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- W3091312314 abstract "Background Hospitalization due to acute asthma exacerbation (AE) is a highly detrimental situation requiring critical management to prevent further deterioration, including mechanical ventilation, intensive care unit (ICU) admission, and death. However, patients hospitalized for AEs are highly heterogeneous and remain largely unexplored. Objective To identify clinical and inflammatory phenotypes of AE requiring hospitalization associated with in-hospital outcomes. Methods We performed a hierarchical cluster analysis of 825 consecutively recruited patients hospitalized for AEs. Logistic regressions were conducted to quantify the independent associations of the identified phenotypes with in-hospital outcomes. Decision tree analysis was developed to predict cluster assignment. Results We identified 3 clusters of patients, which had significantly different characteristics associated with in-hospital adverse outcomes. Cluster 1 (n = 526, 63.8%) was a late-onset phenotype, cluster 2 (n = 97, 11.8%) was an early-onset phenotype, and cluster 3 (n = 202, 24.5%) was a phenotype with fewer eosinophils and more comorbidities. Clusters 2 and 3 had an elevated risk of death (relative ratio [RRadj], 18.10 and 19.17, respectively) and mechanical ventilation (RRadj, 2.56 and 5.71, respectively) than did cluster 1. Individuals in cluster 3 had an extended length of hospital stay (11 days), increased hospitalization direct costs (13,481.57 Chinese Yuan), and a higher risk of ICU admission (RRadj, 2.14) than individuals in clusters 1 and 2. The decision tree assigned 90.8% of the participants correctly. Conclusions We identified 3 phenotypes with differential clinical and inflammatory characteristics associated with in-hospital adverse outcomes. These new phenotypes might have important and clinically relevant implications for the management of patients hospitalized for AEs. Hospitalization due to acute asthma exacerbation (AE) is a highly detrimental situation requiring critical management to prevent further deterioration, including mechanical ventilation, intensive care unit (ICU) admission, and death. However, patients hospitalized for AEs are highly heterogeneous and remain largely unexplored. To identify clinical and inflammatory phenotypes of AE requiring hospitalization associated with in-hospital outcomes. We performed a hierarchical cluster analysis of 825 consecutively recruited patients hospitalized for AEs. Logistic regressions were conducted to quantify the independent associations of the identified phenotypes with in-hospital outcomes. Decision tree analysis was developed to predict cluster assignment. We identified 3 clusters of patients, which had significantly different characteristics associated with in-hospital adverse outcomes. Cluster 1 (n = 526, 63.8%) was a late-onset phenotype, cluster 2 (n = 97, 11.8%) was an early-onset phenotype, and cluster 3 (n = 202, 24.5%) was a phenotype with fewer eosinophils and more comorbidities. Clusters 2 and 3 had an elevated risk of death (relative ratio [RRadj], 18.10 and 19.17, respectively) and mechanical ventilation (RRadj, 2.56 and 5.71, respectively) than did cluster 1. Individuals in cluster 3 had an extended length of hospital stay (11 days), increased hospitalization direct costs (13,481.57 Chinese Yuan), and a higher risk of ICU admission (RRadj, 2.14) than individuals in clusters 1 and 2. The decision tree assigned 90.8% of the participants correctly. We identified 3 phenotypes with differential clinical and inflammatory characteristics associated with in-hospital adverse outcomes. These new phenotypes might have important and clinically relevant implications for the management of patients hospitalized for AEs." @default.
- W3091312314 created "2020-10-08" @default.
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- W3091312314 date "2021-02-01" @default.
- W3091312314 modified "2023-10-10" @default.
- W3091312314 title "Clinical Phenotypes of Patients Hospitalized for an Asthma Exacerbation: Prognostic Implications" @default.
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- W3091312314 doi "https://doi.org/10.1016/j.jaip.2020.09.031" @default.
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