6 research outputs found

    Clinical and inflammatory characteristics of patients with asthma in the Spanish MEGA project cohort

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    Asthma; Inflammation; PhenotypeAsma; Inflamación; FenotiposAsma; Inflamació; FenotipsIntroduction The MEGA (MEchanism underlying the Genesis and evolution of Asthma) project is a multicenter cohort study carried out in eight Spanish hospitals, gathering clinical, physiological, and molecular data from patients with asthma and multimorbidities in order to gain insight into the different physiopathological mechanisms involved in this disorder. Material and Methods We report the baseline clinical and physiological characteristics and biomarker measures of adult participants in the project with the aim of better understanding the natural history and underlying mechanisms of asthma as well as the associated multimorbidities across different levels of severity. We carried out a detailed clinical examination, pulmonary function testing, measurement of fractional exhaled nitric oxide (FeNO), blood counts, induced sputum, skin prick tests, chest computed tomography scan, asthma questionnaires, and multimorbidity assessment in 512 asthmatic patients. Results When compared to patients with milder disease, severe asthmatic patients showed greater presence of symptoms, more exacerbations, lower asthma control, increased airflow obstruction, and higher frequency of chronic rhinosinusitis with nasal polyps, severe rhinitis, anxiety and depression, gastroesophageal reflux, and bronchiectasis. Conclusion The MEGA project succeeded in recruiting a high number of asthma patients, especially those with severe disease, who showed lower control and higher frequency of multimorbidities.This study was supported by Sanofi [02/055], Fondo de Investigación Sanitaria–FIS [PI15/00803], [PI15/01900], the Merck Health Foundation, CIBER de Enfermedades Respiratorias (CIBERES), a Carlos III Institute of Health initiative, and FEDER funds. The authors recognize Oliver Shaw, English editor of IIS-FJD, for his revision and editing of the manuscript, and Ignacio Mahillo-Fernández for statistical revision

    Clinical and inflammatory characteristics of patients with asthma in the Spanish MEGA project cohort

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    Abstract Introduction The MEGA (MEchanism underlying the Genesis and evolution of Asthma) project is a multicenter cohort study carried out in eight Spanish hospitals, gathering clinical, physiological, and molecular data from patients with asthma and multimorbidities in order to gain insight into the different physiopathological mechanisms involved in this disorder. Material and Methods We report the baseline clinical and physiological characteristics and biomarker measures of adult participants in the project with the aim of better understanding the natural history and underlying mechanisms of asthma as well as the associated multimorbidities across different levels of severity. We carried out a detailed clinical examination, pulmonary function testing, measurement of fractional exhaled nitric oxide (FeNO), blood counts, induced sputum, skin prick tests, chest computed tomography scan, asthma questionnaires, and multimorbidity assessment in 512 asthmatic patients. Results When compared to patients with milder disease, severe asthmatic patients showed greater presence of symptoms, more exacerbations, lower asthma control, increased airflow obstruction, and higher frequency of chronic rhinosinusitis with nasal polyps, severe rhinitis, anxiety and depression, gastroesophageal reflux, and bronchiectasis. Conclusion The MEGA project succeeded in recruiting a high number of asthma patients, especially those with severe disease, who showed lower control and higher frequency of multimorbidities

    Identification of Asthma Phenotypes in the Spanish MEGA Cohort Study Using Cluster Analysis

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    Introduction: The definition of asthma phenotypes has not been fully established, neither there are cluster studies showing homogeneous results to solidly establish clear phenotypes. The purpose of this study was to develop a classification algorithm based on unsupervised cluster analysis, identifying clusters that represent clinically relevant asthma phenotypes that may share asthma-related outcomes. Methods: We performed a multicentre prospective cohort study, including adult patients with asthma (N = 512) from the MEGA study (Mechanisms underlying the Genesis and evolution of Asthma). A standardised clinical history was completed for each patient. Cluster analysis was performed using the kernel k-groups algorithm. Results: Four clusters were identified. Cluster 1 (31.5% of subjects) includes adult-onset atopic patients with better lung function, lower BMI, good asthma control, low ICS dose, and few exacerbations. Cluster 2 (23.6%) is made of adolescent-onset atopic asthma patients with normal lung function, but low adherence to treatment (59% well-controlled) and smokers (48%). Cluster 3 (17.1%) includes adult-onset patients, mostly severe non-atopic, with overweight, the worse lung function and asthma control, and receiving combination of treatments. Cluster 4 (26.7%) consists of the elderly-onset patients, mostly female, atopic (64%), with high BMI and normal lung function, prevalence of smokers and comorbidities. Conclusion: We defined four phenotypes of asthma using unsupervised cluster analysis. These clusters are clinically relevant and differ from each other as regards FEV1, age of onset, age, BMI, atopy, asthma severity, exacerbations, control, social class, smoking and nasal polyps

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