title: Predicting speech discrimination from the audiometric thresholds.
abstract: To develop a method for predicting a speech discrimination score (SDS) from audiometric thresholds (SRT and pure-tones) three prediction systems were investigated: a stepwise multiple regression procedure, smear-and-sweep analysis and a clinical classification of the audiometric configuration. Test results of 529 ears with sensorineural hearing loss were taken from copies of audiograms obtained as part of a normal audiology clinic caseload. The three prediction systems had similar predictive ability and yielded slightly higher correlations with the SDS than those in previously reported studies. Squared correlations in this study ranged from 0.58 to 0.60. Smear-and-sweep analysis yielded the best results; however, its complexity makes clinical application difficult at this time. The stepwise multiple regression models or the clinical classification system provided more clinically useful methods for predicting the SDS. An over-riding influence of increasing variability in the SDS with increased hearing loss was observed and significantly limited the accuracy of prediction for the moderate-to-severe hearing loss groups. Small changes in the slope of the audiometric configuration were noted to affect the SDS only when the degree of hearing loss was slight.
mesh_terms: D001299:Audiometry; D001301:Audiometry, Pure-Tone; D001309:Auditory Threshold; D006319:Hearing Loss, Sensorineural / Q000175:diagnosis*; D006801:Humans; D012044:Regression Analysis; D013063:Speech Discrimination Tests; D013067:Speech Perception; D013069:Speech Reception Threshold Test