Predicting need for hospitalization in acute pediatric asthma

Pediatr Emerg Care. 2008 Nov;24(11):735-44. doi: 10.1097/PEC.0b013e31818c268f.

Abstract

Objectives: To develop and validate predictive models to determine the need for hospitalization in children treated for acute asthma in the emergency department (ED).

Methods: Prospective cohort study of children aged 2 years and older treated at 2 pediatric EDs for acute asthma. The primary outcome was successful ED discharge, defined as actual discharge from the ED and no readmission for asthma within 7 days, versus need for extended care. Among those defined as requiring extended care, a secondary outcome of inpatient care (>24 hours) or short-stay care (<24 hours) was defined. Logistic regression and recursive partitioning were used to create predictive models based on historical and clinical data from the ED visit. Models were developed with data from 1 ED and validated in the other.

Results: There were 852 subjects in the derivation group and 369 in the validation group. A model including clinical score (Pediatric Asthma Severity Score) and number of albuterol treatments in the ED distinguished successful discharge from need for extended care with an area under the receiver-operator characteristic curve of 0.89 (95% confidence interval [CI], 0.87-0.92) in the derivation group and 0.92 (95% CI, 0.89-0.95) in the validation group. Using a score of 5 or more as a cutoff, the likelihood ratio positive was 5.2 (95% CI, 4.2-6.5), and the likelihood ratio negative was 0.22 (95% CI, 0.17-0.28). Among those predicted to need extended care, a classification tree using number of treatments in the ED, clinical score at end of ED treatment, and initial pulse oximetry correctly classified 63% (95% CI, 56-70) of the derivation group as short stay or inpatient, and 62% (95% CI, 55-68) of the validation group.

Conclusions: Successful discharge from the ED for children with acute asthma can be predicted accurately using a simple clinical model, potentially improving disposition decisions. However, predicting correct placement of patients requiring extended care is problematic.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Acute Disease
  • Adolescent
  • Anti-Asthmatic Agents / administration & dosage
  • Asthma / diagnosis*
  • Asthma / epidemiology
  • Asthma / therapy*
  • Child
  • Child, Preschool
  • Cohort Studies
  • Emergency Service, Hospital / statistics & numerical data*
  • Emergency Treatment / methods
  • Emergency Treatment / statistics & numerical data
  • Female
  • Follow-Up Studies
  • Hospitalization / statistics & numerical data*
  • Hospitals, Pediatric
  • Humans
  • Logistic Models
  • Male
  • Multivariate Analysis
  • Needs Assessment
  • Predictive Value of Tests
  • Prospective Studies
  • Reproducibility of Results
  • Respiratory Function Tests
  • Risk Assessment
  • Severity of Illness Index
  • Status Asthmaticus / diagnosis
  • Status Asthmaticus / drug therapy*
  • Status Asthmaticus / epidemiology
  • Treatment Outcome

Substances

  • Anti-Asthmatic Agents