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Overview of Risk Factors and Diagnosis of Invasive Candidiasis

Valentina Daniela Sisu1, Anda Băicuș1

  • 1Faculty of Medicine, University of Medicine and Pharmacy, Carol Davila, 020021 Bucharest, Romania.

Journal of Fungi (Basel, Switzerland)
|June 25, 2026
PubMed

Insights

Early diagnosis of invasive candidiasis (IC) is crucial for timely antifungal treatment. This review covers IC clinical syndromes, diagnostic methods, risk factors, and emerging biomarkers for improved detection.

Area of Science:

  • Medical Mycology
  • Infectious Diseases
  • Clinical Microbiology

Background:

  • Invasive candidiasis (IC) is a growing healthcare concern due to increasing risk factors and Candida species' ability to invade tissues and survive on surfaces.
  • Prompt diagnosis of IC is essential to initiate antifungal therapy and improve patient outcomes.
  • The spread of IC is influenced by Candida's transition from colonization to invasion and its persistence on abiotic surfaces.

Purpose of the Study:

  • To review clinical syndromes associated with invasive candidiasis.
  • To discuss current diagnostic methods for invasive candidiasis.
  • To explore risk factors and novel biomarkers for early IC detection.

Main Methods:

  • Narrative review of clinical syndromes and diagnostic approaches for invasive candidiasis.
  • Assessment of risk factors associated with invasive candidiasis.
  • Exploration of research-stage biomarkers for predicting or identifying IC.

Main Results:

  • Current diagnostic methods and clinical syndromes of invasive candidiasis are detailed.
  • Recent updates on risk factor assessment for IC are provided.
  • Emerging biomarkers show potential for improved prediction and earlier identification of IC, though results are partial.

Conclusions:

  • Timely diagnosis and treatment of invasive candidiasis are critical.
  • Understanding risk factors and utilizing advanced diagnostic tools, including biomarkers, are key to combating IC.
  • Continued research into novel biomarkers is necessary for more accurate and earlier identification of invasive candidiasis.
Keywords:
candidemiadiagnostic algorithmintra-abdominal candidiasisprediction modelsrisk factors

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