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Related Concept Videos

Inflammatory Bowel Disease III: Diagnostic Studies and Management I-Nutritional Therapy01:30

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Various diagnostic tests are employed in the diagnostic process for Inflammatory Bowel Disease (IBD), particularly to differentiate between Crohn's disease and ulcerative colitis.
Diagnostic studies
A colonoscopy is the definitive screening test, distinguishing ulcerative colitis from other colon diseases with similar symptoms. During a colonoscopy test, inflamed mucosa with exudate ulcerations can be observed, and biopsies are taken to determine the histologic characteristics of the...
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Inflammatory Bowel Disease IV: Pharmacological Management01:29

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Upon diagnosis, managing Inflammatory Bowel Disease (IBD) involves addressing several crucial aspects. The primary goals include resting the bowel, correcting malnutrition, and providing symptomatic relief. Resting the bowel may consist of medications to reduce inflammation and promote healing. Correcting malnutrition is essential, often requiring dietary adjustments and nutritional supplements. Symptomatic relief aims to ease pain, diarrhea, and other discomforts in IBD.
Pharmacologic...
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Inflammatory Bowel Disease II: Crohn's Disease01:30

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Introduction
Inflammatory bowel disease, commonly known as IBD, refers to a collection of disorders that lead to persistent inflammation of the gastrointestinal tract. The two types of IBD are ulcerative colitis, which impacts the colon, and Crohn's disease, which can involve any part of the gastrointestinal segment.
Crohn's disease
Crohn's disease is a chronic, systemic inflammatory bowel disease (IBD) that predominantly affects the gastrointestinal tract. It is marked by...
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Drugs for Treatment of Crohn's Disease in IBD Using Biologic Agents: Anti-TNF01:24

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Tumor Necrosis Factor (TNF), a proinflammatory cytokine, contributes significantly to the inflammation seen in Crohn's disease. It exists as soluble TNF and membrane-bound TNF, with actions mediated through TNF receptors (TNFR). TNFR activation leads to the release of proinflammatory cytokines, T-cell activation, collagen production, and leukocyte migration, all contributing to inflammation in Crohn's disease. Anti-TNF monoclonal antibodies, namely infliximab (Remicade), adalimumab...
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Inflammatory Bowel Disease V: Surgical Management01:21

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Surgical interventions for inflammatory bowel disease (IBD), which includes ulcerative colitis and Crohn's disease, are essential in managing symptoms and addressing complications. The selection of surgical procedures is contingent upon the specific conditions and complications that stem from these illnesses.
Here are some common surgical interventions for IBD:
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Drugs for Treatment of Crohn's Disease in IBD Using Immunomodulatory Agents01:29

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Crohn's disease is an inflammatory bowel disorder marked by chronic inflammation of the GI tract. Various treatment strategies for Crohn's disease are employed, such as immunomodulatory agents, glucocorticoids, and biologics or anti-TNF therapy. Azathioprine (Imuran), a commonly used immunomodulatory drug for Crohn's disease, is converted in the body to mercaptopurine, which inhibits purine biosynthesis and cell proliferation. Both are utilized in severe cases of Inflammatory Bowel...
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Artificial Intelligence for Inflammatory Bowel Diseases (IBD); Accurately Predicting Adverse Outcomes Using Machine

Aria Zand1,2,3, Zack Stokes4,5, Arjun Sharma4

  • 1UCLA Center for Inflammatory Bowel Diseases, Vatche and Tamar Manoukian Division of Digestive Disease, David Geffen School of Medicine, University of California at Los Angeles, 10945 Le Conte Ave #2338, Los Angeles, CA, 90095, USA. azand89@gmail.com.

Digestive Diseases and Sciences
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Artificial Intelligence (AI) models can accurately predict adverse outcomes in patients with Inflammatory Bowel Diseases (IBD). These AI tools show promise for clinical risk stratification and proactive patient management.

Keywords:
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Area of Science:

  • Medical Informatics
  • Computational Biology
  • Clinical Data Science

Background:

  • Inflammatory Bowel Diseases (IBD) present complex and heterogeneous clinical challenges.
  • Artificial Intelligence (AI) offers potential for improved clinical management of IBD.

Purpose of the Study:

  • To develop and validate advanced computational models for predicting adverse outcomes in IBD patients.
  • To leverage a nationally representative dataset for clinical application of predictive models.

Main Methods:

  • Utilized LASSO, Ridge regressions, Support Vector Machines, Random Forests, and Neural Networks on a large dataset from The OptumLabs® Data Warehouse (OLDW).
  • Employed a training and validation cohort approach (72,178 and 69,165 patients, respectively) to assess model performance.
  • Analyzed relative performance and identified key predictors for various AI models.

Main Results:

  • Random Forest and LASSO models achieved high predictive accuracies (AUCs 0.70-0.92).
  • Artificial neural networks demonstrated comparable performance (AUCs 0.61-0.90).
  • Key adverse outcomes included hospitalization (4.1%), surgery (2.9%), long-term steroid use (17%), and biological therapy initiation (13%) in the validation set.

Conclusions:

  • Demonstrated the feasibility of accurately predicting IBD adverse outcomes using AI on large, longitudinal datasets.
  • AI models can be applied for risk stratification and implementing preemptive strategies in clinical settings.