Source: Annual Congress 2011 - COPD diagnosis
Disease area: Airway diseases



Rating:

Share or cite this content

Citations should be made in the following way:
P. R. Burgel, J. L. Paillasseur, D. Caillaud, I. Tillie-Leblond, P. Chanez, R. Escamilla, I. Court-Fortune, T. Perez, P. Carré, N. Roche (Paris, France). Longitudinal validation of clinical COPD phenotypes identified by cluster analysis. Eur Respir J 2011; 38: Suppl. 55, 3562

Member's Comments

No comment yet.

Related content which might interest you: Clinical COPD phenotypes identified by cluster analysis: validation with mortality Source: Eur Respir J 2012; 40: 495-496 Year: 2012 Identification of clinical phenotypes using cluster analyses in COPD patients Source: International Congress 2019 – Phenotypes and comorbidities of airway diseases Year: 2019 Adult asthma phenotypes identified by a cluster analysis on clinical and biological characteristics Source: International Congress 2018 – Asthma in children and adults: long-term aspects Year: 2018 Cluster analysis and clinical asthma phenotypes Source: Annual Congress 2013 –Severe asthma: moving from phenotyping to endotyping Year: 2013 Identification and analysis of clinical phenotypes in COPD patients: PALOMB Cohort Source: Virtual Congress 2021 – COPD burden, epidemiology and management Year: 2021 Cluster analysis to identify phenotypes in COPD Source: Annual Congress 2009 - Quality of life and symptoms in COPD Year: 2009 Clinical COPD phenotypes: a novel approach using principal component and cluster analyses Source: Eur Respir J 2010; 36: 531-539 Year: 2010 COPD subphenotypes in a population-based survey by factor and cluster analysis Source: Annual Congress 2012 - COPD comorbidities II Year: 2012 A network analysis of clinical characteristics of patients with COPD: partial results. Source: International Congress 2018 – Chronic respiratory disease: effects of rehabilitation interventions in patients Year: 2018 Muscle phenotypes in COPD patients: An exploratory cluster analysis Source: Annual Congress 2012 - The best posters on physical inactivity, muscle dysfunction and exercise intolerance Year: 2012 Identification of asthma phenotypes using cluster analysis Source: International Congress 2018 – Exploring the importance of daily physical activity in chronic respiratory disease Year: 2018 Use of cluster analysis to define COPD phenotypes Source: Eur Respir J 2010; 36: 472-474 Year: 2010 Cluster analysis identifies distinct clinical phenotypes with poor treatment responsiveness in asthma. Source: International Congress 2018 – Asthma: clinical screening tools Year: 2018 COPD phenotypes revealed by the integrated sputum microbiome and proteome analysis in COPDMAP cohort Source: International Congress 2019 – Host-microbe interactions in lung disease and exacerbations Year: 2019 Identification of asthma clusters in two independent Korean adult asthma cohorts Source: Eur Respir J 2013; 41: 1308-1314 Year: 2013 Stratifying COPD patients by cluster analysis using clinical and behavioral variables Source: Virtual Congress 2020 – Clinical data and COPD management Year: 2020 Longitudinal analysis of sarcoidosis blood transcriptomic signatures and disease outcomes Source: Eur Respir J 2014; 44: 985-993 Year: 2014 Cluster analysis of clinical phenotypes of OSA and its implications for comorbidities Source: Virtual Congress 2021 – What is new for sleep apnoea? The European perspective: findings from the European Sleep Apnoea Database (ESADA) Year: 2021 Unsupervised and externally validated clinical cluster analysis from the U-BIOPRED paediatric cohorts Source: International Congress 2018 – Paediatric asthma: new mechanisms and tools Year: 2018 Two phenothypes of severe asthma identified by cluster analysis Source: International Congress 2018 – Clinical markers of asthma Year: 2018