ArticleJournal of inflammation research2025
Predicting Risk of Post-Treatment Relapse in Patients with Inflammatory Bowel Disease Based on Intestinal Microbiota.
Article in Journal of inflammation research, 2025. 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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19 authors.
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Abstract
Background: Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract. Post-treatment relapse is a major clinical challenge, and gut microbiota dysbiosis is hypothesized to be involved. Methods: We enrolled 88 patients with IBD (46 UC, 42 CD) to investigate gut microbiota features associated with post-treatment relapse. Fecal samples collected before and after therapy were analyzed by 16S rRNA sequencing. A random forest (RF) model was developed to evaluate the predictive value of microbiota signatures for recurrence. Results: At baseline (pre-treatment), no differences were observed in gut microbiota diversity between patients with UC and CD. However, significant compositional differences were observed, with Conclusion: Our findings suggest that gut microbiota composition may hold clues for predicting IBD relapse. The RF model is a proof-of-concept that warrants external validation in prospective, multi-center studies before clinical application.
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