Gut Microbiota Profile in Pediatric Patients With Inflammatory Bowel Disease: A Systematic Review
Bibliographic record
Abstract
Background and Aim: Accumulating evidence have implicated gut microbiota alterations in pediatric and adult patients with inflammatory bowel disease (IBD); however, the results of different studies are often inconsistent and even contradictory. It is believed that early changes in new-onset and treatment-naïve pediatric patients are more informative. We performed a systematic review to investigate the gut microbiota profiles in pediatric IBD and identify specific microbiota biomarkers associated with this disorder. Methods: Electronic databases were searched from inception to 31 July 2020 for studies that observed gut microbiota alterations in pediatric patients with IBD. Study quality was assessed using the Newcastle–Ottawa scale. Results: A total of 41 original studies investigating gut microbiota profiles in pediatric patients with IBD were included in this review. Several studies have reported a decrease in α-diversity and an overall difference in β-diversity. Although no specific gut microbiota alterations were consistently reported, a gain in Enterococcus and a significant decrease in Anaerostipes, Blautia, Coprococcus, Faecalibacterium, Roseburia, Ruminococcus, and Lachnospira were found in the majority of the included articles. Moreover, there is insufficient data to show specific microbiota bacteria associated with disease activity, location, and behavior in pediatric IBD. Conclusions: This systematic review identified evidence for differences in the abundance of some bacteria in pediatric patients with IBD when compared to patients without IBD; however, no clear overall conclusion could be drawn from the included studies due to inconsistent results and heterogeneous methodologies. Further studies with large samples that follow more rigorous and standardized methodologies are needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".