ArticleBMC pulmonary medicine2019
Dynamics of microbiota during mechanical ventilation in aspiration pneumonia.
Article in BMC pulmonary medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled 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.
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
15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Impact of Invasive Mechanical Ventilation on the Lung Microbiome.Advances in respiratory medicine · 2025Pooled it
- A comprehensive evaluation of risk factors for mortality, infection and colonization associated with CRGNB in adult solid organ transplant recipients: a systematic review and meta-analysis.Annals of medicine · 2024Pooled it
- Factors associated withJournal of thoracic disease · 2026Article
- Subglottic microbiota in periodontitis patients undergoing short-term endotracheal intubation: a pilot study.BMC microbiology · 2026Article
- Bronchoalveolar Lavage Microbiota in Critically Ill Patients with Aspiration Pneumonia: An Exploratory Comparison with Community-Acquired Pneumonia and Analysis ofInfection and drug resistance · 2026Article
- Airway tracers and biomarkers for aspiration detection and VAP prediction in ICU patients with tracheal tubes: a systematic review and diagnostic accuracy meta-analysis.Annals of intensive care · 2026Review
- Evaluation of V3-V4 and FL-16S rRNA amplicon sequencing approach for microbiota community analysis of tracheostomy aspirates.mSphere · 2025Article
- Article
- Profiles of oral microbiome associated with nasogastric tube feeding.Journal of oral microbiology · 2023Article
- Differences in the microbiota of oral rinse, lesion, and normal site samples from patients with mucosal abnormalities on the tongue.Scientific reports · 2022Article
- Clinical practices underlie COVID-19 patient respiratory microbiome composition and its interactions with the host.Nature communications · 2021Article
- Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing.Scientific reports · 2021Article
- Factors influencing lower respiratory tract infection in older patients after general anesthesia.The Journal of international medical research · 2021Article
- The respiratory microbiota during and following mechanical ventilation for respiratory infections in children.The European respiratory journal · 2021Article
- Bacterial composition of nasal discharge in children based on highly accurate 16S rRNA gene sequencing analysis.Scientific reports · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe emergence of multi-drug resistant pathogens is an urgent health-related problem, and the appropriate use of antibiotics is imperative. It is often difficult to identify the causative bacteria in patients with aspiration pneumonia because tracheal aspirate contains contaminants of oral bacteria. We investigated the dynamics of microbiota in mechanically ventilated patients with aspiration pneumonia to develop a treatment strategy.
methodsTwenty-two intubated patients with aspiration pneumonia were recruited. Saliva and tracheal aspirate of the subjects were collected at three time points: (A) within 2 h after intubation, (B) just before administration of antibiotics, and (C) 48-72 h after administration of antibiotics. The microbiota in each specimen was analyzed by using the 16S rRNA gene clone library sequencing method. Bacterial floras of the samples were analyzed by principal component analysis.
resultsPrincipal component analysis based on the composition of genus revealed that although the changes of microbiota in the saliva from (A) to (B) were not clear, the composition of anaerobes in the tracheal aspirate (B) was lower than (A). In fact, the reduction of anaerobes, not in the saliva but in the tracheal aspirate from (A) to (B), was confirmed by incident rate ratios estimated by a multilevel Poisson regression model (p < 0.001). The extent of decrease in anaerobes was fully dependent on the time difference between the sampling of tracheal aspirate (A) and (B)-in particular, over 3 h of mechanical ventilation. This indicates that the alterations of microbiota (involving the reduction of anaerobes in the lower respiratory tract) occurred during mechanical ventilation prior to the administration of antibiotics. After the administration of antibiotics, Enterobacter spp., Corynebacterium spp., Pseudomonas aeruginosa, Klebsiella pneumoniae, Staphylococcus aureus, and Granulicatera adiacens were predominantly detected in the tracheal aspirate (C).
conclusionThe microbiota of the lower respiratory tract changes dynamically during mechanical ventilation and during the administration of antibiotics in intubated patients with aspiration pneumonia. Antibiotics should be selected on the premise that dynamic changes in microbiota (involved in the reduction of anaerobes) may occur during the mechanical ventilation in these patients.
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.