Development and Internal Validation of a Pediatric Acute Asthma Prediction Rule for Hospitalization

Abstract

Clinicians have difficulty predicting need for hospitalization of children with acute asthma exacerbations. 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. 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. 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. 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.