Intestinal gas and liver steatosis: a casual association? A prospective multicentre assessment
Bibliographic record
Abstract
BACKGROUND & AIMS: Excessive intestinal gas and liver steatosis are frequent sonographic findings. Both of these appear to be caused by variations of the gut microflora. We assessed the relationship between ultrasonographic detection of intestinal gas and liver steatosis. METHODS: This study included 204 consecutive patients (99 male; mean age 53.0 ± 15.6 years), who underwent ultrasonography for abdominal complaints or follow-up of benign lesions. Body mass index, biochemical liver markers, sonographic presence of liver steatosis and/or degree of intestinal gas interfering with the examination were collected. Both sonographic findings were assessed based on standardized criteria. The association between liver steatosis and intestinal gas was evaluated by means of univariate and multivariate analyses. RESULTS: Eighty (39.2%) of patients showed moderate to large amounts of gas preventing an accurate evaluation of the liver or pancreas and 90 (44.1%) had liver steatosis. A significant correlation between the degree of intestinal gas and liver steatosis both in obese (r=.603; P<.001) and in nonobese patients (r=.555; P<.001) was found. Univariate analysis showed that intestinal gas, body mass index, aspartate transaminase, alanine transaminase, gamma-GT, age and sex were predictors of liver steatosis; only intestinal gas (OR 7.4; 95% CI 3.4-16.1) and body mass index (OR; 1.4, 95% CI 1.2-1.5), however, were independent predictors at multivariate analysis. The presence of excessive gas was also significantly correlated with liver steatosis coupled with elevated ALT (P = .001). CONCLUSION: This study shows a significant correlation between excessive intestinal gas and liver steatosis. The reasons of this finding and its clinical implications remain to be defined.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".