ArticlePathogens (Basel, Switzerland)2023
Analysis of Lung Microbiome in COVID-19 Patients during Time of Hospitalization.
Article in Pathogens (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- Review
- Deciphering respiratory viral infections by harnessing organ-on-chip technology to explore the gut-lung axis.Open biology · 2025Review
- Relationship between post-COVID-19 symptoms and daily physical activity.Frontiers in rehabilitation sciences · 2025Article
- Review
- Major alteration of lung microbiome and the host responses in critically ill COVID-19 patients with high viral load.Scientific reports · 2024Article
- Fungal lung disease.The European respiratory journal · 2024Review
- A proposed approach to pulmonary long COVID: a viewpoint.The European respiratory journal · 2024Article
- Microbiome-Mucosal Immunity Nexus: Driving Forces in Respiratory Disease Progression.Journal of microbiology (Seoul, Korea) · 2024Review
- Article
- The Impact of Pulmonary Disorders on Neurological Health (Lung-Brain Axis).Immune network · 2024Review
- Major alteration of Lung Microbiome and the Host Reaction in critically ill COVID-19 Patients with high viral load.Research square · 2024Article
- Typing ofPathogens (Basel, Switzerland) · 2023Article
- Gut microbe-host interactions in post-COVID syndrome: a debilitating or restorative partnership?Gut microbesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the pathogenic agent of the rapidly spreading pneumonia called coronavirus disease 2019 (COVID-19), primarily infects the respiratory and digestive tract. Several studies have indicated the alterations of the bacterial microbiome in the lower respiratory tract during viral infection. However, both bacterial and fungal microbiota in the lung of COVID-19 patients remained to be explored.
methodsIn this study, we conducted nanopore sequencing analyses of the lower respiratory tract samples from 38 COVID-19 patients and 26 non-COVID-19 pneumonia controls. Both bacterial and fungal microbiome diversities and microbiota abundances in the lung were compared.
resultsOur results revealed significant differences in lung microbiome between COVID-19 patients and non-COVID-19 controls, which were strongly associated with SARS-CoV-2 infection and clinical status. COVID-19 patients exhibited a notably higher abundance of opportunistic pathogens, particularly
conclusionsOur study highlights the differences in lung microbiome diversity and composition between COVID-19 patients and non-COVID-19 patients. This may contribute to predicting co-pathogens and selecting optimal treatments for respiratory infections caused by SARS-CoV-2.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.