Kim JH, Nam SJ. Prediction models for recurrence in patients with small bowel bleeding. World J Clin Cases 2023; 11(17): 3949-3957 [PMID: 37388787 DOI: 10.12998/wjcc.v11.i17.3949]
Corresponding Author of This Article
Seung-Joo Nam, MD, PhD, Assistant Professor, Division of Gastroenterology and Hepatology, Department of Internal Medicine, Kangwon National University Hospital, Baengnyeong-ro 156, Chuncheon, Gangwon-Do, 24289, South Korea. pinetrees@daum.net
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Cases. Jun 16, 2023; 11(17): 3949-3957 Published online Jun 16, 2023. doi: 10.12998/wjcc.v11.i17.3949
Prediction models for recurrence in patients with small bowel bleeding
Ji Hyun Kim, Seung-Joo Nam
Ji Hyun Kim, Seung-Joo Nam, Division of Gastroenterology and Hepatology, Department of Internal Medicine, Kangwon National University School of Medicine, Chuncheon 24341, South Korea
Author contributions: Kim JH and Nam SJ wrote the manuscript; and Nam SJ supervised the reported work.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Seung-Joo Nam, MD, PhD, Assistant Professor, Division of Gastroenterology and Hepatology, Department of Internal Medicine, Kangwon National University Hospital, Baengnyeong-ro 156, Chuncheon, Gangwon-Do, 24289, South Korea. pinetrees@daum.net
Received: December 27, 2022 Peer-review started: December 27, 2022 First decision: March 20, 2023 Revised: April 10, 2023 Accepted: May 15, 2023 Article in press: May 15, 2023 Published online: June 16, 2023 Processing time: 166 Days and 18.4 Hours
Abstract
Obscure gastrointestinal bleeding (OGIB) has traditionally been defined as gastrointestinal bleeding whose source remains unidentified after bidirectional endoscopy. OGIB can present as overt bleeding or occult bleeding, and small bowel lesions are the most common causes. The small bowel can be evaluated using capsule endoscopy, device-assisted enteroscopy, computed tomography enterography, or magnetic resonance enterography. Once the cause of small-bowel bleeding is identified and targeted therapeutic intervention is completed, the patient can be managed with routine visits. However, diagnostic tests may produce negative results, and some patients with small bowel bleeding, regardless of diagnostic findings, may experience rebleeding. Predicting those at risk of rebleeding can help clinicians form individualized surveillance plans. Several studies have identified different factors associated with rebleeding, and a limited number of studies have attempted to create prediction models for recurrence. This article describes prediction models developed so far for identifying patients with OGIB who are at greater risk of rebleeding. These models may aid clinicians in forming tailored patient management and surveillance.
Core Tip: Some patients with small bowel bleeding, regardless of the diagnostic findings, may experience rebleeding. Predicting those at risk of rebleeding can help clinicians form individualized surveillance plans. This article describes prediction models developed so far for identifying patients with obscure gastrointestinal bleeding who are at greater risk of rebleeding. There are prediction models that can help identify patients with a greater risk of rebleeding.