title: Systematic review and meta-analysis of flow cytometry in urinary tract infection screening.
abstract: BACKGROUND
  Automated urine sediment analysis of white blood cells (WBCs) and bacteria is a promising approach for urinary tract infections (UTIs) screening. However, available data on their screening efficacy is inconsistent.
  
  
  METHODS
  English articles from Pubmed, EMBASE, and Web of Science published before December 1, 2012 were analyzed. The Quality Assessment for Studies of Diagnostic Accuracy (QUADAS) tool was used to evaluate the quality of eligible studies. Performance characteristics of WBCs and bacteria (sensitivity, specificity, and other measures of accuracy) were pooled and examined by random-effects models.
  
  
  RESULTS
  Nineteen studies containing 22,305 samples were included. Pooled sensitivities were 0.87 (95% confidence interval [CI], 0.86-0.89) for WBCs and 0.92 (95% CI, 0.91-0.93) for bacteria. Corresponding pooled specificities were 0.67 (95% CI, 0.66-0.68) for WBCs and 0.60 (95% CI, 0.59-0.61) for bacteria. Areas under the summary receiver operating characteristics curves were 0.87 and 0.93 for WBCs and bacteria, respectively. The major limitation of eligible studies was that enrolled subjects were often not representative of clinical patient populations in which UTI would be suspected.
  
  
  CONCLUSIONS
  WBC and bacterial measurements by the UF-100 and UF-1000i are useful indicators in UTI screening; however, the performances of these systems should be rigorously evaluated by additional studies.
authors.affiliation: Department of Laboratory Diagnosis, Changhai Hospital, Second Military Medical University, Shanghai China.
authors.forename: Yan-Jun
authors.initials: YJ
authors.lastname: Shang
authors.forename: Qian-Qian
authors.initials: QQ
authors.lastname: Wang
authors.forename: Jian-Rong
authors.initials: JR
authors.lastname: Zhang
authors.forename: Yu-Lian
authors.initials: YL
authors.lastname: Xu
authors.forename: Wei-Wei
authors.initials: WW
authors.lastname: Zhang
authors.forename: Yan
authors.initials: Y
authors.lastname: Chen
authors.forename: Ming-Li
authors.initials: ML
authors.lastname: Gu
authors.forename: Zhi-De
authors.initials: ZD
authors.lastname: Hu
authors.forename: An-Mei
authors.initials: AM
authors.lastname: Deng
mesh_terms: D019540:Area Under Curve; D001437:Bacteriuria / Q000175:diagnosis / Q000473:pathology / Q000652:urine*; D015169:Colony Count, Microbial; D016206:Databases, Bibliographic; D005434:Flow Cytometry / Q000706:statistics & numerical data*; D006801:Humans; D007958:Leukocyte Count; D007962:Leukocytes / Q000473:pathology; D012372:ROC Curve; D016482:Urinalysis / Q000706:statistics & numerical data*; D014552:Urinary Tract Infections / Q000175:diagnosis / Q000473:pathology / Q000652:urine*
keywords: Automated urine sediment analyzer; Meta-analysis; Systematic review; Urinary tract infection