title: Can urine dipstick testing for urinary tract infection at point of care reduce laboratory workload?
abstract: OBJECTIVE
  The University Hospitals of Leicester NHS Trust microbiology laboratory receives 150 000 urine samples each year, approximately 80% of which prove to be culture negative. The aim of this study was to reduce the proportion of culture negative urines arriving in the laboratory, by producing local evidence based guidelines for the use of urine dipstick testing at point of care within the trust's three acute hospitals.
  
  
  METHODS
  One thousand and seventy six unborated urine samples were dipstick tested at the point of care using an automatic strip reader. Quantitative results for the four infection associated markers-leucocyte esterase, nitrite, blood, and protein-were compared with the results of conventional laboratory microscopy and culture.
  
  
  RESULTS
  The performance of different marker combinations was calculated against the routine laboratory methods. One hundred and seventy five (16.3%) samples were negative for all four markers. Of these dipstick negative samples, only three (1.7% of all true positives) were positive by culture. The absence of all four infection associated markers was found to have a greater than 98% negative predictive value and a sensitivity and specificity of 98.3% and 19.2%, respectively.
  
  
  CONCLUSIONS
  A urinary dipstick testing algorithm for infection associated markers was derived for use in hospital patients to screen out negative urines. Two years after distributing the algorithm and promoting access to reagent strips and strip readers, a reduction in the urine workload has been seen against an otherwise increasing laboratory specimen load.
authors.affiliation: Department of Clinical Microbiology, University Hospitals of Leicester NHS Trust, Leicester LE1 5WW, UK.
authors.forename: H D
authors.initials: HD
authors.lastname: Patel
authors.forename: S A
authors.initials: SA
authors.lastname: Livsey
authors.forename: R A
authors.initials: RA
authors.lastname: Swann
authors.forename: S S
authors.initials: SS
authors.lastname: Bukhari
mesh_terms: D000465:Algorithms; D001437:Bacteriuria / Q000175:diagnosis*; D015415:Biomarkers / Q000652:urine; D004739:England; D006302:Health Services Research / Q000379:methods; D006801:Humans; D007755:Laboratories, Hospital / Q000706:statistics & numerical data*; D019095:Point-of-Care Systems; D017410:Practice Guidelines as Topic; D011237:Predictive Value of Tests; D011934:Reagent Strips; D012680:Sensitivity and Specificity; D016482:Urinalysis / Q000379:methods*; D014552:Urinary Tract Infections / Q000175:diagnosis*; D016526:Workload / Q000706:statistics & numerical data*
chemical_list: D015415:Biomarkers; D011934:Reagent Strips