Phenotypes of asthma exacerbation associated with disease progression during hospitalization
Published online: October 1, 2020
Asthma exacerbation (AE) remains a serious treatment challenge. AE is a frequent cause of hospitalization or emergency room admission presentation. Thus, AE imposes considerable suffering and patient burden and constitute a major burden on health care resources. In 2016, the Global Burden of Disease collaboration estimated that there were approximately 420,000 deaths globally due to asthma. Asthma is a heterogeneous and common chronic airway disease. In recent years, there has been an increasing interest in the heterogeneity and phenotyping of asthma. Previous studies identified subsets of patients sharing clinical characteristics, and several studies involving phenotypes of stable asthma have been published. These studies have significantly advanced knowledge of stable asthma and have important implications for clinical practice. To the best of our knowledge, few studies have grouped patients with an AE into different phenotypes immediately at hospital admission, and then related those identified phenotypes to disease progression and risk of in-hospital adverse outcomes. Investigation of the heterogeneity of AE would help identify patients at increased risk of serious asthma-related adverse outcomes during hospitalization. Furthermore, recognizing heterogeneity among patients with AEs is essential to guide management and determine priorities for critical care.
In a research article recently published in The Journal of Allergy and Clinical Immunology: In Practice, Wang and colleagues conducted a cluster analysis to group patients with an AE into different phenotypes immediately at hospital admission and further explored the relationship of the identified phenotypes to the risk of serious asthma-related adverse outcomes during hospitalization, such as the need for mechanical ventilation, intensive care unit (ICU) admission, prolonged length of stay (LOS), death, and economic burden. A decision tree algorithm was applied to predict the cluster for each subject, and misclassification rates were calculated.
Three phenotypes in patients with AEs were identified: “late-onset,” “early-onset,” and a phenotype of “fewer eosinophils and increased comorbidities.” Of these 3, the “fewer eosinophils and increased comorbidities” phenotype was significantly associated with worse in-hospital outcomes. Using only 2 variables, prehospital rescue use of oral corticosteroids for exacerbation and age of onset (cut at age 12), 90.8% of patients could be assigned to the correct cluster.
These findings were clinically relevant to disease progression and in-hospital adverse outcomes, indicating that the identified phenotypes and decision tree diagram have important and clinically relevant implications for the clinical practice and individualized management of patients hospitalized for AEs.
The Journal of Allergy and Clinical Immunology: In Practice is an official journal of the AAAAI, focusing on practical information for the practicing clinician.
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