in performance were observed with less hearing loss for the QuickSIN than for WRQ. Most important, we demonstrate that classification of good or excellent word-recognition scores in quiet can be predicted with high accuracy by the high-frequency pure-tone average and the QuickSIN SNR loss.
Taken together, these data suggest that SIN measures provide more information than WRQ. More important, the predictive power of our model suggests that SIN can replace WRQ in most instances, by providing guidelines as to when performance in quiet is likely to be excellent and does not need to be measured. Making this subtle, but profound shift to clinical practice would enable routine audiometric testing to be more sensitive to patient concerns, and may benefit both clinicians and researchers.
摘要：
目标：几十年来，安静中的单音节单词识别（WRQ）已成为常规听力学评估中语音识别的默认测试。WRQ评分的持续使用在某种程度上是值得注意的，因为难以理解噪声中的语音（SIN）可能是听力损失患者最常见的抱怨。将SIN措施纳入常规临床实践的最简单方法是SIN取代WRQ评估作为言语感知的主要测试。为了实现这一目标，我们根据QuickSIN信噪比(SNR)损失和听力阈值预测WRQ评分的分类.
方法：我们检查了在斯坦福耳科研究所接受听力测量评估的5808例患者的数据。所有的人都完成了纯音测听,和由单声道WRQ组成的语音评估，和单声道QuickSIN。然后，我们进行了多元逻辑回归，以确定是否可以从纯音阈值和QuickSINSNR损失预测WRQ分数的分类。
结果：尽管WRQ评分优异，但许多患者在QuickSIN上表现出显著的挑战。两种措施的性能均随听力损失而下降。然而,与WRQ相比，QuickSIN的听力损失较少，表现下降。最重要的是,我们证明，可以通过高频纯音平均值和QuickSINSNR损失来高精度地预测安静中良好或出色的单词识别分数的分类。
结论：综合来看，这些数据表明SIN测量比WRQ提供更多的信息.更重要的是,我们模型的预测能力表明，在大多数情况下，SIN可以取代WRQ，通过提供指南，说明何时安静的表现可能是优秀的，不需要测量。让这个微妙的，但是，向临床实践的深刻转变将使常规听力测试对患者的担忧更加敏感，并可能使临床医生和研究人员受益。
方法：我们检查了在斯坦福耳科研究所接受听力测量评估的5808例患者的数据。所有的人都完成了纯音测听,和由单声道WRQ组成的语音评估，和单声道QuickSIN。然后，我们进行了多元逻辑回归，以确定是否可以从纯音阈值和QuickSINSNR损失预测WRQ分数的分类。
结果：尽管WRQ评分优异，但许多患者在QuickSIN上表现出显著的挑战。两种措施的性能均随听力损失而下降。然而,与WRQ相比，QuickSIN的听力损失较少，表现下降。最重要的是,我们证明，可以通过高频纯音平均值和QuickSINSNR损失来高精度地预测安静中良好或出色的单词识别分数的分类。
结论：综合来看，这些数据表明SIN测量比WRQ提供更多的信息.更重要的是,我们模型的预测能力表明，在大多数情况下，SIN可以取代WRQ，通过提供指南，说明何时安静的表现可能是优秀的，不需要测量。让这个微妙的，但是，向临床实践的深刻转变将使常规听力测试对患者的担忧更加敏感，并可能使临床医生和研究人员受益。
