Alterations of gut microbiome following gastrointestinal surgical procedures and their potential complications
Bibliographic record
Abstract
Intestinal microorganisms play a crucial role in shaping the host immunity and maintaining homeostasis. Nevertheless, alterations in gut bacterial composition may occur and these alterations have been linked with the pathogenesis of several diseases. In surgical practice, studies revealed that the microbiome of patients undergoing surgery changes and several post-operative complications seem to be associated with the gut microbiota composition. In this review, we aim to provide an overview of gut microbiota (GM) in surgical disease. We refer to several studies which describe alterations of GM in patients undergoing different types of surgery, we focus on the impacts of peri-operative interventions on GM and the role of GM in development of post-operative complications, such as anastomotic leak. The review aims to enhance comprehension regarding the correlation between GM and surgical procedures based in the current knowledge. However, preoperative and postoperative synthesis of GM needs to be further examined in future studies, so that GM-targeted measures could be assessed and the different surgery complications could be reduced.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".