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Scoring systems in clinical small-bowel capsule endoscopy: all you need to know!

05 Out. 2021 |

Bruno Rosa Reuma Margalit-Yehuda Kelly Gatt Martina Sciberras Carlo GirelliJean-Christophe Saurin Pablo Cortegoso Valdivia Jose Cotter Rami EliakimFlavio Caprioli Gunnar BaatrupMartin KeuchelPierre Ellul Ervin Toth Anastasios Koulaouzidis 

Palavra-Chave: small-bowel capsule endoscopy

Abstract

Capsule endoscopy (CE) emerged out of the pressing clinical need to image the small bowel (SB) in cases of midgut bleeding and provide an overall comfortable and reliable gastrointestinal (GI) diagnosis 1 . Since its wider adoption in clinical practice, significant progress has been made in several areas including software development, hardware features and clinical indications, while innovative applications of CE never cease to appear 2 3 . Currently, several manufacturers provide endoscopic capsules with more or less similar technological features 4 . Although there is engaging and continuous academic and industry-fueled R&D, promising furtherment of CE technology 4 5 , the current status of clinical CE remains that of by and large an imaging modality. Clinical relevance of CE images is cornerstone in the decision-making process for medical management. In one of the larger to date SB CE studies, 4,206 abnormal images were detected in 3,280 patients 6 . Thus, CE leads to the identification of a large amount of potential pathology, some of which are pertinent (or relevant) while some (probably the majority) are not. Soon artificial intelligence (AI) is likely to carry out several roles currently performed by humans; in fact, we are witnessing only the first stages of a transition in the clinical adoption of AI-based solutions in several aspects of gastroenterology including CE 7 . Until then though, human-based decision-making profoundly impacts patient care and – although not suggested in the updated European Society of Gastrointestinal Endoscopy (ESGE) European curriculum 8 9 – it should be an integral part of CE training. Frequently, interpretation of CE images by experts or at least experienced readers differs. In a tandem CE reading study, expert review of discordant cases revealed a 50 % (13/25 discordant results) error rate by experienced readers, corresponding (in 5/13 cases) to ‘over-classification’ of an irrelevant abnormality 10 . Another comparative study showed an ‘over-classification’ of such irrelevant abnormalities in ~10 % of CE readings 11 . One thing which has been for a while on the table – in relation to optimizing and/or standardizing CE reporting and subsequent decision-making – is the need for reproducible scoring systems and for a reliable common language among clinicians responsible for further patient’s management. Over the years, several of these scoring systems were developed while others appear in the wake of software and hardware improvements aiming to replace and/or complement their predecessors. This review presents a comprehensive account of the currently available classification/scoring systems in clinical CE spanning from predicting the bleeding potential of identified SB lesions (with emphasis on vascular lesions), and the individual rebleeding risk; scoring systems for the prediction of SB lesions in patients with obscure gastrointestinal bleeding (OGlB), having the potential to improve patient selection and rationalize the use of enteroscopy, with better allocation of resources, optimized diagnostic workflow and tailored treatment. This review also includes scores for reporting the inflammatory burden, the cleansing level that underscores confidence in CE reporting and the mass or bulge question in CE. Essentially, the aim is to become a main text for reference when scoring is required and facilitate the inclusion of -through readiness of access- one of the other in the final report.

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