Small intestinal bacterial overgrowth and metabolic dysfunction-associated steatotic liver disease
Bibliographic record
Abstract
Small intestinal bacterial overgrowth (SIBO), characterized by alterations in both the type and quantity of bacteria in the small intestine, leads to impaired intestinal digestion and absorption that can cause a range of clinical symptoms. Recent studies have identified significant changes in the composition of the small intestinal microbiota and metabolomic profiles of patients with metabolic dysfunction-associated steatotic liver disease (MASLD). This study systematically reviewed and synthesized the available data to explore the association between SIBO and MASLD. Comprehensive literature searches of the Embase, PubMed, Web of Science, Ovid, and Cochrane databases were conducted. Article quality screening was performed using the Newcastle-Ottawa Quality Assessment Scale. Cross-sectional, cohort, and case–control studies were included. A total of 7,200 articles were initially screened, of which 14 were ultimately included for analysis. Individuals with SIBO in both the MASLD and non-MASLD groups were extracted and a chi-square test was performed to calculate the odds ratio (OR) and 95% confidence interval (CI). The I 2 index was used to measure heterogeneity. For heterogeneity >50%, a random effects model was used. There was a clear association between SIBO and MASLD (OR = 3.09; 95% CI 2.09–4.59, I 2 = 66%, p < 0.0001). Subgroup analyses by MASLD stage showed that the probability of SIBO positivity increased with MASLD lesion severity. After stratifying by the diagnostic methods for SIBO and MASLD, the meta-analysis results suggest a reduction in inter-group heterogeneity. For the MASLD subgroup diagnosed via liver biopsy, the OR was 4.89. A subgroup analysis of four studies that included intestinal permeability testing revealed an OR of 3.86 (95% CI: 1.80–8.28, I 2 = 9%, p = 0.0005). A meta-regression analyses revealed that both race and regional development level significantly influenced the relationship between SIBO and MASLD ( p = 0.010, p = 0.047). In conclusion, this meta-analyses provides strong evidence that SIBO may contribute to the development and progression of MASLD. The strongest associations were observed between lactulose breath testing, gut microbiota culture, liver biopsy diagnosis of MASLD, and SIBO detected through intestinal permeability testing. The primary sources of heterogeneity are race and developed regions. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=427040 .
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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 | 0.001 | 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".