Evidence map›Paper›PMID 36714050›Full record

ArticleJournal of asthma and allergy2023

Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study.

Hung-Ling Huang, Ying-Jhen Huang, Yi-Chi Chu, Chia-Wei Chen, Hsin-Chou Yang, Jing-Shiang Hwang, Chun-Houh Chen, Ta-Chien Chan

Open access · goldAbstract read
In one paragraph

Article in Journal of asthma and allergy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

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

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Hung-Ling Huang *Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan.
Ying-Jhen Huang *Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan.ORCID 0000-0001-9387-2593
Yi-Chi ChuResearch Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan.
Chia-Wei ChenInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Hsin-Chou YangInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Jing-Shiang HwangInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.
Chun-Houh ChenInstitute of Statistical Science, Academia Sinica, Taipei, Taiwan.ORCID 0000-0003-0899-7477
Ta-Chien ChanResearch Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan.ORCID 0000-0002-1685-783X
Institute of Statistical Science, Academia Sinica · TWResearch Center for Humanities and Social Sciences, Academia Sinica · TWKaohsiung Medical University · TWNational Yang Ming Chiao Tung University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Uncontrolled asthma in adults leads to poor clinical outcome, while the clinical heterogeneity of phenotypes interferes the applicable genetic determinants. This study aimed to identify phenotypes and genetic impact on poorly-controlled asthma to optimize individualized treatment strategies. Methods: This propensity score-matched case-control study included 340 and 1020 asthmatics with poorly-controlled asthma and well-controlled asthma, respectively. Data were obtained from the 2008-2015 Taiwan Biobank Database and linked to the National Health Insurance Research Database. All asthmatics were aged ≥30 years, without cancer history, and each completed a questionnaire, physical examination, and genome-wide single nucleotide polymorphisms (SNPs). Multivariate adjusted odds ratios (ORs) for genetic risk scores were calculated using conditional logistic regression, stratified by age and sex. A model integrating obesity- and asthma-associated phenotypes and genotypes was applied for poorly-controlled asthma risk prediction. Results: General obesity with body mass index (BMI) ≥27 kg/m Conclusion: The prediction model integrating obesity-asthma phenotypes and genotypes for poorly-controlled asthma can facilitate the prediction of high-risk asthma and provide potential targets for novel treatment.

Indexed as

biobankbiomarkergenetic scoreobesitypoorly-controlled asthma

Identifiers

PMID36714050
PMCPMC9875574
OpenAlexW4317538692

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.