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Cochlear Pathology in Presbycusis

Schuknecht, Harold F., Gacek, Mark R.·1993·Annals of Otology, Rhinology & Laryngology

Abstract

A survey of the temporal bone collection at the Massachusetts Eye and Ear Infirmary reveals 21 cases that meet the criterion for the clinical diagnosis of presbycusis. It is evident that the previously advanced concept of four predominant pathologic types of presbycusis is valid, these being sensory, neural, strial, and cochlear conductive. An abrupt high-tone loss signals sensory presbycusis, a flat threshold pattern is indicative of strial presbycusis, and loss of word discrimination is characteristic of neural presbycusis. When the increments of threshold loss present a gradually decreasing linear distribution pattern on the audiometric scale and have no pathologic correlate, it is speculated that the hearing loss is caused by alterations in the physical characteristics of the cochlear duct, and the loss is identified as cochlear conductive presbycusis. It is clear that many individual cases do not separate into a specific type but have mixtures of these pathologic types and are termed mixed presbycusis. About 25% of all cases of presbycusis show none of the above characteristics and are classified as indeterminate presbycusis.

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Metadata

Authors
Schuknecht, H. F., & Gacek, M. R.
Venue
Annals of Otology, Rhinology & Laryngology
Published
1993-01
Volume
102
Issue
1_suppl
Pages
1-16
ISSN
  • 0003-4894 (ISSN-L)
  • 1943-572X
OpenAlex
W2268695670
Cited by
873
References
0
FWCI
2.67
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Cochlear Pathology in Presbycusis. https://app.cochat.ai/papers/10.1177/00034894931020s101
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Schuknecht, H. F., & Gacek, M. R. (1993). Cochlear Pathology in Presbycusis. Annals of Otology, Rhinology & Laryngology. https://doi.org/10.1177/00034894931020s101

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.