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  3. Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study.

Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study.

Fecha de publicación: Fecha Ahead of Print:

Autores de IIS La Fe

Participantes ajenos a IIS La Fe

  • Wang X
  • Villa C
  • Dobarganes Y
  • Olveira C
  • Girón R
  • García-Clemente M
  • Máiz L
  • Sibila O
  • Golpe R
  • Rodríguez-López J
  • Prados C
  • Rodriguez JL
  • de la Rosa D
  • Duran X
  • Garcia-Ojalvo J
  • Barreiro E

Grupos

Abstract

Differential phenotypic characteristics using data mining approaches were defined in a large cohort of patients from the Spanish Online Bronchiectasis Registry (RIBRON). Three differential phenotypic clusters (hierarchical clustering, scikit-learn library for Python, and agglomerative methods) according to systemic biomarkers: neutrophil, eosinophil, and lymphocyte counts, C reactive protein, and hemoglobin were obtained in a patient large-cohort ( n = 1092). Clusters #1-3 were named as mild, moderate, and severe on the basis of disease severity scores. Patients in cluster #3 were significantly more severe (FEV 1 , age, colonization, extension, dyspnea (FACED), exacerbation (EFACED), and bronchiectasis severity index (BSI) scores) than patients in clusters #1 and #2. Exacerbation and hospitalization numbers, Charlson index, and blood inflammatory markers were significantly greater in cluster #3 than in clusters #1 and #2. Chronic colonization by Pseudomonas aeruginosa and COPD prevalence were higher in cluster # 3 than in cluster #1. Airflow limitation and diffusion capacity were reduced in cluster #3 compared to clusters #1 and #2. Multivariate ordinal logistic regression analysis further confirmed these results. Similar results were obtained after excluding COPD patients. Clustering analysis offers a powerful tool to better characterize patients with bronchiectasis. These results have clinical implications in the management of the complexity and heterogeneity of bronchiectasis patients.

Datos de la publicación

ISSN/ISSNe:
2227-9059, 2227-9059

Biomedicines  MDPI AG

Tipo:
Article
Páginas:
-
PubMed:
35203435
Factor de Impacto:
0,874 SCImago ℠
Cuartil:
Q1 SCImago ℠

Citas Recibidas en Web of Science: 4

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Keywords

  • C reactive protein, blood neutrophil, clinical outcomes, disease severity scores, eosinophil, hemoglobin, hierarchical clustering, lymphocyte counts, multivariate analyses, non-cystic fibrosis bronchiectasis, phenotypic clusters

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