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Phenotyping of difficult asthma using longitudinal physiological and biomarker measurements reveals significant differences in stability between clusters

Overview of attention for article published in BMC Pulmonary Medicine, May 2016
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Title
Phenotyping of difficult asthma using longitudinal physiological and biomarker measurements reveals significant differences in stability between clusters
Published in
BMC Pulmonary Medicine, May 2016
DOI 10.1186/s12890-016-0232-2
Pubmed ID
Authors

T. Zaihra, C. J. Walsh, S. Ahmed, C. Fugère, Q. A. Hamid, R. Olivenstein, J. G. Martin, A. Benedetti

Abstract

Although the heterogeneous nature of asthma has prompted asthma phenotyping with physiological or biomarker data, these studies have been mostly cross-sectional. Longitudinal studies that assess the stability of phenotypes based on a combination of physiological, clinical and biomarker data are currently lacking. Our objective was to assess the longitudinal stability of clusters derived from repeated measures of airway and physiological data over a 1-year period in moderate and severe asthmatics. A total of 125 subjects, 48 with moderate asthma (MA) and 77 with severe asthma (SA) were evaluated every 3 months and monthly, respectively, over a 1-year period. At each 3-month time point, subjects were grouped into 4 asthma clusters (A, B, C, D) based on a combination of clinical (duration of asthma), physiological (FEV1 and BMI) and biomarker (sputum eosinophil count) variables, using k-means clustering. Majority of subjects in clusters A and C had severe asthma (93 % of subjects in cluster A and 79.5 % of subjects in cluster C at baseline). Overall, a total of 59 subjects (47 %) had stable cluster membership, remaining in clusters with the same subjects at each evaluation time. Cluster A was the least stable (21 % stability) and cluster B was the most stable cluster (71 % stability). Cluster stability was not influenced by changes in the dosage of inhaled corticosteroids. Asthma phenotyping based on clinical, physiologic and biomarker data identified clusters with significant differences in longitudinal stability over a 1-year period. This finding indicates that the majority of patients within stable clusters can be phenotyped with reasonable accuracy after a single measurement of lung function and sputum eosinophilia, while patients in unstable clusters will require more frequent evaluation of these variables to be properly characterized.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 21%
Student > Bachelor 5 18%
Student > Master 3 11%
Researcher 2 7%
Librarian 1 4%
Other 4 14%
Unknown 7 25%
Readers by discipline Count As %
Medicine and Dentistry 9 32%
Nursing and Health Professions 4 14%
Immunology and Microbiology 2 7%
Agricultural and Biological Sciences 2 7%
Biochemistry, Genetics and Molecular Biology 2 7%
Other 2 7%
Unknown 7 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 May 2016.
All research outputs
#6,653,300
of 7,690,302 outputs
Outputs from BMC Pulmonary Medicine
#523
of 616 outputs
Outputs of similar age
#224,063
of 268,158 outputs
Outputs of similar age from BMC Pulmonary Medicine
#32
of 42 outputs
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