Latent class analysis to identify clinical profiles among indigenous infants with bronchiolitis

Abstract

Objective: Better phenotyping of the heterogenous bronchiolitis syndrome may lead to targeted future interventions. This study aims to identify severe bronchiolitis profiles among hospitalized Australian Indigenous infants, a population at risk of bronchiectasis, using latent class analysis (LCA). Methods: We included prospectively collected clinical, viral, and nasopharyngeal bacteria data from 164 Indigenous infants hospitalized with bronchiolitis from our previous studies. We undertook multiple correspondence analysis (MCA) followed by LCA. The best-fitting model for LCA was based on adjusted Bayesian information criteria and entropy R2. Results: We identified five clinical profiles. Profile-A's (23.8% of cohort) phenotype was previous preterm (90.7%), low birth-weight (89.2%) and weight-for-length z-score