ReviewDigestion2026
Endoscopic Evaluation of the Gastroesophageal Junction and Diagnosis of Barrett's Esophagus.
Review in Digestion, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
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0 citing papers in PubMed.
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Authors and funding
1 author.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundBarrett's esophagus (BE) is a recognized precursor to esophageal adenocarcinoma (EAC), yet its endoscopic diagnosis remains inconsistent worldwide. This review summarizes current challenges and recent advancements in the endoscopic diagnosis of BE, including updates from international consensus statements and emerging technologies such as image-enhanced endoscopy (IEE) and artificial intelligence (AI). SUMMARY: This narrative review integrated international guidelines, multicenter studies, expert consensuses, including the Kyoto International Consensus and Asian Barrett Consortium data, and recent trials of diagnostic imaging and quality indicators (QIs) regarding BE surveillance. KEY MESSAGES: Discrepancies in defining the gastroesophageal junction (GEJ) - notably between palisade vessels and gastric folds - contribute to the global variability of the BE diagnosis. The Kyoto International Consensus recommends using the distal end of the palisade vessels as a more stable and histologically consistent landmark. Additionally, the Prague C & M criteria offer a standardized approach to measuring the BE length; however, limitations for ultra-short-segment BE exist. IEE modalities such as linked color imaging and red dichromatic imaging enhance GEJ visualization, whereas AI systems have the potential for automated BE classification. QIs such as the neoplasia detection rate, inspection time, and adherence to biopsy protocols have been proposed to improve diagnostic consistency and outcomes. Standardizing the endoscopic definition of BE and adopting quality-based surveillance strategies are essential to improving detection and reducing variability. Incorporating IEE- and AI-based tools into routine practice may support a more reliable and efficient diagnostic pathway for BE, thus facilitating early EAC detection and prevention worldwide.
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