A non-invasive simplified scoring system to predict airway mucus plugs in asthma.
9 affiliations
- 1Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
- 2National Health Commission Key Laboratory of Respiratory Diseases, Hubei Provincial Clinical Research Center for Chronic Airway Inflammatory Diseases, Wuhan, China.
- 3Department of General Practice, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- 4Key Laboratory of Respiratory Disease of Zhejiang Province, Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
- 5State Key Laboratory of Respiratory Disease, National Center for Respiratory Medicine, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
- 6Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. [email protected].
- 7National Health Commission Key Laboratory of Respiratory Diseases, Hubei Provincial Clinical Research Center for Chronic Airway Inflammatory Diseases, Wuhan, China. [email protected].
- 8Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. [email protected].
- 9National Health Commission Key Laboratory of Respiratory Diseases, Hubei Provincial Clinical Research Center for Chronic Airway Inflammatory Diseases, Wuhan, China. [email protected].
Abstract
Background
Airway mucus plugs are a core pathological feature of severe asthma and are closely associated with airflow limitation and poor prognosis. However, rapid and efficient clinical screening tools for identifying airway mucus plugs in asthma are currently lacking.Objective
This study aimed to develop and evaluate meta‑analysis‑weighted scores for estimating the presence and severity of airway mucus plugs in adults with asthma.Methods
A systematic review and meta-analysis of six major databases (up to February 2025) were conducted to identify significant risk factors for mucus plugs. Subsequently, a mathematical equation-based score and a simplified scoring system were constructed based on the converted standardized effect-size weights (β). Internal validation of the scoring system was then performed using a cohort of 105 asthma patients from Tongji Hospital, Huazhong University of Science and Technology (2024∼2026).Results
The meta-analysis included 10 studies (837 patients) and identified age, pulmonary function parameters (FEV₁%, FVC%, FEV₁/FVC%), and type 2 inflammatory markers (FeNO, blood eosinophil count, IgE) as key associated factors. In the internal validation cohort, the simplified scoring system showed an AUC of 0.864 (95% CI: 0.785-0.943) for estimating mucus plug presence, with a specificity of 0.941 and sensitivity of 0.718. For estimating higher mucus plug burden, the AUC was 0.859 (95% CI: 0.777-0.941), with a sensitivity of 0.917 and specificity of 0.684.Conclusion
The meta-analysis-weighted scores showed promising preliminary discrimination for mucus plug presence and higher burden. These scores may assist in prioritizing patients for HRCT, though external validation is required.
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BibTeX
@article{wang2026noninvasive,
title = {{A non-invasive simplified scoring system to predict airway mucus plugs in asthma.}},
author = {Zhen Wang and Tiantian Xiong and Gongqi Chen and Chunli Huang and Wei Gu and Huiru Jie and Lixia Xia and Ruchong Chen and Yuchen Feng and Guohua Zhen},
journal = {BMC pulmonary medicine},
year = {2026},
month = aug,
doi = {10.1186/s12890-026-04560-0},
url = {https://europepmc.org/article/MED/42958132},
note = {CC BY},
}
RIS
TY - JOUR
TI - A non-invasive simplified scoring system to predict airway mucus plugs in asthma.
AU - Zhen Wang
AU - Tiantian Xiong
AU - Gongqi Chen
AU - Chunli Huang
AU - Wei Gu
AU - Huiru Jie
AU - Lixia Xia
AU - Ruchong Chen
AU - Yuchen Feng
AU - Guohua Zhen
PY - 2026
DA - 2026/08/04
JO - BMC pulmonary medicine
DO - 10.1186/s12890-026-04560-0
UR - https://europepmc.org/article/MED/42958132
AB - Background Airway mucus plugs are a core pathological feature of severe asthma and are closely associated with airflow limitation and poor prognosis. However, rapid and efficient clinical screening tools for identifying airway mucus plugs in asthma are currently lacking.Objective This study aimed to develop and evaluate meta‑analysis‑weighted scores for estimating the presence and severity of airway mucus plugs in adults with asthma.Methods A systematic review and meta-analysis of six major databases (up to February 2025) were conducted to identify significant risk factors for mucus plugs. Subsequently, a mathematical equation-based score and a simplified scoring system were constructed based on the converted standardized effect-size weights (β). Internal validation of the scoring system was then performed using a cohort of 105 asthma patients from Tongji Hospital, Huazhong University of Science and Technology (2024∼2026).Results The meta-analysis included 10 studies (837 patients) and identified age, pulmonary function parameters (FEV₁%, FVC%, FEV₁/FVC%), and type 2 inflammatory markers (FeNO, blood eosinophil count, IgE) as key associated factors. In the internal validation cohort, the simplified scoring system showed an AUC of 0.864 (95% CI: 0.785-0.943) for estimating mucus plug presence, with a specificity of 0.941 and sensitivity of 0.718. For estimating higher mucus plug burden, the AUC was 0.859 (95% CI: 0.777-0.941), with a sensitivity of 0.917 and specificity of 0.684.Conclusion The meta-analysis-weighted scores showed promising preliminary discrimination for mucus plug presence and higher burden. These scores may assist in prioritizing patients for HRCT, though external validation is required.
SN - 1471-2466
ER -