title: Development and internal validation of a pediatric acute asthma prediction rule for hospitalization.
abstract: BACKGROUND
  Clinicians have difficulty predicting need for hospitalization of children with acute asthma exacerbations.
  
  
  OBJECTIVE
  The objective of this study was to develop and internally validate a multivariable asthma prediction rule (APR) to inform hospitalization decision making in children aged 5-17 years with acute asthma exacerbations.
  
  
  METHODS
  Between April 2008 and February 2013 we enrolled a prospective cohort of patients aged 5-17 years with asthma who presented to our pediatric emergency department with acute exacerbations. Predictors for APR modeling included 15 demographic characteristics, asthma chronic control measures, and pulmonary examination findings in participants at the time of triage and before treatment. The primary outcome variable for APR modeling was need for hospitalization (length of stay >24 h for those admitted to hospital or relapse for those discharged). A secondary outcome was the hospitalization decision of the clinical team. We used penalized maximum likelihood multiple logistic regression modeling to examine the adjusted association of each predictor variable with the outcome. Backward step-down variable selection techniques were used to yield reduced-form models.
  
  
  RESULTS
  Data from 928 of 933 participants were used for prediction rule modeling, with median [interquartile range] age 8.8 [6.9, 11.2] years, 61% male, and 59% African-American race. Both full (penalized) and reduced-form models for each outcome calibrated well, with bootstrap-corrected c-indices of 0.74 and 0.73 for need for hospitalization and 0.81 in each case for hospitalization decision.
  
  
  CONCLUSIONS
  The APR predicts the need for hospitalization of children with acute asthma exacerbations using predictor variables available at the time of presentation to an emergency department.
authors.affiliation: Departments of Pediatrics and Emergency Medicine, Vanderbilt University School of Medicine, Nashville, Tenn; Center for Asthma & Environmental Sciences Research, Vanderbilt University School of Medicine, Nashville, Tenn. Electronic address: don.arnold@vanderbilt.edu.
authors.forename: Donald H
authors.initials: DH
authors.lastname: Arnold
authors.affiliation: Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tenn; Center for Asthma & Environmental Sciences Research, Vanderbilt University School of Medicine, Nashville, Tenn.
authors.forename: Tebeb
authors.initials: T
authors.lastname: Gebretsadik
authors.affiliation: Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tenn; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands.
authors.forename: Karel G M
authors.initials: KG
authors.lastname: Moons
authors.affiliation: Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tenn.
authors.forename: Frank E
authors.initials: FE
authors.lastname: Harrell
authors.affiliation: Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tenn; Center for Asthma & Environmental Sciences Research, Vanderbilt University School of Medicine, Nashville, Tenn.
authors.forename: Tina V
authors.initials: TV
authors.lastname: Hartert
mesh_terms: D000208:Acute Disease; D000293:Adolescent; D001249:Asthma / Q000175:diagnosis*; D002648:Child; D002675:Child, Preschool; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D012044:Regression Analysis; D015203:Reproducibility of Results; D012720:Severity of Illness Index
keywords: Clinical prediction rule; Hospitalization; Pediatric acute asthma exacerbations