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Updated: Feb 2, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Cluster analysis identifying patients with COPD at high risk of 2-year all-cause mortality
Antenor Rodrigues1,2, Carlos Augusto Camillo1, Karina Couto Furlanetto1,3
11 Laboratory of Research in Respiratory Physiotherapy (LFIP), Universidade Estadual de Londrina (UEL), Londrina, Brazil.
Abstract:
The objective of the article is to identify clusters of patients with COPD according to factors known to be associated with mortality and to verify whether clusters' assignment is associated with 2-year mortality. Patients ( n = 141) were evaluated by bioelectrical impedance, maximal inspiratory pressure (MIP), one-repetition maximum test of the quadriceps femoris (1RMQF) and BODE index (body mass index; airflow obstruction (spirometry); dyspnea (modified Medical Research Council scale); and exercise capacity (6-minute walk test (6MWT) distance). Vital status was retrospectively checked 2 years after the assessments, and time to death was quantified for those deceased in this period. K-means analysis identified two clusters. Patients in cluster one (CL I, n = 69) presented an impaired clinical status in comparison to cluster two (CL II, n = 72). Receiver operating characteristics curves identified the cutoffs discriminating patients composing CL I: forced expiratory volume in the first second <44%pred; 6MWT <479 m; 1RMQF <19 kg; and maximum inspiratory pressures <73 cmH2O (area under the curve range 0.750-0.857). During the follow-up, 19 (13%) patients deceased, 15 in CL I (22%) and 4 in CL II (0.06%) ( p = 0.005). CL I was associated with a higher risk of 2-year mortality (hazard ratio (95% confidence interval): 4.3 (1.40-12.9), p = 0.01). A cluster of patients with COPD highly associated with 2-year mortality was statistically identified, and cutoffs to identify these subjects were provided.
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