Evidence map›Paper›PMID 42305336›Full record

ArticleArchives of medical science : AMS2026

Exploring the association between asthma and frailty: a cross-sectional and a bidirectional Mendelian randomization study.

Shufei Peng, Huanxian Liu, Xianfeng Ren, Lijuan Guo, Shuai Li, Xiaohai Xu, Meikui Wu, Yi Tian, Bing Mu, Ruihang Chai and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Archives of medical science : AMS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Shufei PengDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Huanxian LiuDepartment of Neurology, Chinese PLA General Hospital, Beijing, China.
Xianfeng RenDepartment of Anesthesiology, China-Japan Friendship Hospital, Beijing, China.
Lijuan GuoDepartment of Lung Transplantation, China-Japan Friendship Hospital, Beijing, China.
Shuai LiDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiaohai XuDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Meikui WuDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yi TianDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Bing MuDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ruihang ChaiDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Zhixing GuoDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiaoyan LiuDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Hui ZhengDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Cheng NiDepartment of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Observational studies suggest a potential association between asthma and frailty, but the causal relationship remains unclear. This study aimed to explore this association and determine its causal nature, with implications for targeted interventions that could improve patient management and quality of life. Material and methods: This study analyzed cross-sectional data from the National Health and Nutrition Examination Survey and included 29,589 participants. Multivariate logistic regression was used to assess the association between asthma and frailty, with propensity score matching for reliability. Bidirectional Mendelian randomization (MR) was used, with genetic variants associated with asthma and frailty obtained from the FinnGen database and a large GWAS meta-analysis. Causal effects were estimated using inverse variance weighting, with sensitivity analyses for robustness. Results: Cross-sectional analysis found a significant association between asthma and frailty (OR = 2.16; 95% CI: 2.01-2.31; Conclusions: This study suggests a bidirectional causal association between asthma and frailty. Routine screening for frailty in asthma patients is recommended, and further research is needed to explore the underlying mechanisms.

Indexed as

asthmacausal effectcross-sectional studyfrailtyMendelian randomization

Identifiers

PMID42305336
PMCPMC13266530

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Registered trials

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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.