Evaluation of Risk Scores to Predict Pediatric Severe Asthma Exacerbations.

BACKGROUND

Asthma exacerbations commonly lead to unplanned health care utilization and are costly. Early identification of children at increased risk of asthma exacerbations would allow a proactive management approach.

OBJECTIVE

We evaluated common asthma risk factors to predict the probability of exacerbation for individual children aged 0-21 years using data from the electronic medical record (EMR).

METHODS

We analyzed longitudinal EMR data for over 3000 participants with asthma seen at Cincinnati Children's Hospital Medical Center over a 7-year period. The study population was divided into 3 age groups: 0-4, 5-11, and 12-21 years. Each age group was divided into a derivation cohort and a validation cohort, which were used to build a risk score model. We predicted risk of exacerbation in the next 12 months, validated the scores by risk stratum, and developed a clinical tool to determine the risk level based on this model.

RESULTS

Risk model results were confirmed with validation cohorts by calendar year and age groups. Race, allergic sensitization, and smoke exposure were each important risk factors in the 0-4 age group. Abnormal spirometry and obesity were more sensitive predictors of exacerbation in children >12 years. For each age group, a higher expanded score was associated with a higher predicted probability of an asthma exacerbation in the subsequent year.

CONCLUSION

This asthma exacerbation prediction model, and the associated clinical tool, may assist clinicians in identifying children at high risk for exacerbation that may benefit from more aggressive management and targeted risk mitigation.