title: Development and validation of a multivariable predictive model to distinguish bacterial from aseptic meningitis in children in the post-Haemophilus influenzae era.
abstract: BACKGROUND
  Children with meningitis are routinely admitted to the hospital and administered broad-spectrum antibiotics pending culture results because distinguishing bacterial meningitis from aseptic meningitis is often difficult.
  
  
  OBJECTIVE
  To develop and validate a simple multivariable model to distinguish bacterial meningitis from aseptic meningitis in children using objective parameters available at the time of patient presentation.
  
  
  METHODS
  Retrospective cohort study of all children with meningitis admitted to 1 urban children's hospital from July 1992 through June 2000, randomly divided into derivation (66%) and validation sets (34%).
  
  
  METHODS
  Six hundred ninety-six previously healthy children aged 29 days to 19 years, of whom 125 (18%) had bacterial meningitis and 571 (82%) had aseptic meningitis.
  
  
  METHODS
  Multivariable logistic regression and recursive partitioning analyses identified the following predictors of bacterial meningitis from the derivation set: Gram stain of cerebrospinal fluid (CSF) showing bacteria, CSF protein > or =80 mg/dL, peripheral absolute neutrophil count > or =10 000 cells/mm3, seizure before or at time of presentation, and CSF absolute neutrophil count > or =1000 cells/mm3. A Bacterial Meningitis Score (BMS) was developed on the derivation set by attributing 2 points for a positive Gram stain and 1 point for each of the other variables.
  
  
  METHODS
  The accuracy of the BMS when applied to the validation set.
  
  
  RESULTS
  A BMS of 0 accurately identified patients with aseptic meningitis without misclassifying any child with bacterial meningitis in the validation set. The negative predictive value of a score of 0 for bacterial meningitis was 100% (95% confidence interval: 97%-100%). A BMS > or =2 predicted bacterial meningitis with a sensitivity of 87% (95% confidence interval: 72%-96%).
  
  
  CONCLUSIONS
  The BMS accurately identifies children at low (BMS = 0) or high (BMS > or =2) risk of bacterial meningitis. Outpatient management may be considered for children in the low-risk group.
mesh_terms: D000293:Adolescent; D000328:Adult; D001419:Bacteria / Q000302:isolation & purification; D002555:Cerebrospinal Fluid / Q000382:microbiology; D002556:Cerebrospinal Fluid Proteins / Q000032:analysis; D002648:Child; D002675:Child, Preschool; D003937:Diagnosis, Differential; D005260:Female; D005840:Gentian Violet; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007958:Leukocyte Count; D016015:Logistic Models; D008297:Male; D008582:Meningitis, Aseptic / Q000097:blood / Q000134:cerebrospinal fluid / Q000175:diagnosis*; D016920:Meningitis, Bacterial / Q000097:blood / Q000134:cerebrospinal fluid / Q000175:diagnosis*; D015999:Multivariate Analysis; D009504:Neutrophils; D010619:Phenazines; D011237:Predictive Value of Tests
chemical_list: D002556:Cerebrospinal Fluid Proteins; C035863:Gram's stain; D010619:Phenazines; D005840:Gentian Violet