ArticleJournal of fungi (Basel, Switzerland)2025
Advancing Dermatomycosis Diagnosis: Evaluating a Microarray-Based Platform for Rapid and Accurate Fungal Detection-A Pilot Study.
Article in Journal of fungi (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Dermatomycosis, including the most prevalent onychomycosis, significantly impacts patients' quality of life due to its chronic nature and high recurrence rate. Conventional diagnostic methods are often limited by low sensitivity and specificity and prolonged turnaround times. This study evaluates the EUROArray Dermatomycosis Platform, a microarray-based molecular assay, for its performance in identifying fungi causing dermatomycosis. Forty reference fungal strains, covering on-panel and off-panel species, and 120 clinical samples from patients with suspected dermatomycosis were analyzed. The platform's accuracy was compared to microscopy and/or culture as the diagnostic standard. The assay demonstrated 100% analytical sensitivity and 97.1% analytical specificity, correctly identifying 33 of 34 fungal species while misclassifying one. In clinical samples, the assay showed good sensitivity (78.6%) and high specificity (91.7%), detecting additional positive cases missed by culture, which highlights the assay's ability to identify non-viable fungi and low fungal loads. The assay achieved a positive predictive value of 75.9% and a negative predictive value of 92.8%, reinforcing its diagnostic reliability. Despite some discordances, the assay provides rapid results and broad-spectrum fungal detection, positioning it as a valuable complement to conventional diagnostics. Future improvements, including expanding the identification panel and optimizing sample handling, could further enhance its clinical utility.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.