Literature DB >> 29223137

Sysmex UF-1000i flow cytometer to screen urinary tract infections: the URISCAM multicentre study.

O Herráez1, M A Asencio1, R Carranza1, M M Jarabo1, M Huertas1, O Redondo1, A Arias-Arias1, S Jiménez-Álvarez2, S Solís3, P Zamarrón4, M S Illescas5, M A Galán6.   

Abstract

The new Sysmex UF-1000i analyzer - which incorporates bacteria morphology distinction - allows to automatically screen samples to be cultured at microbiology laboratories. We have evaluated the feasibility and accuracy of Sysmex UF-1000i to screen urinary tract infections (UTIs). A total amount of 2468 urine samples from six Spanish hospitals were analysed. Demographic and clinical data such as age, gender, source and sample type, preserving conditions, cytometer parameters (bacteria, leucocytes and bacteria morphology) as well as urine culture results (gold standard) were recorded. After applying data mining techniques, the variables of age, bacteria count and rod morphology were defined as predictive variables of UTIs. By using the UF-1000i in combination with a predictive algorithm of three decision rules, we could identify 94·9 and 47·4% positive and negative urine samples, respectively, with a negative predictive value of 97 and only 1·17% diagnostic error. This error was reduced down to 0·4% when contaminated samples were excluded. Our results show that flow cytometry parameters together with age, by means of a predictive algorithm model, can be used to screen UTIs. Its implementation would avoid culturing 38% of urine samples, and therefore, would reduce time to diagnosis with a discrete false negative ratio. SIGNIFICANCE AND IMPACT OF THE STUDY: Fluorescent flow cytometry performance has recently spread for urine screening. However, controversy about cytometer results can be drawn from medical literature. This study shows the diagnosis accuracy of Sysmex UF-1000i analyzer by means of a group of decision rules encompassing both demographic variables (age) and cytometer parameters (bacteria, leucocytes and bacteria morphology). After applying the predictive algorithm, the UF-1000i could optimally identify 95% urinary tract infections with high negative predictive value and low diagnostic error. Implementation of UF-1000i would avoid culturing almost 38% of urine samples, thus reducing time to diagnosis, unnecessary antibiotic treatments and consequently improving cost-effectiveness.
© 2017 The Society for Applied Microbiology.

Entities:  

Keywords:  bacteriuria; flow cytometer; screening; urinary tract infections; urine culture

Mesh:

Year:  2018        PMID: 29223137     DOI: 10.1111/lam.12832

Source DB:  PubMed          Journal:  Lett Appl Microbiol        ISSN: 0266-8254            Impact factor:   2.858


  5 in total

Review 1.  Role of Automated Urine Flow Cytometry for the Diagnosis of Urinary Tract Infection in Children.

Authors:  Om P Mishra; Rajniti Prasad
Journal:  Indian J Pediatr       Date:  2018-08-10       Impact factor: 1.967

2.  Coherent fluctuation nephelometry as a promising method for diagnosis of bacteriuria.

Authors:  Alexander S Gur'ev; Irina E Yudina; Anna V Lazareva; Alexey Yu Volkov
Journal:  Pract Lab Med       Date:  2018-07-18

3.  Urinary Tract Infection in Children.

Authors:  Alexander K C Leung; Alex H C Wong; Amy A M Leung; Kam L Hon
Journal:  Recent Pat Inflamm Allergy Drug Discov       Date:  2019

4.  Evaluation of a Novel Laboratory Candiduria Screening Protocol in the Intensive Care Unit.

Authors:  Zhengxin He; Chang Su; Yuwang Bi; Yan Cheng; Daxin Lei; Fukun Wang
Journal:  Infect Drug Resist       Date:  2021-02-10       Impact factor: 4.003

5.  Use of Sysmex UF-5000 flow cytometry in rapid diagnosis of urinary tract infection and the importance of validating carryover rates against bacterial count cut-off.

Authors:  Kjersti Haugum; Maria Schei Haugan; Jannicke Skage; Mariann Tetik; Aleksandra Jakovljev; Hans-Johnny Schjelderup Nilsen; Jan Egil Afset
Journal:  J Med Microbiol       Date:  2021-12       Impact factor: 2.472

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.