Nilai Diagnostik Leukosituria dan Bakteriuria dengan Automated Urine Flow Cytometry Analyzer pada Pasien Suspek Infeksi Saluran Kemih di RSUP H Adam Malik Medan

Abstract

Background : Urinary tract infection (UTI) is one of the most prevalent diseases in the world that includes infections of the urethra (urethritis), bladder (cystitis), ureters (ureteritis), and kidneys (pyelonephritis) where the prevalence and severity of UTI depends on the demographic characteristics, clinical features, and medical history of the individual. Urine analysis, urine microscopic examination, urine culture are standard laboratory protocols to approach the diagnosis of UTI. Urine culture is the gold standard method of UTI diagnosis, but the time taken to obtain results is usually 48-72 hours so other tests are needed that are reliable in the rapid detection of a UTI. Flow cytometry is a laser-based technology that generates scattered fluorescent light signals, allowing rapid analysis of the size and granularity of single particles or cells. Automated urine flow cytometry analyser has the advantages of being standardised, cheaper, and obtaining results faster than urine culture. This study aims to analyse the association of leukocyturia and bacteriuria in automated urine flow cytometry analyzer compared to urine culture results. Subjects and Methods : This study is a cross-sectional design study with consecutive sampling. A total of 58 people with suspected Urinary Tract Infection at H.Adam Malik Hospital Medan. Urine samples were taken for urinalysis and urine culture. Data were analysed by diagnostic test analysis using urine leukocytes and urine bacteria variables compared by urine culture gold standard examination. Data were analysed using Receiver Operating Characteristic (ROC) curves and assessment of diagnostic test capability was performed by calculating the area under the curve (AUC). Results : Of the 58 research subjects, most of the research subjects had an average age of 55 years, most of them were male (65.5%). In the examination of bacteriuria, there was an AUC area of 86%, with a sensitivity value of 80%, specificity of 78.3%, positive presumptive value of 84.8%, negative presumptive value of 72% and accuracy of bacteriuria examination of 79.3%. In the examination of leukocyturia, there was an AUC area of 66%, with a sensitivity value of 71.4%, specificity of 65.2%, positive presumptive value of 75.8%, negative presumptive value of 60% and accuracy of leukocyturia examination of 68.97%. Conclusion : Examination of leukocyturia and bacteriuria with automated urine flow cytometry analyzer statistically has a good diagnostic value in rapid detection of the possibility of a UTI.