Frontiers in Microbiology (Mar 2023)

A scoring system based on novel biomarkers and clinical risk factors to predict invasive candidiasis in immunocompetent critically ill patients

  • Wen Li,
  • Wen Li,
  • Wen Li,
  • Wen Li,
  • Wen Li,
  • Gang Chen,
  • Gang Chen,
  • Gang Chen,
  • Gang Chen,
  • Gang Chen,
  • Fengyu Lin,
  • Fengyu Lin,
  • Fengyu Lin,
  • Fengyu Lin,
  • Fengyu Lin,
  • Hang Yang,
  • Hang Yang,
  • Hang Yang,
  • Hang Yang,
  • Hang Yang,
  • Yanhui Cui,
  • Yanhui Cui,
  • Yanhui Cui,
  • Yanhui Cui,
  • Yanhui Cui,
  • Rongli Lu,
  • Rongli Lu,
  • Rongli Lu,
  • Rongli Lu,
  • Rongli Lu,
  • Chao Song,
  • Haitao Li,
  • Yi Li,
  • Yi Li,
  • Yi Li,
  • Yi Li,
  • Yi Li,
  • Pinhua Pan,
  • Pinhua Pan,
  • Pinhua Pan,
  • Pinhua Pan,
  • Pinhua Pan

DOI
https://doi.org/10.3389/fmicb.2023.1097574
Journal volume & issue
Vol. 14

Abstract

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BackgroundDelayed diagnosis further increases the mortality of invasive candidiasis (IC) in intensive care unit (ICU) patients. This study aimed to develop and validate a score based on novel serological biomarkers and clinical risk factors for predicting IC in immunocompetent ICU patients.MethodsWe retrospectively collected clinical data and novel serological markers on admission to ICU. Multivariate logistic regression was used to identify the risk factors associated with IC, which were adopted to establish a scoring system.ResultsPatients with IC had a higher C-reactive protein-to-albumin ratio (CAR) and neutrophil-to-lymphocyte ratio (NLR) and lower prognostic nutritional index than those without IC. The NLR, CAR, sepsis, total parenteral nutrition, 1,3-β-D-glucan (BDG)-positivity, and Sequential Organ Failure Assessment score were identified as independent risk factors for IC by multivariate logistic regression analysis and entered into the final scoring system. The area under receiver operating characteristic curve of the score were 0.883 and 0.892, respectively, in the development and validation cohort, higher than Candida score (0.883 vs.0.730, p < 0.001).ConclusionWe established a parsimonious score based on NLR, CAR, BDG-positivity, and clinical risk factors, which can accurately identify IC in ICU patients to give treatment on time and reduce mortality.

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