# Diagnostic Performance of a PCR‐Based Approach for the Diagnosis of Dermatomycosis

## TL;DR

A PCR-based method for diagnosing skin fungal infections was found to be highly accurate and efficient, reducing reliance on traditional methods.

## Contribution

The study introduces a PCR-based workflow that enables rapid, species-level identification of dermatophytes in routine diagnostics.

## Key findings

- The PCR-based workflow achieved 98.5% diagnostic accuracy and 94.6% sensitivity for dermatophyte detection.
- Trichophyton rubrum was the most commonly identified species, followed by T. mentagrophytes-interdigitale complex.
- The workflow reduced the need for microscopy and culture while enabling reliable species identification.

## Abstract

Dermatomycoses, superficial fungal infections of the skin, hair and nails, are among the most common dermatological conditions worldwide. Rapid and accurate diagnosis is essential, particularly in light of emerging antifungal resistance. Conventional diagnostic methods are limited by long turnaround times and lack of species‐level specificity; hence the use of modern DNA‐based tools should be expedient.

The aim of this study was to evaluate the diagnostic performance of a pan‐dermatophyte PCR‐based workflow for dermatomycosis in routine diagnostics and to describe the epidemiological landscape in Tyrol, Austria.

In this retrospective study, 4483 patient specimens (skin, hair and nails) submitted to the Institute of Hygiene and Medical Microbiology, Medical University of Innsbruck, between 2018 and 2024 were analysed. The workflow included initial pan‐dermatophyte PCR, followed by microscopy and fungal culture for PCR‐negative or inconclusive cases. Species identification was performed by Matrix‐assisted Laser‐Desorption Ionisation Time‐of‐Flight mass spectrometry or, if unsuccessful, by sequencing.

Of all specimens, 1170 (26.1%) were PCR‐positive, predominantly with Trichophyton rubrum (76.4%), or members of the T. mentagrophytes‐interdigitale complex (15.4%). In PCR‐negative but microscopy‐positive samples, 67 dermatophytes were identified by culture. The PCR‐based workflow demonstrated a sensitivity of 94.6%, a negative predictive value of 98.0%, and an overall diagnostic accuracy of 98.5%. Among 335 non‐dermatophyte fungi, Aspergillus spp. were most frequent.

The proposed workflow demonstrated high sensitivity and accuracy, supporting its suitability for routine diagnostics. It reduced the need for microscopy and culture while enabling reliable species‐level identification, facilitated epidemiological surveillance, revealing a predominance of
T. rubrum
.