Multicenter Evaluation of BACT-Info. and an Infection Algorithm Using Urine Flow Cytometry among Clinically Diagnosed UTI Patients in Indonesia

Urinary tract infections (UTIs) are the most common infections in both outpatient and inpatient settings, contributing significantly to morbidity, reduced quality of life, and antimicrobial overuse. Although urine culture remains the diagnostic gold standard, it poses practical limitations in clinical workflows. Rapid diagnostic methods such as urine flow cytometry (UF) offer potential for timely, reliable UTI detection. We conducted a multicenter diagnostic study to evaluate the performance of BACT-Info. and UTI-Info. flags on the UF-5000/4000 system in detecting UTIs, using presumptive Gram staining and urine culture (>10 CFU/mL) as references. A total of 763 patients with suspected UTI were enrolled, and 721 patients--with uropathogenic bacteria and complete data--were included in the final analysis (384 with culture-confirmed UTI and 337 without UTI). The diagnostic value of nitrituria was highly specific, while leukocyte esterase was sensitive. For BACT-count and WBC-count of UF-5000/4000, the AUCs were 0.85 and 0.69, respectively. Using cutoffs of WBC >82.05/{micro}L or bacteria >975.4/{micro}L, the UTI-Info flag demonstrated 89% sensitivity, 54% specificity, 69% positive predictive value, and 82% negative predictive value. Positive and negative likelihood ratios were 1.93 and 0.20, respectively. The agreement between the BACT-Info. flag and Gram typing showed Kappa values of 0.716 for Gram-negative and 0.216 for Gram-positive bacteria when compared to culture, and 0.721 and 0.401, respectively, when compared to presumptive Gram staining. The UF-5000/4000 UTI-Info. and BACT-Info. flags show promise as a rapid UTI screening tool. The combination of these flags with urinalysis parameters, nitrite testing and leukocyte has potential to be developed into a diagnostic algorithm for early and sensitive UTI prediction. Such an approach may reduce unnecessary urine cultures and support timely, appropriate empiric antibiotic therapy. Establishing optimal cutoffs tailored to specific clinical settings is essential to enhance diagnostic accuracy and improve clinical utility.