Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare several novel multilevel classification algorithms across several varied data conditions for the purpose of prediction. Among these models, the panel neural network and Bayesian generalized mixed effects model (multilevel Bayes) consistently yielded the highest prediction accuracy in test data across nearly all data conditions.

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Background: Additional therapies for hepatic encephalopathy (HE) treatment are warranted. There are data evaluating the use of zinc for HE; however, clinical outcomes, specifically in the United States, are unknown. Objective: To compare 30-day and 1-year all-cause readmission rates in patients with cirrhosis complicated by HE on lactulose and rifaximin to those on lactulose, rifaximin, and zinc. Methods: This retrospective study included patients admitted with documented cirrhosis and home medications of lactulose and rifaximin, with or without zinc. Patients were stratified into 2 groups: those receiving lactulose and rifaximin for HE (control) and those receiving lactulose, rifaximin, and zinc for HE (treatment). The primary outcomes were 30-day and 1-year all-cause readmission rates. Results: One-hundred fifty-seven patients were included (102 in control group, 55 in treatment group). Regarding 30-day and 1-year all-cause readmission rates, there was no difference between the control and treatment groups. Conclusion and Relevance: This is the first study conducted in the United States evaluating zinc for HE treatment. Zinc did not impact 30-day or 1-year all-cause readmission rates. Further studies are warranted to evaluate the potential benefit of zinc for HE, possibly in correlation with Model for End-stage Liver Disease-Sodium (MELD-Na) scores.

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