title: Comparison between procalcitonin and C-reactive protein in predicting bacteremias and confounding factors: a case-control study.
abstract: BACKGROUND
  The detection of infectious bacteria in blood culture samples is important for diagnosis and treatment, but this requires 1-2 days at least, and is not adequate as a rapid test. Therefore, we have investigated the diagnostic ability and the optimal cutoff value of procalcitonin (PCT) and C-reactive protein (CRP) for predicting the bacteremias using receiver operating characteristic (ROC) curves and relative cumulative frequency distribution (RCD) curves.
  
  
  METHODS
  A case-control study was performed in inpatients (852 subjects: 426 positive cultures and 426 negative cultures) from January 1 to December 31, 2014. We retrospectively investigated their blood culture and blood chemistry findings recorded in this period using electronic medical records.
  
  
  RESULTS
  Area under the ROC curve of PCT and CRP were 0.79 and 0.66, respectively. The optimal cutoff values were 0.5 μg/L with a sensitivity of 70% and specificity of 70% for PCT and 50.0 mg/L with a sensitivity of 63% and specificity of 65% for CRP. When the optimal cutoff value was treated as a reference, the odds ratio (OR) was 71.11 and the hazard ratio (HR) was 6.27 for PCT >2.0 μg/L, and the risk of blood culture positivity was markedly elevated. PCT levels were significantly higher in the population with Gram-negative rod (GNR) infections than in the population with Gram-positive coccal (GPC) infections.
  
  
  CONCLUSIONS
  The elevation of CRP and PCT were significantly associated with bacteremias. PCT was superior to CRP as a diagnostic indicator for predicting bacteremias, for discriminating bacterial from nonbacterial infections, and for determining bacterial species.
authors.affiliation: .
authors.forename: Hirokazu
authors.identifier: http://orcid.org/0000-0003-1492-3490
authors.initials: H
authors.lastname: Nishikawa
authors.affiliation: .
authors.forename: Michinori
authors.initials: M
authors.lastname: Shirano
authors.affiliation: .
authors.forename: Yu
authors.initials: Y
authors.lastname: Kasamatsu
authors.affiliation: .
authors.forename: Ayumi
authors.initials: A
authors.lastname: Morimura
authors.affiliation: .
authors.forename: Ko
authors.initials: K
authors.lastname: Iida
authors.affiliation: .
authors.forename: Tomomi
authors.initials: T
authors.lastname: Kishi
authors.affiliation: .
authors.forename: Tetsushi
authors.initials: T
authors.lastname: Goto
authors.affiliation: .
authors.forename: Saki
authors.initials: S
authors.lastname: Okamoto
authors.affiliation: .
authors.forename: Eiji
authors.initials: E
authors.lastname: Ehara
mesh_terms: D000328:Adult; D000368:Aged; D016470:Bacteremia / Q000097:blood* / Q000175:diagnosis*; D002097:C-Reactive Protein / Q000378:metabolism*; D002116:Calcitonin / Q000097:blood*; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D012189:Retrospective Studies
chemical_list: D002116:Calcitonin; D002097:C-Reactive Protein
keywords: C-reactive protein; bacteremias; confounding factors; procalcitonin; receiver operating characteristics curve; relative cumulative frequency distribution curve