Evaluation of the DendrisKIT®DP for the Diagnosis of Superficial Fungal Infections

TL;DR

A new molecular tool called DendrisKIT®DP was tested for diagnosing skin, nail, and hair fungal infections, offering faster and accurate results compared to traditional methods.

Contribution

The DendrisKIT®DP combines pan-fungal PCR, DNA chip, and machine learning for rapid and simultaneous detection of multiple fungal species.

Findings

The DendrisKIT®DP achieved 83.9% sensitivity and 88.9% specificity in diagnosing fungal infections.

Results were obtained faster than conventional culture methods, improving patient management efficiency.

The tool's performance is expected to improve with ongoing enhancement of its identification algorithm.

Abstract

Conventional diagnosis of fungal infections of the skin, nail, and hair requires both expertise in mycology and prolonged cultures. We evaluated a new molecular tool based on an innovative technology, the DendrisKIT®DP, combining a pan-fungal PCR, a DNA chip and a decision algorithm using machine learning, for the diagnosis of superficial fungal infections directly from clinical samples. It enables the simultaneous detection of Candida albicans and twelve dermatophytes, providing faster results than conventional techniques. Among 85 clinical samples (50 skin scrapings, 29 nail specimens, and 6 hair specimens) routinely tested by microscopic examination and cultures that were retrospectively tested by the DendrisKIT®DP, we found a sensitivity of 83.9% and a specificity of 88.9%. This performance appeared satisfactory compared to microscopy and culture, and results were achieved much faster than with cultures, saving time for patient management. Moreover, thanks to the continuous improvement in the identification algorithm due to enriching the database, its performance is likely to be further enhanced.

Figures