A227 THE EFFECTIVENESS OF PEG 3350 COMPARED TO LACTULOSE FOR THE TREATMENT OF ACUTE HEPATIC ENCEPHALOPATHY IN ADULT CIRRHOTIC PATIENTS: A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
Abstract Background Cirrhosis is the leading cause of liver-related death globally. Hepatic encephalopathy (HE) leads to significant morbidity and mortality. Lactulose is the current gold standard treatment for HE; it eliminates nitrogenous waste from the gut. Polyethylene glycol 3350–electrolyte solution (PEG) is a safe, common and effective purgative with recent studies suggesting its efficacy resulting in faster resolution of HE and shorter hospital length of stay. Aims To assess the efficacy and safety of PEG 3350 compared to lactulose in adult cirrhotic patients 18 years of age and older with overt hepatic encephalopathy on patient important outcomes including: improvement of hepatic encephalopathy, hospital length of stay and mortality. Methods We reviewed databases MEDLINE, EMBASE, OVID, CINAHL, Cochrane Database, PubMed, Trip database, the grey literature, and clinicaltrials.gov from inception to December 2020: PROSPERO CRD42021257641. Search strategy was developed in conjunction with medical librarian. Randomized controlled trials (RCTs), either published or non-published, were included in the review. Continuous data was analyzed using mean difference with random-effects model. Dichotomous data was analyzed using the Mantel-Haenszel method using random-effects model. Statistical effect-size heterogeneity was assessed using Chi2 test and quantifying the relative proportion of variation using I2 statistic. The overall certainty of evidence will be assessed using the Grading of Recommendations, Assessment, Development and Evaluations system (GRADE). Results From the 68 studies, 16 were assessed for full text review from which 5 studies were included in the meta-analysis representing a total of 351 patients. The primary outcome of mean change in Hepatic Encephalopathy Scoring Algorithm (HESA) at 24-hours from baseline demonstrated an improvement in the PEG group compared to lactulose group [Mean difference (MD)= 0.60, 95% CI (0.20, 1.01)]. In comparison to lactulose, PEG also demonstrated a shorter hospital length of stay [MD = -1.00, 95% CI (-1.99, -0.01)], shorter time to HE resolution [MD= -1.49, 95% CI (-1.81, -1.16)] and showed a mortality benefit [RR=0.35, 95% CI (0.13 to 0.92)]. There was no significant difference between change in ammonia levels at 24 hours [MD= -25.80, 95% CI (-95.39, 43.78)]. Conclusions PEG leads to a faster improvement and resolution of HE when compared to the current standard of care, lactulose. Funding Agencies None
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.029 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".