e-learning
resources
Virtual 2020
Pre-Congress Content
Clinical data and COPD management
Login
Search all ERS
e-learning
resources
Disease Areas
Airways Diseases
Interstitial Lung Diseases
Respiratory Critical Care
Respiratory Infections
Paediatric Respiratory Diseases
Pulmonary Vascular Diseases
Sleep and Breathing Disorders
Thoracic Oncology
Events
International Congress
Courses
Webinars
Conferences
Research Seminars
Journal Clubs
Publications
Breathe
Monograph
ERJ
ERJ Open Research
ERR
European Lung White Book
Handbook Series
Guidelines
All ERS guidelines
e-learning
CME Online
Case reports
Short Videos
SpirXpert
Procedure Videos
CME tests
Reference Database of Respiratory Sounds
Radiology Image Challenge
Brief tobacco interventions
EU Projects
VALUE-Dx
ERN-LUNG
ECRAID
UNITE4TB
Disease Areas
Events
Publications
Guidelines
e-learning
EU Projects
Login
Search
Stratifying COPD patients by cluster analysis using clinical and behavioral variables
C. van Zelst (Rotterdam, Netherlands), L. Goossens (Rotterdam, Netherlands), M. Rutten- Van Molken (Rotterdam, Netherlands), J. In 'T Veen (Rotterdam, Netherlands)
Source:
Virtual Congress 2020 – Clinical data and COPD management
Session:
Clinical data and COPD management
Session type:
E-poster session
Number:
1004
Disease area:
Airway diseases
Rating:
You must
login
to grade this presentation.
Share or cite this content
Citations should be made in the following way:
C. van Zelst (Rotterdam, Netherlands), L. Goossens (Rotterdam, Netherlands), M. Rutten- Van Molken (Rotterdam, Netherlands), J. In 'T Veen (Rotterdam, Netherlands). Stratifying COPD patients by cluster analysis using clinical and behavioral variables. 1004
You must
login
to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.
Member's Comments
No comment yet.
You must
Login
to comment this presentation.
Related content which might interest you:
The Relationship Between Functional Status and Fatigue After COVID-19 Infection
Late Breaking Abstract - Implications of treatable traits and treatment choices on exacerbation risk in moderate-severe asthma
Observational cohort study of pulmonary exacerbations in alpha-1 antitrypsin deficiency
Related content which might interest you:
Identification of clinical phenotypes using cluster analyses in COPD patients
Source: International Congress 2019 – Phenotypes and comorbidities of airway diseases
Year: 2019
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
Comparison of sputum characteristics with clinical, laboratorial and functional variables in patients with stable COPD
Source: Annual Congress 2010 - Colonisation and infection in COPD
Year: 2010
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
Dealing with missing longitudinal FEV1 observations when used as time-dependent covariate data in survival analysis for COPD patients within a regional UK population-level database
Source: International Congress 2015 – Epidemiology of respiratory disease
Year: 2015
Cluster analysis and clinical asthma phenotypes
Source: Annual Congress 2013 –Severe asthma: moving from phenotyping to endotyping
Year: 2013
Longitudinal validation of clinical COPD phenotypes identified by cluster analysis
Source: Annual Congress 2011 - COPD diagnosis
Year: 2011
IPF cluster analysis highlights diagnostic delay and cardiovascular comorbidities association with outcome
Source: Virtual Congress 2021 – Interstitial lung disease around the world
Year: 2021
The relationship of comorbidities with clinical and phsyiological parameters in COPD
Source: Annual Congress 2012 - COPD comorbidities II
Year: 2012
The superexacerbator phenotype in patients with COPD: a descriptive analysis
Source: ERJ Open Res, 5 (2) 00235-2018; 10.1183/23120541.00235-2018
Year: 2019
Clinical characteristics and outcomes of elderly patients with COPD: TIOSPIR® post-hoc analysis
Source: International Congress 2016 – Novel avenues in the treatment of COPD II
Year: 2016
Sex differences in COPD outcome in 5,355 women with COPD: A new analysis of the 3CIA study
Source: Virtual Congress 2020 – Phenotypes of obstructive diseases
Year: 2020
Clinical COPD phenotypes identified by cluster analysis: validation with mortality
Source: Eur Respir J 2012; 40: 495-496
Year: 2012
Stability of serum biomarkers and their associations with clinical outcomes in COPD patients and controls: a longitudinal study
Source: Annual Congress 2009 - Biomarkers and biology in COPD
Year: 2009
BREATHE – Distribution and co-expression of T2 biomarkers in asthma and association with severity, clinical characteristics and co-morbidities
Source: Virtual Congress 2021 – Severe asthma: evaluation using patient-reported outcome measures (PROMs) and biomarkers, comorbidities and treatments
Year: 2021
Comparison of prognostic significance of the quality of life questionnaires in patients with COPD combined with hypertension
Source: Virtual Congress 2020 – Clinical data and COPD management
Year: 2020
How to predict COPD in a clinical setting
Source: Annual Congress 2005 - New strategies and drugs for smoking cessation
Year: 2005
Patient baseline variables predict future asthma control status and risk of exacerbations
Source: Annual Congress 2010 - Management of airway disease
Year: 2010
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
COPD characteristics and progression of patients with high vs low health status: an analysis of the observational DACCORD study
Source: International Congress 2019 – COPD treatment: cohorts and real-world studies
Year: 2019
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking "Accept", you consent to the use of the cookies.
Accept