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Eignung der Bestimmung prozentualer Hörverluste zum Monitoring der Cochlea Implantat Rehabilitation
BACKGROUND: Calculation of percentage hearing loss (pHV) from the pure-tune audiogram according to Röser in 1973 or from the speech audiogram according to Boenninghaus and Röser in 1973 is a method still applied for quantitative assessment of hearing. However, this is not common for the evaluation o...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Medizin
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894973/ https://www.ncbi.nlm.nih.gov/pubmed/36592183 http://dx.doi.org/10.1007/s00106-022-01257-8 |
Sumario: | BACKGROUND: Calculation of percentage hearing loss (pHV) from the pure-tune audiogram according to Röser in 1973 or from the speech audiogram according to Boenninghaus and Röser in 1973 is a method still applied for quantitative assessment of hearing. However, this is not common for the evaluation of postoperative results of implantable hearing systems. During the regular work-up after cochlear implantation (CI) in Germany, all necessary parameters are available for calculation of pHV either from categorical loudness scaling (pHV(KLS)) or speech-recognition threshold (pHV(FB)). OBJECTIVE: The parameters pHV(KLS) and pHV(FB) are introduced and calculated from data available from clinical routine. Their potential applicability for assessment of the result of CI is evaluated. MATERIALS AND METHODS: This study comprises retrospective chart review of audiological parameters from 66 CI procedures in one tertiary referral center. pHV(KLS) was calculated from the equal loudness curve 5 CU, pHV(FB) from the Freiburg speech test in free field. RESULTS: While pHV(KLS) shows small variation, the variation in pHV(FB) is initially larger but decreases over time. Furthermore, starting from initial fitting, the mean pHV shows convergence over time. The difference between pHV(FB) and pHV(KLS) is positive and statistically significant. CONCLUSION: It is possible to calculate pHV(KLS) and pHV(FB) from routine data. A correlation of the difference between pHV(FB) and pHV(KLS) with successful CI performance seems plausible. |
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