Acute variceal bleeding (AVB) is a potentially fatal complication of clinically significant portal hypertension and is one of the most common causes of acute upper gastrointestinal bleeding. Thus, esophagogastric varices represent a major economic and population health issue. Patients with advanced chronic liver disease typically undergo an upper endoscopy to screen for esophagogastric varices. However, upper endoscopy is not recommended for patients with liver stiffness < 20 KPa and platelet count > 150 × 10⁹/L as there is a low probability of high-risk varices. Patients with high-risk varices should receive primary prophylaxis with either nonselective beta-blockers or endoscopic band ligation. In cases of AVB, patients should receive upper endoscopy within 12 h after resuscitation and hemodynamic stability, whereas endoscopy should be performed as soon as possible if patients are unstable. In cases of suspected variceal bleeding, starting vasoactive therapy as soon as possible in combination with endoscopic treatment is recommended. On the other hand, in cases of uncontrolled bleeding, balloon tamponade or self-expandable metal stents can be used as a bridge to more definitive therapy such as transjugular intrahepatic portosystemic shunt. This article aims to offer a comprehensive review of recommendations from international guidelines as well as recent updates on the management of esophagogastric varices.

Introduction: Artificial intelligence (AI) is increasingly being applied to improve the diagnosis and management of inflammatory bowel disease (IBD). Aims and Methods: We conducted a narrative review of the literature on AI applications in IBD endoscopy, focusing on diagnosis, disease activity assessment, therapy prediction, and detection of dysplasia. Results: AI systems have demonstrated high accuracy in assessing endoscopic and histological disease activity in ulcerative colitis and Crohn’s disease, with performance comparable to expert clinicians. Machine learning models can predict response to biologics and risk of complications. AI-assisted technologies like confocal laser endomicroscopy enable real-time histological assessment. Computer-aided detection systems improve identification of dysplastic lesions during surveillance. Challenges remain, including need for larger datasets, external validation, and addressing potential biases. Conclusions: AI has significant potential to enhance IBD care by providing rapid, objective assessments of disease activity, predicting outcomes, and assisting in dysplasia surveillance. However, further validation in diverse populations and prospective studies are needed before widespread clinical implementation. With ongoing advances, AI is poised to become a valuable tool to support clinical decision-making and improve patient outcomes in IBD. Addressing methodological, regulatory, and cost barriers will be crucial for the successful integration of AI into routine IBD management.

One of the most essential procedures for individuals with biliopancreatic disorders is endoscopic retrograde cholangiopancreatography (ERCP). It is based on the combination of endoscopy and radiology to study the biliopancreatic ducts and apply therapeutic solutions. ERCP is currently used to treat choledocholithiasis with or without cholangitis, as well as pancreatic duct stones, benign bile, and pancreatic leaks. On the other hand, ERCP is an unpleasant procedure that must be conducted under anesthetic (moderate sedation, deep sedation, or general anesthesia). With procedures becoming more challenging, the role of anesthesia in ERCP has become even more relevant, and the use of general anesthesia has become better defined. In the last decades, many drugs have been used and some new drugs, like dexmedetomidine, have been recently introduced for sedation or anesthesia during ERCP. Moreover, the scientific community is still divided on the level of sedation to be applied, as well as on appropriate airway management. We therefore performed a narrative review of the literature to assess currently available anesthetic medications for elective ERCP and evidence supporting their effectiveness.

Background: Inflammatory Bowel Disease (IBD), comprising Crohn’s disease and ulcerative colitis, requires accurate assessment over time. Imaging techniques play a crucial role in diagnosis, monitoring disease activity, and guiding therapeutic response. This review summarizes the current evidence on radiologic imaging techniques in IBD, focusing on intestinal ultrasound (IUS), computed tomography enterography (CTE), magnetic resonance enterography (MRE), and other emerging technologies. Methods: A literature review was conducted using PubMed, EMBASE, Scopus, and the Cochrane Library, encompassing publications up to 31 October 2024. Results: IUS offers a non-invasive tool for assessing bowel wall thickness, vascularity, and complications. CTE and MRE provide detailed visualization of luminal and extraluminal disease, with MRE preferred for routine monitoring due to the absence of ionizing radiation. Standardized indices and scoring systems aid in objective disease activity assessment. Emerging technologies like Positron Emission Tomography (PET)/MRI and radiomics show promise in combining metabolic and morphological information for complex cases. Conclusions: Imaging has a central role in IBD management, with IUS, CTE, and MRE demonstrating high diagnostic accuracy. Radiomics and Artificial Intelligence (AI) are paving the way for precision imaging. Integrating advanced imaging techniques, scoring systems, and AI-driven analytics represents a transformative step toward more effective and individualized care for patients with IBD.

Background: An extensive body of evidence regarding artificial intelligence (AI) in gastroenterology is currently available, but the transition of these technologies to the bedside is still in progress. This national survey aims to assess the perceptions of AI among gastroenterologists in Italy. Methods: A total of 320 Italian gastroenterologists and trainees in gastroenterology were invited to answer a web-based survey. A sub-group analysis between the two categories was performed. Results: Data from 150 respondents were analyzed. Of these, 67.3% were gastroenterologists and 32.7% trainees. Notably, 99.3% reported familiarity with AI in gastroenterology, with 49.3% currently using AI tools, indicating high levels of awareness and current use. Participants expressed low concerns regarding reliability on a 0-to-10-point scale (median = 4), legal and ethical issues (median = 5), and data protection (median 5), whereas regulatory concerns were moderate (median = 6), representing a key concern. Subgroup analysis revealed that male gastroenterologists had a higher understanding of AI (median = 7) compared to females (median 6, p = 0.036). Additionally, older gastroenterologists showed greater ease of use in AI endoscopy tools (median 8 vs. 7, p = 0.040) and raised more regulatory concerns (median 7 vs. 6, p = 0.036). Conclusions: The data from this survey show that Italian gastroenterologists have high-level awareness and a favorable perception of AI systems, with a good diffusion of AI tools across the national territory and reasonable concerns about regulatory issues, raising attention on international AI regulations.