Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

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

BMC pulmonary medicine - 10 May 2016

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

Abstract excerpt

BACKGROUND: 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...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Adrenal Cortex Hormones
Share to Asthma

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Eosinophils

Share to Longitudinal Studies

Share to Quebec

Share to Respiratory Function Tests

Share to Severity of Illness Index

Share to Sputum

Source

Open in PubMed Open full text

Identifiers

PMID: 27165150
DOI: 10.1186/s12890-016-0232-2
PMCID: PMC4862112

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Phenotyping of difficult asthma using longitudinal physiological and biomarker measurements reveals significant differences in stability between clusters.PMID 27165150Read ↗

Stability of phenotypes defined by physiological variables and biomarkers in adults with asthma.Semantic proximity Read ↗

Statistical cluster analysis of the British Thoracic Society Severe refractory Asthma Registry: clinical outcomes and phenotype stability.Semantic proximity Read ↗

Ten-year follow-up of cluster-based asthma phenotypes in adults. A pooled analysis of three cohorts.Semantic proximity Read ↗

Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study.Semantic proximity Read ↗

Sputum microbiome profiles identify severe asthma phenotypes of relative stability at 12 to 18 monthsSemantic proximity Read ↗

Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications.Semantic proximity Read ↗

Clinical Subtypes of Neutrophilic Asthma: A Cluster Analysis From Australasian Severe Asthma Network.Semantic proximity Read ↗

Heterogeneity of Paucigranulocytic Asthma: A Prospective Cohort Study with Hierarchical Cluster Analysis.Semantic proximity Read ↗

Clustering of patients with severe asthma based on long-term percentage of forced expiratory volume in 1 second (FEV1) changes: Real-world evidence.Semantic proximity Read ↗

Clinical Phenotypes of Difficult-to-treat and Mild Asthma Defined by Cluster AnalysisSemantic proximity Read ↗

Functional phenotypes determined by fluctuation-based clustering of lung function measurements in healthy and asthmatic cohort participants.Semantic proximity Read ↗

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.