ArticleNpj gut and liver2026
Closing the screening gap but not the writing gap: a two-topic evaluation of LLMs for systematic reviews and meta-analyses in hepatology.
Article in Npj gut and liver, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
Systematic reviews are essential but labor-intensive. We evaluated LLM-assisted literature screening and drafting in two hepatology topics: carvedilol in compensated cirrhosis and anticoagulation in portal vein thrombosis. For each topic, we searched PubMed, Cochrane, and EMBASE. A few-shot prompt with explicit inclusion/exclusion criteria was used to screen titles and abstracts, with results compared to manual review. Included studies were then processed using a retrieval-augmented LLM to generate ten automated systematic review and meta-analysis drafts per topic, which were evaluated by a separate judge LLM for PRISMA 2020 compliance against human reviews. Screening performance: After deduplication (703 and 370 records), LLM-assisted screening showed high agreement with manual review (sensitivity 86-93%, specificity 96-99%) while reducing screening time to 3 and 2 h versus 62 and 30 h manually. Drafting performance: RAG-enabled LLMs generated structured manuscripts with variable PRISMA 2020 compliance: 100% for titles, 91% for introductions, 75-80% for methods, and 68-75% for results, with downstream weaknesses in abstracts and discussions (<65%). LLM-based PRISMA scoring closely matched human review (ICC ≈ 0.90). LLM-assisted screening was highly accurate, reducing workload by >90%, but automated drafting was reliable mainly for titles and introductions, requiring human oversight to prevent errors and hallucinations.
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Registered trials
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