A Meta-Analysis of Nutritional Supplementation for Management of Hospitalized Alcoholic Hepatitis
Bibliographic record
Abstract
BACKGROUND: Alcoholic liver disease (ALD) is associated with a high risk of morbidity and mortality. Malnutrition accompanies this condition and may be both a consequence of and contributor to the pathology. Many trials have investigated the benefits of providing supplemental nutrition in the management of patients with ALD. The present study is a meta-analysis of the available evidence. METHOD: A meta-analysis of randomized controlled studies comparing nutritional supplementation plus a normal hospital diet versus diet alone. RESULTS: Seven randomized controlled studies including 262 patients with ALD were identified. Pooled analysis revealed no statistical difference in mortality between groups given special nutritional therapy versus a normal balanced diet (OR 0.80 [95% CI 0.42 to 1.52]). In addition, nutrition did not significantly improve ascites (OR 1.29 [95% CI 0.52 to 3.20]) or any biochemical parameters. However, encephalopathy showed a significant improvement or resolution (OR 0.24 [95% CI 0.06 to 0.93]). CONCLUSION: Nutritional supplementation provided no mortality benefit in patients with ALD, and neither ascites nor biochemical parameters significantly improved. However, encephalopathy was significantly ameliorated and, therefore, nutritional supplementation should be encouraged in that setting.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.022 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".