Development and validation of a risk score for predicting invasive fungal infectious in an intensive care unit

Area of Science:

• Critical Care Medicine
• Infectious Diseases
• Epidemiology

Background:

• Delayed antifungal therapy in intensive care units (ICUs) leads to increased patient morbidity and mortality.
• Accurate risk stratification is crucial for early detection and management of invasive fungal infections (IFI).

Purpose of the Study:

• To develop and validate a predictive risk score system for identifying patients at high risk of developing invasive fungal infections (IFI) in the ICU.

Main Methods:

• Retrospective analysis of 1812 ICU patients with a minimum stay of 4 days.
• Univariate and multivariable logistic regression identified key risk factors for ICU-IFI.
• A risk score was derived and validated in an independent patient cohort.

Main Results:

• Seven significant predictors for ICU-IFI were identified: diabetes mellitus, gastrointestinal surgery, hematological malignancies, prolonged mechanical ventilation, central venous catheter, total parenteral nutrition, and extended broad-spectrum antibiotic use.
• The risk score demonstrated good predictive performance with an area under the receiver operating characteristic curve of 0.807.
• Risk groups showed distinct ICU-IFI percentages: low (4.2-5.2%), intermediate (30.1-31.6%), and high (63.2-66.7%).

Conclusions:

• A novel, validated risk score effectively predicts invasive fungal infections in ICU patients.
• This tool can aid clinicians in early identification of high-risk individuals, potentially improving outcomes and survival rates.