2016International Journal of AudiologyOpen access

Clinical validation of automated audiometry with continuous noise-monitoring in a clinically heterogeneous population outside a sound-treated environment

Christopher G. Brennan‐Jones, Robert H. Eikelboom, De Wet Swanepoel, Peter Friedland, Marcus D. Atlas

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Abstract

OBJECTIVE: Examine the accuracy of automated audiometry in a clinically heterogeneous population of adults using the KUDUwave automated audiometer. DESIGN: Prospective accuracy study. Manual audiometry was performed in a sound-treated room and automated audiometry was not conducted in a sound-treated environment. STUDY SAMPLE: 42 consecutively recruited participants from a tertiary otolaryngology department in Western Australia. RESULTS: Absolute mean differences ranged between 5.12-9.68 dB (air-conduction) and 8.26-15 dB (bone-conduction). A total of 86.5% of manual and automated 4FAs were within 10 dB (i.e. ±5 dB); 94.8% were within 15 dB. However, there were significant (p < 0.05) differences between automated and manual audiometry at 250, 500, 1000, and 2000 Hz (air-conduction) and 500 and 1000 Hz (bone-conduction). The effect of age (≥55 years) on accuracy (p = 0.014) was not significant on linear regression (p > 0.05; R(2) =( ) 0.11). The presence of a hearing loss (better ear ≥26 dB) did not significantly affect accuracy (p = 0.604; air-conduction), (p = 0.218; bone-conduction). CONCLUSIONS: This study provides clinical validation of automated audiometry using the KUDUwave in a clinically heterogeneous population, without the use of a sound-treated environment. Whilst threshold variations were statistically significant, future research is needed to ascertain the clinical significance of such variation.

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OBJECTIVE: Examine the accuracy of automated audiometry in a clinically heterogeneous population of adults using the KUDUwave automated audiometer. DESIGN: Prospective accuracy study. Manual audiometry was performed in a sound-treated room and automated audiometry was not conducted in a sound-treated environment. STUDY SAMPLE: 42 consecutively recruited participants from a tertiary otolaryngology department in Western Australia. RESULTS: Absolute mean differences ranged between 5.12-9.68 dB (air-conduction) and 8.26-15 dB (bone-conduction). A total of 86.5% of manual and automated 4FAs were within 10 dB (i.e. ±5 dB); 94.8% were within 15 dB. However, there were significant (p < 0.05) differences between automated and manual audiometry at 250, 500, 1000, and 2000 Hz (air-conduction) and 500 and 1000 Hz (bone-conduction). The effect of age (≥55 years) on accuracy (p = 0.014) was not significant on linear regression (p > 0.05; R(2) =( ) 0.11). The presence of a hearing loss (better ear ≥26 dB) did not significantly affect accuracy (p = 0.604; air-conduction), (p = 0.218; bone-conduction). CONCLUSIONS: This study provides clinical validation of automated audiometry using the KUDUwave in a clinically heterogeneous population, without the use of a sound-treated environment. Whilst threshold variations were statistically significant, future research is needed to ascertain the clinical significance of such variation.

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Available abstract

OBJECTIVE: Examine the accuracy of automated audiometry in a clinically heterogeneous population of adults using the KUDUwave automated audiometer. DESIGN: Prospective accuracy study. Manual audiometry was performed in a sound-treated room and automated audiometry was not conducted in a sound-treated environment. STUDY SAMPLE: 42 consecutively recruited participants from a tertiary otolaryngology department in Western Australia. RESULTS: Absolute mean differences ranged between 5.12-9.68 dB (air-conduction) and 8.26-15 dB (bone-conduction). A total of 86.5% of manual and automated 4FAs were within 10 dB (i.e. ±5 dB); 94.8% were within 15 dB. However, there were significant (p < 0.05) differences between automated and manual audiometry at 250, 500, 1000, and 2000 Hz (air-conduction) and 500 and 1000 Hz (bone-conduction). The effect of age (≥55 years) on accuracy (p = 0.014) was not significant on linear regression (p > 0.05; R(2) =( ) 0.11). The presence of a hearing loss (better ear ≥26 dB) did not significantly affect accuracy (p = 0.604; air-conduction), (p = 0.218; bone-conduction). CONCLUSIONS: This study provides clinical validation of automated audiometry using the KUDUwave in a clinically heterogeneous population, without the use of a sound-treated environment. Whilst threshold variations were statistically significant, future research is needed to ascertain the clinical significance of such variation.

Key concepts: Audiology, Audiometry, Noise (video), Sound (geography), Population, Medicine, Computer science, Hearing loss

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