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Multimorbidity networks of chronic obstructive pulmonary disease and heart failure in men and women: Evidence from the EpiChron Cohort

Published: January 1, 2021
Category: Bibliography
Authors: Alexandra Prados-Torres, Antonio Gimeno-Miguel, Beatriz Poblador-Plou, Ignatios Loakeim-Skoufa, Jesús Díez-Manglano, Jonás Carmona-Pírez, Jose Maria Marin Trigo, Manuel Jesus Morillo-Jimenez
Country: Spain
Language: English
Types: Care Management, chronic condition, Population Health
Settings: Government, Province

Abstract

Objective

Patients with heart failure (HF) and/or chronic obstructive pulmonary disease (COPD) constitute a complex population with different phenotypes based on pathophysiology, comorbidity, sex and age. We aimed to compare the multimorbidity patterns of HF and COPD in men and women using network analysis.

Methods

Individuals aged 40 years or older on 2015 of the EpiChron Cohort (Aragon, Spain) were stratified by sex and as having COPD (n = 28,608), HF (n = 13,414), or COPD and HF (n = 3952). We constructed one network per group by obtaining age-adjusted phi correlations between comorbidities. For each sex, networks differed between the three study groups; between sexes, similarities were found for the two HF groups.

Results

We detected some specific diseases highly connected in all networks (e.g., cardio-metabolic, respiratory diseases, and chronic kidney failure), and some others that were group-specific that would require further study. We identified common clusters (i.e., cardio-metabolic, cardiovascular, cancer, and neuro-psychiatric) and others specific and clinically relevant in COPD patients (e.g., behavioral risk disorders were systematically associated with psychiatric diseases in women and cancer in men).

Conclusion

Network analysis represents a powerful tool to analyze, visualize, and compare the multimorbidity patterns of COPD and HF, also facilitated by developing an ad hoc website.

chronic obstructive pulmonary disease,heart failure,multimorbidity,network analysis,real world data

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