ArticleClinical and translational medicine2017
Proteomics in asthma: the clinicians were right after all, were not they?
Article in Clinical and translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Response of patients with chest tightness variant asthma with routine asthma treatment regimen: A 1-year multicenter, prospective, real-world study.Clinical and translational medicine · 2020Article
- The application of proteomics in the diagnosis and treatment of bronchial asthma.Annals of translational medicine · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Clinical disease phenotypes with underlying information of molecular and biological signatures for the same, is a prerequisite for improving medical care and developing more effective, stratified management strategies. This commentary reviews the research carried out by Cao et al. to unravel biological networks associated with different clinical categories of asthma. It finally comments on the utility of using data from multiple platforms aided by integrated systems approaches to effectively find out the obvious underlying physiological disease signatures related to clinical disease sub-types.
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.