title: A model to predict the improvement of automated blood culture bacterial detection by doubling platelet sample volume.
abstract: BACKGROUND
  Some transmissions of bacterial infection from platelet (PLT) transfusion have occurred since introduction of automated blood culturing of apheresis PLTs. The majority of these cases involved false-negative culture results in which slow-growing Staphylococcus organisms were implicated. This study analyses the projected benefit in detecting slow growing organisms by increasing sample volume from 4 to 8 mL.
  
  
  METHODS
  Bacterial growth was modeled by varying the initial inoculum, doubling time, and lag time. The numbers of organisms present at a 24-hour sampling time were calculated. Poisson analysis was used to determine the fraction of 4- or 8-mL samples that could be detected because they contained organisms. For each inoculum, the percentage of improved detection by doubling sample volume was defined as delta, the difference between the percentage of detection of 8- and 4-mL samples.
  
  
  RESULTS
  The maximum improvement in detection by doubling sample volume was 25 percent and did not depend on bacterial growth rate or lag time. As inocula increased toward 40 colony-forming units per unit, delta decreased. As lag and doubling times increased, inocula corresponding to maximum delta increased and the width of the distribution curve broadened.
  
  
  CONCLUSIONS
  Doubling sample volume will not double the chance of detecting slow growing organisms, but instead is predicted to improve detection by 25 percent or less.
authors.affiliation: Blood Components Department, American Red Cross Holland Laboratory for the Biomedical Sciences, Rockville, Maryland 20855, USA. wagners@usa.redcross.org
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Wagner
authors.forename: Anne F
authors.initials: AF
authors.lastname: Eder
mesh_terms: D001331:Automation; D001419:Bacteria / Q000254:growth & development; D001769:Blood / Q000382:microbiology; D001792:Blood Platelets / Q000382:microbiology*; D001800:Blood Specimen Collection / Q000379:methods*; D006801:Humans; D008828:Microbiological Techniques / Q000379:methods*; D015233:Models, Statistical; D016012:Poisson Distribution