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Related Concept Videos

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Chronic Obstructive Pulmonary Disease01:24

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COPD is defined as a heterogeneous lung condition marked by persistent respiratory symptoms such as dyspnea, cough, and sputum production, caused by abnormalities in the airways that cause airflow obstruction.
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Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
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Multi-level differential network analysis of COPD exacerbations.

Guillaume Noell1,2,3, Borja G Cosío1,4,3, Rosa Faner1,2,3

  • 1CIBER Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Barcelona, Spain.

The European Respiratory Journal
|September 29, 2017
PubMed
Summary
This summary is machine-generated.

Episodes of chronic obstructive pulmonary disease (COPD) exacerbations disrupt normal biological networks. A simple biomarker panel including dyspnea, neutrophils, and C-reactive protein (CRP) can effectively diagnose these events.

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Area of Science:

  • Pulmonary Medicine
  • Systems Biology
  • Biomarker Discovery

Background:

  • Chronic obstructive pulmonary disease (COPD) exacerbations (ECOPD) significantly worsen disease progression.
  • ECOPD are heterogeneous with unclear pathobiology and non-specific diagnostic criteria.
  • Network analysis offers a novel approach to understanding complex biological systems.

Purpose of the Study:

  • To investigate the utility of comparing multi-level correlation networks during ECOPD versus convalescence.
  • To identify novel pathobiological insights into ECOPD using network analysis.
  • To evaluate a panel of biomarkers for objective ECOPD diagnosis.

Main Methods:

  • A multicenter, proof-of-concept study involving 86 hospitalized ECOPD patients in Spain.
  • Comprehensive patient characterization during the first 72 hours of hospitalization and during clinical stability (≥3 months post-discharge).
  • Multi-level correlation network analysis (clinical, physiological, biological, imaging, microbiological) during ECOPD and convalescence.

Main Results:

  • ECOPD episodes are characterized by a disruption of the correlation network observed during convalescence.
  • A diagnostic panel comprising dyspnea, circulating neutrophils, and C-reactive protein (CRP) demonstrated high predictive value for ECOPD (AUC 0.97).
  • Network disruption indicates a loss of homeokinesis during ECOPD compared to stable periods.

Conclusions:

  • ECOPD are associated with a disruption of network homeokinesis present during convalescence.
  • A readily available biomarker panel (dyspnea, neutrophils, CRP) can objectively identify ECOPD.
  • This approach offers a promising tool for the objective diagnosis and understanding of ECOPD.