l-Ornithine l-Aspartate (LOLA) for Hepatic Encephalopathy in Cirrhosis: Results of Randomized Controlled Trials and Meta-Analyses
Bibliographic record
Abstract
This manuscript represents an appraisal of the evidence in support of L-ornithine-L-aspartate (LOLA) for the management and treatment of hepatic encephalopathy (HE) in cirrhosis. Meta-analyses of randomized controlled trials (RCTs) conducted over the last two decades generally reveal evidence of benefit of LOLA in a range of clinical presentations. This included improvement of mental state grade in overt HE (OHE) assessed by West Haven criteria as well as in minimal HE (MHE) assessed by psychometric testing where the oral formulation of LOLA was determined to be particularly effective. However, concerns over study quality were noted in one meta-analysis. Nevertheless, the concomitant lowering of fasting blood ammonia was reported in all RCTs using this endpoint. Network meta-analyses showed that LOLA appears to be comparable (or superior) in efficacy to non-absorbable disaccharides or probiotics. Emerging evidence from single RCTs show efficacy of LOLA for the treatment of post-transjugular intrahepatic portosystemic shunt (TIPSS) HE as well as for secondary HE prophylaxis. These findings provide support for the use of LOLA in the treatment of HE and future trials should focus on the use of LOLA for prophylaxis.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.026 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".