Unsupervised Phenotyping of Asthma: Integrating Serum Periostin with Clinical and Inflammatory Profiles.

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

4 citing papers in PubMed.

1. Respiratory Biomarkers: An Opportunity for Patient-Centric Microsampling Approach for Treatment Optimization.Clinical and translational science · 2026
   Review
2. The Architecture of Deep Phenotyping in Asthma: Integrating Molecular, Metabolic, and Neuro-Hormonal Endotypes.International journal of molecular sciences · 2026
   Review
3. Prediction of early responses to dupilumab treatment in patients with moderate-to-severe atopic dermatitis by a machine learning model integrating clinical characteristics and serum biomarkers.Postepy dermatologii i alergologii · 2026
   Article
4. Melatonin: a promising therapy to combat type 2 airway inflammation via MT1-Sirt1 pathway.Frontiers in pharmacology · 2026
   Article

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

Authors and funding

17 authors.

Funding

No grant is acknowledged in the PubMed record.

Abstract

PubMed holds no abstract for this paper.

Indexed as