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An evidenced-based diagnostic tool for superior semicircular canal dehiscence syndrome

PURPOSE: To construct a symptoms-based prediction tool to assess the likelihood of superior canal dehiscence (SSCD) on high-resolution CT. MATERIALS AND METHODS: Mathematical modeling was employed to predict radiologic evidence of SSCD at a tertiary neurotology referral center. RESULTS: A total of 1...

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Detalles Bibliográficos
Autores principales: Fritz, Christian G., Casale, Garrett G., Kana, Lulia A., Hong, Robert S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Chinese PLA General Hospital 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593562/
https://www.ncbi.nlm.nih.gov/pubmed/37877067
http://dx.doi.org/10.1016/j.joto.2023.09.006
Descripción
Sumario:PURPOSE: To construct a symptoms-based prediction tool to assess the likelihood of superior canal dehiscence (SSCD) on high-resolution CT. MATERIALS AND METHODS: Mathematical modeling was employed to predict radiologic evidence of SSCD at a tertiary neurotology referral center. RESULTS: A total of 168 patients were included, of which 118 had imaging-confirmed SSCD. On univariate analysis significant predictors of SSCD presence were: sound/pressure-induced vertigo (p = 0.006), disequilibrium (p = 0.008), hyperacusis (p = 0.008), and autophony (p = 0.034). Multivariate analysis enabled a 14-point symptom-weighted tool to be developed, wherein a score of ≥6 raised the suspicion of SSCD (≥70% likelihood of being present), R(2) = 0.853. CONCLUSIONS: The likelihood of SSCD on CT scan can be determined with a high degree of certainty based on symptoms recorded at presentation. Using the evidenced-based diagnostic tool validated herein, a score ≥6 with any symptom combination justifies ordering a CT scan.