Gut Microbiota Profiles and Microbial-Based Therapies in Post-operative Crohn's Disease: A Systematic Review
Bibliographic record
Abstract
Background and Aims: Gut microbiota recolonization after intestinal resection had been reported to be associated with post-operative recurrence in Crohn's disease (CD). However, the results of different studies are inconsistent and even contradictory. In addition, knowledge on the efficacy of microbial-based therapies in preventing post-operative recurrence of CD is limited. Therefore, the aim of this review was to investigate gut microbiota profiles in patients with CD before and after surgery and evaluate microbial-based therapies in preventing post-operative recurrence. Methods: Electronic databases were searched from inception to 31 June 2020 using predefined terms. Studies that investigated gut microbiota pre- and post-intestinal resection, and microbial-based therapies in preventing post-operative recurrence, were eligible. Study quality was assessed using either the Newcastle–Ottawa scale or Jadad scoring system. Results: Twelve studies investigating gut microbiota of CD patients suffering from operation, and other 12 studies evaluating the efficacy of antibiotics and probiotics, were included in our review. The mucosa-associated microbiota in surgical biopsy of CD patients is significantly distinct from that in normal mucosa from healthy subjects. Gut microbiota recolonization following surgery might be associated with post-operative recurrence in CD patients. Furthermore, CD patients with post-operative recurrence presented a gain in pro-inflammatory pathogenic bacteria and a loss in short-chain fatty acid-producing bacteria before and after surgery. However, no consistent bacteria or metabolites were found to predict the post-operative recurrence of CD. Additionally, microbial-based therapies are deficient and present restricted widespread clinical utility due to several deficiencies. Conclusion: Recurrence-associated bacteria observed pre- and post- operation might be promising in preventing the post-operative recurrence of CD. Furthermore, potential microbe biomarkers for predicting subsequent disease recurrence should be validated with larger sample sizes using more rigorous and standardized methodologies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".