A systematic review of gut microbiota profile in <scp>COVID</scp>‐19 patients and among those who have recovered from <scp>COVID</scp>‐19
Bibliographic record
Abstract
OBJECTIVES: Given the scale and persistence of coronavirus disease 2019 (COVID-19), significant attention has been devoted to understanding the relationship between human gut microbiota and COVID-19. In this systematic review we aimed to comprehensively assess the gut microbiota composition in patients infected with COVID-19 and those recovered from COVID-19 in comparison to healthy controls (HCs). METHODS: Peer-reviewed articles and preprints published up to September 1, 2022, were searched in Ovid MEDLINE, Ovid EMBASE, and SCOPUS. Observational studies reporting the gut microbiota profile in adult (≥18 years) COVID-19 patients or those recovered from COVID-19 compared to HCs were eligible for inclusion in this systematic review. The quality assessment of studies was performed using the Newcastle-Ottawa scale. RESULTS: We identified 27 studies comprising 18 studies that compared COVID-19 patients and six that compared recovered COVID-19 patients to HCs, while the other three studies compared both COVID-19 and recovered COVID-19 patients to HCs. Compared to HCs, decreased gut microbial diversity and richness and a distinctive microbial composition were reported in COVID-19 patients and recovered COVID-19 patients. In COVID-19 patients, Bacteroidetes were found to be enriched, and Firmicutes depleted. Decreased short-chain fatty acid (SCFA)-producing bacteria, such as Faecalibacterium, Ruminococcus, and Bifidobacterium, among others, were also observed in COVID-19 patients, which were not restored to normal levels in those who recovered. CONCLUSION: Gut dysbiosis was evident in COVID-19, and available data suggested that dysbiosis persisted even in recovered COVID-19 patients, with decreased Firmicutes and SCFA-producing bacteria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".