title: Risk stratification for hospitalization in acute asthma: the CHOP classification tree.
abstract: OBJECTIVE
  Simple risk stratification rules are limited in acute asthma. We developed and externally validated a classification tree for asthma hospitalization.
  
  
  METHODS
  Data were obtained from 2 large, multicenter studies on acute asthma, the National Emergency Department Safety Study and the Multicenter Airway Research Collaboration cohorts. Both studies involved emergency department (ED) patients aged 18 to 54 years presenting to the ED with acute asthma. Clinical information was obtained from medical record review. The Classification and Regression Tree method was used to generate a simple decision tree. The tree was derived in the National Emergency Department Safety Study cohort and then was validated in the Multicenter Airway Research Collaboration cohort.
  
  
  RESULTS
  There were 1825 patients in the derivation cohort and 1335 in the validation cohort. Admission rates were 18% and 21% in the derivation and validation cohorts, respectively. The Classification and Regression Tree method identified 4 important variables (CHOP): change [C] in peak expiratory flow severity category, ever hospitalization [H] for asthma, oxygen [O] saturation on room air, and initial peak expiratory flow [P]. In a simple 3-step process, the decision rule risk-stratified patients into 7 groups, with a risk of admission ranging from 9% to 48%. The classification tree performed satisfactorily on discrimination in both the derivation and validation cohorts, with an area under the receiver operating characteristic curve of 0.72 and 0.65, respectively.
  
  
  CONCLUSIONS
  We developed and externally validated a novel classification tree for hospitalization among ED patients with acute asthma. Use of this explicit risk stratification rule may aid decision making in the emergency care of acute asthma.
authors.affiliation: Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA. cltsai@post.harvard.edu
authors.forename: Chu-Lin
authors.initials: CL
authors.lastname: Tsai
authors.forename: Sunday
authors.initials: S
authors.lastname: Clark
authors.forename: Carlos A
authors.initials: CA
authors.lastname: Camargo
mesh_terms: D000208:Acute Disease; D000328:Adult; D000465:Algorithms; D001249:Asthma / Q000145:classification* / Q000175:diagnosis / Q000453:epidemiology; D016009:Chi-Square Distribution; D015331:Cohort Studies; D003663:Decision Trees; D004635:Emergency Medicine / Q000458:organization & administration; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008297:Male; D010343:Patient Admission / Q000706:statistics & numerical data; D018579:Patient Selection; D010366:Peak Expiratory Flow Rate; D011237:Predictive Value of Tests; D012372:ROC Curve; D012044:Regression Analysis; D018570:Risk Assessment / Q000379:methods* / Q000592:standards; D012720:Severity of Illness Index; D018709:Statistics, Nonparametric