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Objectives
Measures of speech-in-noise, such as the QuickSIN, are increasingly common tests of speech perception in audiologic practice. However, the effect of vestibular schwannoma (VS) on speech-in-noise abilities is unclear. Here, we compare the predictive ability of interaural QuickSIN asymmetry for detecting VS against other measures of audiol...
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Context 1
... analyses suggests that QuickSIN SNR asymmetry is more sensitive and specific at detecting VS than other measures of audiometric asymmetry. Table 4 shows the sensitivity and specificity at different asymmetry cutpoints for PTA, WRQ scores, and QuickSIN SNR loss. In general, specificity of WRQ and QuickSIN SNR loss cutpoints were higher than PTA for a given degree of sensitivity. ...Context 2
... QuickSIN SNR loss asymmetry and PTA asymmetry were significantly predictive of VS (p < 0.001 and p = 0.025, respectively), while WRQ asymmetry was not (p = 0.064). QuickSIN SNR loss asymmetry had a higher odds ratio than PTA asymmetry (1.232 versus 1.039) with no overlap in the 95% confidence intervals (Table 4). In contrast, the 95% confidence intervals for PTA asymmetry and WRQ asymmetry overlapped with a minimal difference in the odds ratio (1.039 versus 1.029). ...Citations
Objectives
Self-assessment of perceived communication difficulty has been used in clinical and research practices for decades. Such questionnaires routinely assess the perceived ability of an individual to understand speech, particularly in background noise. Despite the emphasis on perceived performance in noise, speech recognition in routine audiologic practice is measured by word recognition in quiet (WRQ). Moreover, surprisingly little data exist that compare speech understanding in noise (SIN) abilities to perceived communication difficulty. Here, we address these issues by examining audiometric thresholds, WRQ scores, QuickSIN signal to noise ratio (SNR) loss, and perceived auditory disability as measured by the five questions on the Speech Spatial Questionnaire-12 (SSQ12) devoted to speech understanding (SSQ12-Speech5).
Design
We examined data from 1633 patients who underwent audiometric assessment at the Stanford Ear Institute. All individuals completed the SSQ12 questionnaire, pure-tone audiometry, and speech assessment consisting of ear-specific WRQ, and ear-specific QuickSIN. Only individuals with hearing threshold asymmetries ≤10 dB HL in their high-frequency pure-tone average (HFPTA) were included. Our primary objectives were to (1) examine the relationship between audiometric variables and the SSQ12-Speech5 scores, (2) determine the amount of variance in the SSQ12-Speech5 scores which could be predicted from audiometric variables, and (3) predict which patients were likely to report greater perceived auditory disability according to the SSQ12-Speech5.
Results
Performance on the SSQ12-Speech5 indicated greater perceived auditory disability with more severe degrees of hearing loss and greater QuickSIN SNR loss. Degree of hearing loss and QuickSIN SNR loss were found to account for modest but significant variance in SSQ12-Speech5 scores after accounting for age. In contrast, WRQ scores did not significantly contribute to the predictive power of the model. Degree of hearing loss and QuickSIN SNR loss were also found to have moderate diagnostic accuracy for determining which patients were likely to report SSQ12-Speech5 scores indicating greater perceived auditory disability.
Conclusions
Taken together, these data indicate that audiometric factors including degree of hearing loss (i.e., HFPTA) and QuickSIN SNR loss are predictive of SSQ12-Speech5 scores, though notable variance remains unaccounted for after considering these factors. HFPTA and QuickSIN SNR loss—but not WRQ scores—accounted for a significant amount of variance in SSQ12-Speech5 scores and were largely effective at predicting which patients are likely to report greater perceived auditory disability on the SSQ12-Speech5. This provides further evidence for the notion that speech-in-noise measures have greater clinical utility than WRQ in most instances as they relate more closely to measures of perceived auditory disability.
Objectives
Understanding speech in noise (SIN) is the dominant complaint of individuals with hearing loss. For decades, the default test of speech perception in routine audiologic assessment has been monosyllabic word recognition in quiet (WRQ), which does not directly address patient concerns, leading some to advocate that measures of SIN should be integrated into routine practice. However, very little is known with regard to how SIN abilities are affected by different types of hearing loss. Here, we examine performance on clinical measures of WRQ and SIN in a large patient base consisting of a variety of hearing loss types, including conductive (CHL), mixed (MHL), and sensorineural (SNHL) losses.
Design
In a retrospective study, we examined data from 5593 patients (51% female) who underwent audiometric assessment at the Stanford Ear Institute. All individuals completed pure-tone audiometry, and speech perception testing of monaural WRQ, and monaural QuickSIN. Patient ages ranged from 18 to 104 years (average = 57). The average age in years for the different classifications of hearing loss was 51.1 (NH), 48.5 (CHL), 64.2 (MHL), and 68.5 (SNHL), respectively. Generalized linear mixed-effect models and quartile regression were used to determine the relationship between hearing loss type and severity for the different speech-recognition outcome measures.
Results
Patients with CHL had similar performance to patients with normal hearing on both WRQ and QuickSIN, regardless of the hearing loss severity. In patients with MHL or SNHL, WRQ scores remained largely excellent with increasing hearing loss until the loss was moderately severe or worse. In contrast, QuickSIN signal to noise ratio (SNR) losses showed an orderly systematic decrease as the degree of hearing loss became more severe. This effect scaled with the data, with threshold-QuickSIN relationships absent for CHL, and becoming increasingly stronger for MHL and strongest in patients with SNHL. However, the variability in these data suggests that only 57% of the variance in WRQ scores, and 50% of the variance in QuickSIN SNR losses, could be accounted for by the audiometric thresholds. Patients who would not be differentiated by WRQ scores are shown to be potentially differentiable by SIN scores.
Conclusions
In this data set, conductive hearing loss had little effect on WRQ scores or QuickSIN SNR losses. However, for patients with MHL or SNHL, speech perception abilities decreased as the severity of the hearing loss increased. In these data, QuickSIN SNR losses showed deficits in performance with degrees of hearing loss that yielded largely excellent WRQ scores. However, the considerable variability in the data suggests that even after classifying patients according to their type of hearing loss, hearing thresholds only account for a portion of the variance in speech perception abilities, particularly in noise. These results are consistent with the idea that variables such as cochlear health and aging add explanatory power over audibility alone.
Objectives
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.
Design
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.
Results
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.
Conclusions
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.
