The Diagnostic Performance of Urine Flow Cytometer UF1000i for Urinary Tract Infections.

Abstract

Urinary tract infections (UTIs) are one of the most common infectious diseases in clinic. Urine flow cytometry is receiving more and more attention due to its rapid forecast of UTIs. The Urine Flow Cytometer UF1000i has a series of software programs to quantify bacteria (BACT) and white blood cells (WBC), and describe the scatter diagram of bacteria. The UTIs were predicted based on the cutoff values with the Receiver Operating Characteristic (ROC) curves of BACT and WBC counts. To evaluate the diagnostic performance of UF1000i for UTIs, the sensitivity and specificity of 889 urine samples were determined in comparison to the results of urine culture. Meanwhile the bacterial morphology indication of the UF1000i was evaluated in order to help doctors choose antibiotics. The angle of the scatter cloud with the x-axis was used to classify the infected bacteria as bacilli (< 30°) or cocci (≥ 30°). The best cutoff value of BACT counts for predicting UTIs was 119 per µL, and the sensitivity and specificity were 95.5% and 88.7%, respectively. While the best cutoff value of WBC counts was 81.5 per µL, and the sensitivity and specificity were 77.6% and 76.7%, respectively. In addition, the best cutoff values for females were 583 BACT per µL and 137.5 WBC per µL. They were much higher than for males (118 BACT per µL and 91 WBC per µL). The coincidence of the bacterial morphology information between the UF1000i software indication and the bacterial actual morphology identified by urine culture was 83% (bacilli) and 68% (cocci), respectively. Data demonstrated that the performance of BACT counts for UTIs is superior to WBC counts. In addition, the bacterial morphology could preliminarily be predicated by the scatter diagram. Since the urine flow cytometer UF1000i can provide the data of both BACT counts and the scatter diagram, the urine flow cytometry was regarded as a suitable method for screening UTIs. Moreover, it would be better to take gender into consideration when setting the best cutoff value for diagnosis of UTIs in clinic.