Fistulizing perianal disease is a debilitating complication present in nearly half of all patients diagnosed with Crohn's disease. The majority of anal fistulas arising in these patients are complex. Treatment can be challenging with therapy often requiring both medical and surgical interventions with differing levels of symptomatic relief. Fecal diversion is an option after medical and surgical modalities have been exhausted but demonstrates limited efficacy. Complex perianal fistulizing Crohn's disease is inherently morbid and can be difficult to manage. We present a case of a young male with Crohn's, severe malnutrition and multiple perianal abscess with extensive fistula tracts up to his back; a planned fecal diversion was instituted to control sepsis and allow for wound healing and optimize medical therapy.
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http://dx.doi.org/10.1093/jscr/rjad364 | DOI Listing |
Nan Fang Yi Ke Da Xue Xue Bao
December 2024
Department of Immunology, School of Laboratory Medicine, Bengbu Medical University, Bengbu 233030, China.
Objectives: To investigate the effects of asperosaponin VI (AVI) on intestinal epithelial cell apoptosis and intestinal barrier function in a mouse model of Crohn's disease (CD)-like colitis and explore its mechanisms.
Methods: Male C57BL/6 mice with TNBS-induced CD-like colitis were treated with saline or AVI (daily dose 150 mg/kg) by gavage for 6 days. The changes in body weight, colon length, DAI scores, and colon pathologies of the mice were observed, and the expressions of inflammatory factors and tight injunction proteins were detected using ELISA and RT-qPCR.
Gastroenterology
December 2024
Guangdong Provincial Key Laboratory of Gastroenterology Institute of Gastroenterology of Guangdong Province Department of Gastroenterology, Nanfang Hospital Southern Medical University, Guangzhou, China.
Dig Dis Sci
December 2024
OHDSI Collaborators, Observational Health Data Sciences and Informatics (OHDSI), New York, NY, USA.
Background And Aims: Observational healthcare data are an important tool for delineating patients' inflammatory bowel disease (IBD) journey in real-world settings. However, studies that characterize IBD cohorts typically rely on a single resource, apply diverse eligibility criteria, and extract variable sets of attributes, making comparison between cohorts challenging. We aim to longitudinally describe and compare IBD patient cohorts across multiple geographic regions, employing unified data and analysis framework.
View Article and Find Full Text PDFJ Am Med Inform Assoc
December 2024
Statistical Modeling, Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riβ 88400, Germany.
Background: Machine learning and deep learning are powerful tools for analyzing electronic health records (EHRs) in healthcare research. Although family health history has been recognized as a major predictor for a wide spectrum of diseases, research has so far adopted a limited view of family relations, essentially treating patients as independent samples in the analysis.
Methods: To address this gap, we present ALIGATEHR, which models inferred family relations in a graph attention network augmented with an attention-based medical ontology representation, thus accounting for the complex influence of genetics, shared environmental exposures, and disease dependencies.
Gastroenterol Rep (Oxf)
December 2024
[This corrects the article DOI: 10.1093/gastro/goad072.].
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