Premium
Comparison of diagnostic methods for onychomycosis, and proposal of a diagnostic algorithm
Author(s) -
Jung M. Y.,
Shim J. H.,
Lee J. H.,
Lee J. H.,
Yang J. M.,
Lee D.Y.,
Jang K.T.,
Lee N. Y.,
Lee J.H.,
Park J.H.,
Park K. K.
Publication year - 2015
Publication title -
clinical and experimental dermatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 78
eISSN - 1365-2230
pISSN - 0307-6938
DOI - 10.1111/ced.12593
Subject(s) - medicine , algorithm , diagnostic test , dermatology , computer science , pediatrics
Summary Background Traditionally, the gold standard for diagnosis of onychomycosis has been the combination of direct microscopy with potassium hydroxide ( KOH ) staining and fungal culture. However, several studies have suggested that periodic‐acid–Schiff ( PAS ) staining of nail‐plate clippings may be a very sensitive method for the diagnosis of onychomycosis. Aim To compare the sensitivities of direct microscopy with KOH , fungal culture and PAS staining of nail‐plate clippings, and to define an efficient, high‐yield and cost‐effective diagnostic strategy for the diagnosis of onychomycosis in the clinical setting. Methods We evaluated a total of 493 patients with clinically suspected onychomycosis. Group A comprised 400 patient samples, evaluated using fungal culture and PAS stain, while group B comprised 93 patient samples evaluated using KOH , fungal culture and PAS . Diagnosis of onychomycosis was defined as clinical morphology plus at least one positive test result. Results In group A , sensitivities of fungal culture and PAS were 49.5% and 93.1% ( P < 0.005), respectively. In group B, the most sensitive single test was PAS (88.2%) followed by KOH (55.9%) and fungal culture (29.4%). The combination of fungal culture and PAS (94.1%) was significantly ( P < 0.001) more sensitive than that of KOH and culture (72.1%). Conclusion PAS staining of nail clippings is much more sensitive than KOH and fungal culture for the diagnosis of onychomycosis. Based on our results, we propose a diagnostic algorithm for onychomycosis that takes into consideration the sensitivity, cost‐effectiveness and necessary time for each test.