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Automated Microscopy, Dipsticks and the Diagnosis of Urinary Tract Infection
  1. Andrew Lunn,
  2. Stephen Holden,
  3. Tim Boswell,
  4. Alan R Watson*
  1. Nottingham University Hospitals NHS Trust, United Kingdom
  1. Correspondence to: Alan R Watson, Paediatric Nephrology, Nottingham University Hospitals - QMC Campus, Nottingham University Hospitals, QMC Campus, Derby Road, Nottingham, NG7 2UH, United Kingdom; judith.hayes{at}nuh.nhs.uk

Abstract

Objectives: Automated microscopy (AM) is increasingly used to screen samples for suspected urinary tract infection (UTI). A 98.8% negative predictive value has been reported in adult studies. The aim of our study was to validate this method in a paediatric population.

Methods: Urine samples were collected from children with known or suspected nephrourological disease attending nephrology and urology clinics over a 6 week time period. Samples were tested with dipstick, the UF100 flow cytometer (AM) and culture. A gold standard of a positive culture of 105 colony forming units per ml (cfu/ml) with a pathogenic organism was used and the sensitivity, specificity and likelihood ratios were calculated.

Results: 280 urine samples were collected from 263 patients (143 male, median age 10.2 years, range 0.1-19.75 years). 221(79%) were midstream or clean-catch samples. AM identified 42 of 186 samples as requiring culture and 17 of 19 samples which had a pure growth > 105 cfu/ml. Two patients were not identified by AM, one was treated for vulvovaginitis, one commenced prophylactic antibiotics prior to the culture result being obtained. The sensitivity, specificity, positive and negative likelihood ratios were 0.89, 0.85, 5.98 and 0.17 respectively. This compared to 0.95, 0.72, 3.34 and 0.29 respectively with urine dipstick.

Conclusion: AM performed comparably to urine dipstick in the diagnosis of UTI with improved specificity and likelihood ratios with a slight reduction in sensitivity. The data support the use of AM for screening urines for culture in children but different AM methods and algorithms require local evaluation.

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