ArticleAllergy, asthma & immunology research2017
Clinical Characteristics of Exacerbation-Prone Adult Asthmatics Identified by Cluster Analysis.
Article in Allergy, asthma & immunology research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 26 citations in OpenAlex.
- Severe Asthma Exacerbations: From Risk Factors to Precision Management Strategies.Journal of clinical medicine · 2026Review
- Unsupervised Phenotyping of Asthma: Integrating Serum Periostin with Clinical and Inflammatory Profiles.Diagnostics (Basel, Switzerland) · 2025Article
- Computational Phenotyping of Obstructive Airway Diseases: A Systematic Review.Journal of asthma and allergy · 2025Review
- Development and validation of a Multi-Causal investigation and discovery framework for knowledge harmonization (MINDMerge): A case study with acute kidney injury risk factor discovery using electronic medical records.International journal of medical informatics · 2024Article
- A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection.JMIR medical informatics · 2024Article
- Leptin/obR signaling exacerbates obesity-related neutrophilic airway inflammation through inflammatory M1 macrophages.Molecular medicine (Cambridge, Mass.) · 2023Article
- Association of genetic variants of oxidative stress responsive kinase 1 (OXSR1) with asthma exacerbations in non-smoking asthmatics.BMC pulmonary medicine · 2022Article
- A Systematic Review of Asthma Phenotypes Derived by Data-Driven Methods.Diagnostics (Basel, Switzerland) · 2021Review
- Challenges of Clustering Multimodal Clinical Data: Review of Applications in Asthma Subtyping.JMIR medical informatics · 2020Review
- Innate Lymphoid Cells in the Airways: Their Functions and Regulators.Allergy, asthma & immunology research · 2020Review
- Exacerbation-Prone Asthma.The journal of allergy and clinical immunology. In practice · 2020Article
- Association Between Epithelial Cytokines and Clinical Phenotypes of Elderly Asthma.Allergy, asthma & immunology research · 2019Article
- Characteristics of Adult Severe Refractory Asthma in Korea Analyzed From the Severe Asthma Registry.Allergy, asthma & immunology research · 2019Article
- Obesity-Associated Metabolic Signatures Correlate to Clinical and Inflammatory Profiles of Asthma: A Pilot Study.Allergy, asthma & immunology research · 2018Article
- Effective Strategies for Managing Asthma Exacerbations for Precision Medicine.Allergy, asthma & immunology research · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeAsthma is a heterogeneous disease characterized by various types of airway inflammation and obstruction. Therefore, it is classified into several subphenotypes, such as early-onset atopic, obese non-eosinophilic, benign, and eosinophilic asthma, using cluster analysis. A number of asthmatics frequently experience exacerbation over a long-term follow-up period, but the exacerbation-prone subphenotype has rarely been evaluated by cluster analysis. This prompted us to identify clusters reflecting asthma exacerbation.
methodsA uniform cluster analysis method was applied to 259 adult asthmatics who were regularly followed-up for over 1 year using 12 variables, selected on the basis of their contribution to asthma phenotypes. After clustering, clinical profiles and exacerbation rates during follow-up were compared among the clusters.
resultsFour subphenotypes were identified: cluster 1 was comprised of patients with early-onset atopic asthma with preserved lung function, cluster 2 late-onset non-atopic asthma with impaired lung function, cluster 3 early-onset atopic asthma with severely impaired lung function, and cluster 4 late-onset non-atopic asthma with well-preserved lung function. The patients in clusters 2 and 3 were identified as exacerbation-prone asthmatics, showing a higher risk of asthma exacerbation.
conclusionsTwo different phenotypes of exacerbation-prone asthma were identified among Korean asthmatics using cluster analysis; both were characterized by impaired lung function, but the age at asthma onset and atopic status were different between the two.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.