ICU患者のリスク層別化における自動尿中酵母様細胞数（YLCC）の診断性能と臨床的有用性

To evaluate the diagnostic performance of automated urine yeast-like cell count (YLCC) as a rapid screening tool for identifying high-risk patients in the intensive care unit (ICU) and to establish an optimal cutoff value for clinical application.

This retrospective cohort study enrolled 317 adult ICU patients. YLCC was measured using the Sysmex UF-1000i automated urine analyzer, which provides real-time quantitative results without additional cost. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis. The association between YLCC and candiduria was evaluated, and multivariate logistic regression identified independent risk factors.

YLCC positivity was detected in 71.3% of patients, with a median time to positivity of only 5 days-approximately 12 days earlier than traditional candiduria diagnosis. YLCC showed strong correlation with positive urine Candida culture (OR=23.00, 95% CI: 3.12-169.48, p = 0.002). ROC analysis established an optimal YLCC cutoff of >1.35 cells/μL (AUC=0.71, sensitivity=82.0%, specificity=54.3%) for risk stratification. Patients with elevated YLCC (>1.35 cells/μL) had significantly higher mortality (25.2% vs. 5.8%, p < 0.001). Multivariate analysis confirmed YLCC as the strongest independent predictor (adjusted OR=4.09, 95% CI: 1.77-9.46, p = 0.001).

Automated YLCC measurement provides a rapid, cost-effective screening tool for early identification of high-risk ICU patients. The established cutoff of >1.35 cells/μL enables effective risk stratification using routine urinalysis, offering significant advantages over conventional culture-based methods in terms of turnaround time and clinical utility.