ArticleScientific reports2024
Deciphering the lung microbiota in COVID-19 patients: insights from culture analysis, FilmArray pneumonia panel, ventilation impact, and mortality trends.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- No difference in microbial diversity between bronchoalveolar lavage and tracheal sampling: a systematic review and meta-analysis.BMJ open respiratory research · 2025Pooled it
- Impact of Invasive Mechanical Ventilation on the Lung Microbiome.Advances in respiratory medicine · 2025Pooled it
- The Role of the Respiratory Microbiome in Pneumonia.Clinics in chest medicine · 2026Review
- Epidemiological characteristics and co-occurrence patterns ofJournal of oral microbiology · 2026Article
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Few studies have analyzed the role of the lung microbiome in the diagnosis of pulmonary coinfection in ventilated ICU COVID-19 patients. We characterized the lung microbiota in COVID-19 patients with severe pneumonia on invasive mechanical ventilation using full-length 16S rRNA gene sequencing and established its relationship with coinfections, mortality, and the need for mechanical ventilation for more than 7 days. This study included 67 COVID-19 ICU patients. DNA extracted from mini-bronchoalveolar lavage fluid and endotracheal aspirates was amplified by PCR with specific 16S primers (27F and 1492R). General and relative bacterial abundance analysis was also conducted. Alpha diversity was measured by the Shannon and Simpson indices, and differences in the microbiota were established using beta diversity. A linear discriminant analysis (LDA) effect size algorithm was implemented to describe biomarkers. Streptococcus spp. represented 51% of the overall microbial abundance. There were no differences in alpha diversity between the analyzed variables. There was variation in bacterial composition between samples that had positive and negative cultures. The genera Veillonella sp., Granulicatella sp., Enterococcus sp. and Lactiplantibacillus sp., with LDA scores > 2, were biomarkers associated with negative cultures. Rothia sp., with an LDA score > 2, was a biomarker associated with mortality.
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Registered trials
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