Abstract

The urine culture is the “gold standard” for the diagnosis of urinary tract infections (UTI) but constitutes a significant workload in the routine clinical laboratory. Due to the high percentage of negative results, there is a need for an efficient screening method, with a high negative predictive value (NPV) that could reduce the number of unnecessary culture tests. With the purpose of improving the efficiency of laboratory work, several methods for screening out the culture-negative samples have been developed, but none of them has shown adequate sensitivity (SE) and high NPV. Many authors show data about the efficacy of flow cytometry in the routine clinical laboratory. The aim of this article is to review and discuss the current literature on the feasibility of urine flow cytometry (UFC) and its utility as an alternative analytical technique in urinalysis.

Highlights

  • Urinary tract infections (UTIs) are among the most common infections in both hospitalized patients and outpatients [1,2,3,4], and the health cost they cause is considerable

  • Citations were limited to studies conducted in humans and using the UF1000i (Sysmex) analyzer for UTI screening and the urine culture as the reference standard

  • It is important to remember that the number of bacteria deemed relevant for the diagnosis of UTI depends on various factors

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Summary

Introduction

Urinary tract infections (UTIs) are among the most common infections in both hospitalized patients and outpatients [1,2,3,4], and the health cost they cause is considerable. In the USA, it is responsible for more than 7 million medical visits annually, and the most recent medical literature indicates a global prevalence of 0.7% of community-acquired UTI (19.6% in Europe, 12.9% in the USA, and 24% in developing countries) [8]. E. coli more usually causes lower community-acquired UTI [9, 10]. Up to 15% of antibiotics prescribed in the community are due to these infections, with an annual cost of approximately 1.6 billion US dollars [11]. Taking these data into account, there is an enhanced risk of antibiotic resistance [12]

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