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Risk stratification for hospitalization in acute asthma: the CHOP classification tree
Chu-Lin Tsai1, Sunday Clark, Carlos A Camargo
1Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA. cltsai@post.harvard.edu
The American Journal of Emergency Medicine
|September 15, 2010
Summary
A new decision tree accurately predicts acute asthma hospitalizations in emergency departments. This tool, using four key factors, aids clinicians in managing asthma patients effectively.
Area of Science:
- Emergency Medicine
- Pulmonology
- Clinical Decision Support
Background:
- Current risk stratification tools for acute asthma are insufficient.
- Effective risk assessment is crucial for managing emergency department (ED) patients with acute asthma.
Purpose of the Study:
- To develop and externally validate a classification tree for predicting asthma hospitalization.
- To create a simple, explicit risk stratification rule for acute asthma care.
Main Methods:
- Utilized data from two large, multicenter studies: the National Emergency Department Safety Study and the Multicenter Airway Research Collaboration cohorts.
- Employed the Classification and Regression Tree method to derive a decision tree using clinical information from 1825 ED patients.
- Validated the derived tree in a separate cohort of 1335 ED patients.
Main Results:
- Identified four key predictors: change in peak expiratory flow severity, prior asthma hospitalization, oxygen saturation, and initial peak expiratory flow (CHOP mnemonic).
- The 3-step decision rule stratified patients into 7 risk groups, with admission rates from 9% to 48%.
- The classification tree demonstrated satisfactory discrimination, with areas under the receiver operating characteristic curve of 0.72 (derivation) and 0.65 (validation).
Conclusions:
- A novel classification tree for predicting asthma hospitalization in ED patients was successfully developed and validated.
- This explicit risk stratification rule can assist emergency care providers in making informed decisions for acute asthma management.
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