title: Sepsis biomarkers in neutropaenic systemic inflammatory response syndrome patients on standard care wards.
abstract: BACKGROUND
  Neutropaenic patients are at a high risk of contracting severe infections. In particular, in these patients, parameters with a high negative predictive value are desirable for excluding infection or bacteraemia. This study evaluated sepsis biomarkers in neutropaenic patients suffering from systemic inflammatory response syndrome (SIRS). Further, the predictive capacities of evaluated biomarkers in neutropaenic SIRS patients were compared to non-neutropaenic SIRS patients.
  
  
  METHODS
  In this prospective observational cohort study, patients with clinically suspected sepsis were screened. The predictive capacities of procalcitonin (PCT), C-reactive protein and lipopolysaccharide-binding protein (LBP) in neutropaenic SIRS patients were evaluated in terms of their potential to identify infection or bacteraemia and were compared to results for non-neutropaenic SIRS patients. To select an appropriate control cohort, propensity score matching was applied, balancing confounding factors between neutropaenic and non-neutropaenic SIRS patients.
  
  
  RESULTS
  Of 3370 prospectively screened patients with suspected infection, 51 patients suffered from neutropaenic SIRS. For the identification of infection, none of the assessed biomarkers presented a clinically relevant discriminatory potency. Lipopolysaccharide-binding protein and PCT demonstrated discriminatory capacity to discriminate between nonbacteraemic and bacteraemic SIRS in patients with neutropaenia [receiver-operating characteristics-area under the curves (ROC-AUCs): 0.860, 0.818]. In neutropaenic SIRS patients, LBP had a significantly better ROC-AUC than in a comparable non-neutropaenic patient cohort for identifying bacteraemia (P = 0.01).
  
  
  CONCLUSIONS
  In neutropaenic SIRS patients, none of the evaluated biomarkers was able to adequately identify infection. LBP and PCT presented a good performance in identifying bacteraemia. Therefore, these markers could be used for screening purposes to increase the pretest probability of blood culture analysis.
authors.affiliation: Division of Medical and Chemical Laboratory Diagnostics, Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria.
authors.forename: Franz
authors.initials: F
authors.lastname: Ratzinger
authors.affiliation: Division of Medical and Chemical Laboratory Diagnostics, Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria.
authors.forename: Helmuth
authors.identifier: http://orcid.org/0000-0003-4605-2503
authors.initials: H
authors.lastname: Haslacher
authors.affiliation: Division of Medical and Chemical Laboratory Diagnostics, Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria.
authors.forename: Thomas
authors.initials: T
authors.lastname: Perkmann
authors.affiliation: Division of Medical and Chemical Laboratory Diagnostics, Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria.
authors.forename: Klaus G
authors.initials: KG
authors.lastname: Schmetterer
authors.affiliation: Division of Infectious Diseases and Tropical Medicine, Department of Medicine I, Medical University of Vienna, Vienna, Austria.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Poeppl
authors.affiliation: Division of Clinical Microbiology, Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria.
authors.forename: Dieter
authors.initials: D
authors.lastname: Mitteregger
authors.affiliation: Section for Artificial Intelligence, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
authors.forename: Georg
authors.initials: G
authors.lastname: Dorffner
authors.affiliation: Division of Infectious Diseases and Tropical Medicine, Department of Medicine I, Medical University of Vienna, Vienna, Austria.
authors.forename: Heinz
authors.initials: H
authors.lastname: Burgmann
mesh_terms: D000209:Acute-Phase Proteins; D000328:Adult; D000368:Aged; D019540:Area Under Curve; D016470:Bacteremia / Q000097:blood* / Q000175:diagnosis; D002097:C-Reactive Protein / Q000378:metabolism*; D002116:Calcitonin / Q000097:blood*; D015740:Calcitonin Gene-Related Peptide; D002352:Carrier Proteins / Q000097:blood*; D016022:Case-Control Studies; D015331:Cohort Studies; D005260:Female; D006801:Humans; D008297:Male; D008562:Membrane Glycoproteins / Q000097:blood*; D008875:Middle Aged; D009503:Neutropenia / Q000097:blood*; D011237:Predictive Value of Tests; D057216:Propensity Score; D011446:Prospective Studies; D011498:Protein Precursors / Q000097:blood*; D012372:ROC Curve; D018805:Sepsis / Q000097:blood / Q000175:diagnosis; D018746:Systemic Inflammatory Response Syndrome / Q000097:blood / Q000175:diagnosis; D000099231:Lipopolysaccharide-Binding Protein
chemical_list: D000209:Acute-Phase Proteins; D002097:C-Reactive Protein; D002116:Calcitonin; D015740:Calcitonin Gene-Related Peptide; D002352:Carrier Proteins; D008562:Membrane Glycoproteins; D011498:Protein Precursors; D000099231:Lipopolysaccharide-Binding Protein; C000606589:CALCA protein, human
keywords: Infection; lipopolysaccharide-binding protein; neutropaenia; procalcitonin; propensity score; sepsis