Portal de investigación
Multi-level differential network analysis of COPD exacerbations
Fecha de publicación:
Autores de IIS La Fe
Participantes ajenos a IIS La Fe
- Noell, G
- Cosio, BG
- Faner, R
- Monso, E
- Peces-Barba, G
- Esteban, C
- Gea, J
- Rodriguez-Roisin, R
- Garcia-Nunez, M
- Pozo-Rodriguez, F
- Kalko, SG
- Agusti, A
Grupos
Abstract
Patients with chronic obstructive pulmonary disease (COPD) often suffer episodes of exacerbation (ECOPD) that impact negatively the course of their disease. ECOPD are heterogeneous events of unclear pathobiology and non-specific diagnosis. Network analysis is a novel research approach that can help unravelling complex biological systems. We hypothesised that the comparison of multi-level (i.e., clinical, physiological, biological, imaging and microbiological) correlation networks determined during ECOPD and convalescence can yield novel patho-biologic information. In this proof-of-concept study we included 86 patients hospitalised because of ECOPD in a multicentre study in Spain. Patients were extensively characterised both during the first 72 h of hospitalisation and during clinical stability, at least 3 months after hospital discharge. We found that 1) episodes of ECOPD are characterised by disruption of the network correlation observed during convalescence; and 2) a panel of biomarkers that include increased levels of dyspnoea, circulating neutrophils and C-reactive protein (CRP) has a high predictive value for ECOPD diagnosis (AUC 0.97). We conclude that ECOPD 1) are characterised by disruption of network homeokinesis that exists during convalescence; and 2) can be identified objectively by using a panel of three biomarkers (dyspnoea, circulating neutrophils and CRP levels) frequently determined in clinical practice.
Datos de la publicación
- ISSN/ISSNe:
- 0903-1936, 1399-3003
- Tipo:
- Article
- Páginas:
- -
- PubMed:
- 28954781
- Factor de Impacto:
- 3,788 SCImago ℠
- Cuartil:
- Q1 SCImago ℠
EUROPEAN RESPIRATORY JOURNAL EUROPEAN RESPIRATORY SOC JOURNALS LTD
Citas Recibidas en Web of Science: 39
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