ArticleJournal of thoracic disease2025
16S rRNA sequencing-based analysis of sputum microbiome in patients with acute exacerbations of chronic obstructive pulmonary disease: retrospective cohort study.
Article in Journal of thoracic disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global research trends and thematic evolution of respiratory microbiota in COPD: a bibliometric study.Frontiers in medicine · 2026Pooled it
- Construction and Validation of a Machine Learning Model Based on Clinical and Microbiomic Features for Predicting High Mucus Secretion in COPD.International journal of chronic obstructive pulmonary disease · 2026Article
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4 authors.
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Abstract
Background: Chronic obstructive pulmonary disease (COPD) is characterized mainly by persistent airflow limitation. Its acute exacerbation of COPD (AECOPD) significantly accelerates the progression of the disease. Current studies have shown that dysregulation of the airway microbiota may be related to the occurrence of AECOPD. However, the dynamic changes of the microbiota in sputum during AECOPD and their correlations with clinical indicators still need to be further clarified. This study aimed to investigate sputum microbiome characteristics and differences between healthy people and patients with AECOPD, and to analyse the correlation between the microecological structural characteristics of the sputum of AECOPD patients and clinical indicators. Methods: A total of 35 sputum samples from patients with AECOPD, 13 sputum samples from patients in the recovery stage, and 20 sputum samples from healthy controls were collected. The 16S ribosomal RNA (rRNA) sequencing method was used to analyse the differences in respiratory microecology. The characteristics of sputum microbiome in healthy people and patients with AECOPD were revealed through the analysis of alpha diversity, beta diversity, and linear discriminant analysis (LDA) effect size (LEfSe) differences. Results: Sputum microbiome structures were differences between COPD patients and healthy population. Compared with the healthy control group, the diversity and abundance of AECOPD patients and the recovery group was significantly reduced. The dominant phyla in the AECOPD group are the Conclusions: Our study reveals changes in the sputum microbiome of AECOPD and analyses its correlation with clinical indicators. The results suggested that ecological dysregulation of the microbiota may contribute to disease progression. This study contributes potential microbial biomarkers that could aid in the diagnosis of AECOPD.
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