Patients with HEV-NA are usually anicteric and have a distinct clinical phenotype, with predominately bilateral asymmetrical involvement of, and more extensive damage to, the brachial plexus. Involvement outside the brachial plexus is more common in HEV-NA. The relationship between HEV and NA is likely to be causal, but is easily overlooked. Patients presenting with NA should be tested for HEV, irrespective of liver function test results. Prospective treatment/outcome studies of HEV-NA are warranted.

This ESGE Position Statement defines the expected value of artificial intelligence (AI) for the diagnosis and management of gastrointestinal neoplasia within the framework of the performance measures already defined by ESGE. This is based on the clinical relevance of the expected task and the preliminary evidence regarding artificial intelligence in artificial or clinical settings. Main recommendations: (1) For acceptance of AI in assessment of completeness of upper GI endoscopy, the adequate level of mucosal inspection with AI should be comparable to that assessed by experienced endoscopists. (2) For acceptance of AI in assessment of completeness of upper GI endoscopy, automated recognition and photodocumentation of relevant anatomical landmarks should be obtained in ≥90% of the procedures. (3) For acceptance of AI in the detection of Barrett’s high grade intraepithelial neoplasia or cancer, the AI-assisted detection rate for suspicious lesions for targeted biopsies should be comparable to that of experienced endoscopists with or without advanced imaging techniques. (4) For acceptance of AI in the management of Barrett’s neoplasia, AI-assisted selection of lesions amenable to endoscopic resection should be comparable to that of experienced endoscopists. (5) For acceptance of AI in the diagnosis of gastric precancerous conditions, AI-assisted diagnosis of atrophy and intestinal metaplasia should be comparable to that provided by the established biopsy protocol, including the estimation of extent, and consequent allocation to the correct endoscopic surveillance interval. (6) For acceptance of artificial intelligence for automated lesion detection in small-bowel capsule endoscopy (SBCE), the performance of AI-assisted reading should be comparable to that of experienced endoscopists for lesion detection, without increasing but possibly reducing the reading time of the operator. (7) For acceptance of AI in the detection of colorectal polyps, the AI-assisted adenoma detection rate should be comparable to that of experienced endoscopists. (8) For acceptance of AI optical diagnosis (computer-aided diagnosis [CADx]) of diminutive polyps (≤5 mm), AI-assisted characterization should match performance standards for implementing resect-and-discard and diagnose-and-leave strategies. (9) For acceptance of AI in the management of polyps ≥ 6 mm, AI-assisted characterization should be comparable to that of experienced endoscopists in selecting lesions amenable to endoscopic resection.

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ObjectiveTo determine the diagnostic accuracy of calprotectin to diagnose inflammatory bowel disease (IBD) in children in whom general practitioners (GPs) suspected IBD.DesignProspective observational cohort study of a new calprotectin-based primary care referral pathway.Setting48 GP practices and gastroenterology secondary care services at the Royal Devon and Exeter NHS Foundation Trust in the South-West of England, UK.Patients195 children aged between 4 and 18 years referred on the pathway between January 2014 and August 2017 for investigation of gastrointestinal symptoms were included.InterventionsPrimary-care-driven faecal calprotectin testing. Primary and secondary care records over 12 months from the point of calprotectin testing were used as the reference standard.Main outcome measuresDiagnostic accuracy of calprotectin testing to detect IBD.Results7% (13/195) tested patients were diagnosed with IBD. Using our prespecified cut-off of 100 µg/g, calprotectin had a diagnostic accuracy of 91% (95% CI 86% to 95%) with a sensitivity for distinguishing IBD from non-IBD of 100% (95% CI 75% to 100%), a specificity of 91% (95% CI 85% to 94%), a positive predictive value of 43% (95% CI 25% to 63%) and a negative predictive value of 100% (95% CI 98% to 100%). Calprotectin testing had no effect on the time to diagnosis, but a negative test contributed to saved referrals and was associated with fewer diagnostic tests in secondary care.ConclusionsCalprotectin testing of children with suspected IBD in primary care accurately distinguishes IBD from a functional gut disorder, reduces secondary care referrals and associated diagnostic healthcare utilisation.