title: Early diagnosis model for meningitis supports public health decision making.
abstract: OBJECTIVE
  To develop a predictive model for rapid differential diagnosis of meningitis and meningococcal septicaemia to support public health decisions on chemoprophylaxis for contacts.
  
  
  METHODS
  Prospective study of suspected cases of acute meningitis and meningococcal septicaemia admitted to hospitals in the South West, West Midlands and London Regions of England from July 2008 to June 2009. Epidemiological, clinical and laboratory variables on admission were recorded. Logistic regression was used to derive a predictive model.
  
  
  RESULTS
  Of the 719 suspect cases reported, 385 confirmed cases were included in analysis. Peripheral blood polymorphonuclear count of >16 × 10(9)/l, serum C-reactive protein of >100 mg/l and haemorrhagic rash were strongly and independently associated with diagnosis of bacterial meningitis and meningococcal septicaemia. Using a simple scoring system, the presence of any one of these factors gave a probability of >95% in predicting the final diagnosis.
  
  
  CONCLUSIONS
  We have developed a model using laboratory and clinical factors, but not dependent on availability of CSF, for differentiating acute bacterial from viral meningitis within a few hours of admission to hospital. This scoring system is recommended in public health management of suspected cases of meningitis and meningococcal septicaemia to inform decisions on chemoprophylaxis.
authors.affiliation: Health Protection Agency South West, Gloucester Business Park Brockworth, Gloucester GL3 4AB, UK. Rebecca.close@hpa.org.uk
authors.forename: Rebecca M
authors.initials: RM
authors.lastname: Close
authors.forename: Oluwatoyin O
authors.initials: OO
authors.lastname: Ejidokun
authors.forename: Neville Q
authors.initials: NQ
authors.lastname: Verlander
authors.forename: Graham
authors.initials: G
authors.lastname: Fraser
authors.forename: Margie
authors.initials: M
authors.lastname: Meltzer
authors.forename: Yasmin
authors.initials: Y
authors.lastname: Rehman
authors.forename: Peter
authors.initials: P
authors.lastname: Muir
authors.forename: Nelly
authors.initials: N
authors.lastname: Ninis
authors.forename: James M
authors.initials: JM
authors.lastname: Stuart
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002097:C-Reactive Protein / Q000032:analysis; D018890:Chemoprevention; D002648:Child; D002675:Child, Preschool; D003657:Decision Making; D003937:Diagnosis, Differential; D042241:Early Diagnosis; D004739:England; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016015:Logistic Models; D008297:Male; D008581:Meningitis / Q000097:blood* / Q000382:microbiology* / Q000517:prevention & control; D008589:Meningococcal Infections / Q000097:blood* / Q000382:microbiology*; D008875:Middle Aged; D009345:Neisseria meningitidis; D011446:Prospective Studies; D015980:Public Health Practice; D018571:Sentinel Surveillance; D018805:Sepsis / Q000097:blood* / Q000382:microbiology; D055815:Young Adult
chemical_list: D002097:C-Reactive Protein