Application of Asthma Prediction Tools in a Cohort of Infants with Severe Bronchiolitis

Abstract

Background: Severe bronchiolitis is a strong childhood asthma risk factor. Early and accurate asthma prediction is key. We applied the Asthma Predictive Index (API), the modified Asthma Predictive Index (mAPI), and the Pediatric Asthma Risk Score (PARS) in a cohort of high-risk infants to predict asthma at age 6 years. Methods: We conducted a 17-center cohort of infants (age <1 year) hospitalized with severe bronchiolitis during 2011-2014. We used only infancy data to predict asthma at age 6 years. Results: The prevalence of parent-reported asthma at age 6 years was 328/880 (37%). The prevalences of a positive index/score for stringent and loose API, mAPI, and PARS were 21%, 51%, 11%, and 34%, respectively. Area under the receiver operating characteristic curves [95% confidence interval (CI)] ranged from 0.57 (95% CI 0.55-0.60) for mAPI to 0.66 (95% CI 0.63-0.70) for PARS. Conclusions: An asthma prediction tool for high-risk infants is needed to identify those who would benefit most from asthma prevention interventions.