title: Validation of a prediction rule for endocarditis in febrile injection drug users.
abstract: BACKGROUND
  Infectious endocarditis (IE) in febrile injection drug users (IDUs) is a critical diagnosis to identify in the emergency department (ED). A decision tool that identifies patients at very low risk for endocarditis using readily available clinical data could reduce admissions and cost.
  
  
  OBJECTIVE
  To evaluate the diagnostic performance of a previously derived decision instrument to rule out endocarditis in febrile IDUs (Prediction Rule for Endocarditis in Injection Drug Users [PRE-IDU]) and to develop a prediction model for likelihood of endocarditis for those who are not ruled out by PRE-IDU.
  
  
  METHODS
  Febrile IDUs admitted to rule out endocarditis were prospectively enrolled from 2 urban EDs in June 2007 to March 2011. Clinical data from ED presentation (first 6 hours) and outcome data from inpatient records were recorded and reviewed by 2 independent investigators. Diagnosis of IE was based on modified Duke criteria and discharge summaries. The diagnostic performance of PRE-IDU, which combines tachycardia, cardiac murmur, and absence of skin infection, was determined using recursive partitioning and logistic regression modeling.
  
  
  RESULTS
  Of the 249 subjects, 18 (7%) had IE. Recursive partitioning yielded an instrument with 100% sensitivity (95% confidence interval [CI], 84%-100%) and 100% negative predictive value (95% CI, 91%-100%), but low specificity (13%; 95% CI, 12%-13%). Multiple logistic regression modeling with the 3 clinical predictors allowed risk stratification with posttest probabilities ranging from 3% to 20%.
  
  
  CONCLUSIONS
  The PRE-IDU instrument predicted IE with high sensitivity and ruled out IE with high negative predictive value. Our logistic regression model provided posttest probabilities ranging from 3% to 20%. The PRE-IDU instrument and the associated model may help guide hospital admission and diagnostic testing in evaluation of febrile IDUs in the ED.
authors.affiliation: Stanford University Medical Center, Stanford, CA.
authors.forename: Hangyul
authors.initials: H
authors.lastname: Chung-Esaki
authors.affiliation: San Francisco General Hospital/University of California San Francisco, San Francisco, CA. Electronic address: robert.rodriguez@emergency.ucsf.edu.
authors.forename: Robert M
authors.initials: RM
authors.lastname: Rodriguez
authors.affiliation: Alameda County Medical Center, Oakland, CA.
authors.forename: Harrison
authors.initials: H
authors.lastname: Alter
authors.affiliation: Alameda County Medical Center, Oakland, CA.
authors.forename: Bitou
authors.initials: B
authors.lastname: Cisse
mesh_terms: D000328:Adult; D004636:Emergency Service, Hospital; D004696:Endocarditis / Q000175:diagnosis*; D005260:Female; D005334:Fever; D006801:Humans; D008297:Male; D011237:Predictive Value of Tests; D011446:Prospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D015819:Substance Abuse, Intravenous / Q000150:complications*