Cluster features in fibrosing interstitial lung disease and associations with prognosis.

ABSTRACT:

Background

Clustering is helpful in identifying subtypes in complex fibrosing interstitial lung disease (F-ILD) and associating them with prognosis at an early stage of the disease to improve treatment management. We aimed to identify associations between clinical characteristics and outcomes in patients with F-ILD.

Methods

Retrospectively, 575 out of 926 patients with F-ILD were eligible for analysis. Four clusters were identified based on baseline data using cluster analysis. The clinical characteristics and outcomes were compared among the groups.

Results

Cluster 1 was characterized by a high prevalence of comorbidities and hypoxemia at rest, with the worst lung function at baseline; Cluster 2 by young female patients with less or no smoking history; Cluster 3 by m

SUBMITTER: Wang Y 

PROVIDER: S-EPMC10621076 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature