title: A risk prediction model for screening bacteremic patients: a cross sectional study.
abstract: BACKGROUND
  Bacteraemia is a frequent and severe condition with a high mortality rate. Despite profound knowledge about the pre-test probability of bacteraemia, blood culture analysis often results in low rates of pathogen detection and therefore increasing diagnostic costs. To improve the cost-effectiveness of blood culture sampling, we computed a risk prediction model based on highly standardizable variables, with the ultimate goal to identify via an automated decision support tool patients with very low risk for bacteraemia.
  
  
  METHODS
  In this retrospective hospital-wide cohort study evaluating 15,985 patients with suspected bacteraemia, 51 variables were assessed for their diagnostic potency. A derivation cohort (n = 14.699) was used for feature and model selection as well as for cut-off specification. Models were established using the A2DE classifier, a supervised Bayesian classifier. Two internally validated models were further evaluated by a validation cohort (n = 1,286).
  
  
  RESULTS
  The proportion of neutrophile leukocytes in differential blood count was the best individual variable to predict bacteraemia (ROC-AUC: 0.694). Applying the A2DE classifier, two models, model 1 (20 variables) and model 2 (10 variables) were established with an area under the receiver operating characteristic curve (ROC-AUC) of 0.767 and 0.759, respectively. In the validation cohort, ROC-AUCs of 0.800 and 0.786 were achieved. Using predefined cut-off points, 16% and 12% of patients were allocated to the low risk group with a negative predictive value of more than 98.8%.
  
  
  CONCLUSIONS
  Applying the proposed models, more than ten percent of patients with suspected blood stream infection were identified having minimal risk for bacteraemia. Based on these data the application of this model as an automated decision support tool for physicians is conceivable leading to a potential increase in the cost-effectiveness of blood culture sampling. External prospective validation of the model's generalizability is needed for further appreciation of the usefulness of this tool.
authors.affiliation: Department of Laboratory Medicine, Division of Medical and Chemical Laboratory Diagnostics, Medical University of Vienna, Vienna, Austria.
authors.forename: Franz
authors.initials: F
authors.lastname: Ratzinger
authors.affiliation: Department of Medicine I, Division of Infectious Diseases and Tropical Medicine, Medical University Vienna, Vienna, Austria.
authors.forename: Michel
authors.initials: M
authors.lastname: Dedeyan
authors.affiliation: Department of Medicine I, Division of Infectious Diseases and Tropical Medicine, Medical University Vienna, Vienna, Austria.
authors.forename: Matthias
authors.initials: M
authors.lastname: Rammerstorfer
authors.affiliation: Department of Laboratory Medicine, Division of Medical and Chemical Laboratory Diagnostics, Medical University of Vienna, Vienna, Austria.
authors.forename: Thomas
authors.initials: T
authors.lastname: Perkmann
authors.affiliation: Department of Medicine I, Division of Infectious Diseases and Tropical Medicine, Medical University Vienna, Vienna, Austria.
authors.forename: Heinz
authors.initials: H
authors.lastname: Burgmann
authors.affiliation: Department of Laboratory Medicine, Division of Clinical Microbiology, Medical University of Vienna, Vienna, Austria.
authors.forename: Athanasios
authors.initials: A
authors.lastname: Makristathis
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: Department of Medicine I, Division of Infectious Diseases and Tropical Medicine, Medical University Vienna, Vienna, Austria.
authors.forename: Felix
authors.initials: F
authors.lastname: Lötsch
authors.affiliation: Clinical Institute for Hospital Hygiene, Medical University of Vienna, Vienna, Austria.
authors.forename: Alexander
authors.initials: A
authors.lastname: Blacky
authors.affiliation: Department of Medicine I, Division of Infectious Diseases and Tropical Medicine, Medical University Vienna, Vienna, Austria; Institut für Tropenmedizin, Universität Tübingen, Tübingen, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Ramharter
mesh_terms: D000328:Adult; D000368:Aged; D016470:Bacteremia / Q000097:blood* / Q000175:diagnosis* / Q000401:mortality*; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007958:Leukocyte Count; D008297:Male; D008875:Middle Aged; D008954:Models, Biological