일반 내시경의 위점막 패턴 근접관찰로 Helicobacter pylori 감염 예측 가능성 연구
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 윤경한 | - |
dc.contributor.author | 장영운 | - |
dc.contributor.author | 조준형 | - |
dc.contributor.author | 이유호 | - |
dc.contributor.author | 김권기 | - |
dc.contributor.author | 김태영 | - |
dc.contributor.author | 홍성훈 | - |
dc.contributor.author | 고원진 | - |
dc.contributor.author | 김정욱 | - |
dc.contributor.author | 장재영 | - |
dc.date.available | 2020-02-28T21:44:27Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2014 | - |
dc.identifier.issn | 1738-3331 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/13939 | - |
dc.description.abstract | Background/Aims: Common endoscopic findings in stomachs with Helicobacter pylori infections include antral nodularity, thickened gastric folds, and visible submucosal vessels. These findings are suggestive but not diagnostic of H. pylori infection. Magnifying endoscopy can reveal more precisely the abnormal mucosal patterns in an H. pylori-infected stomach; however, it requires more training, expertise, and time. We aimed to establish a new classification for predicting H. pylori-infected stomachs by non-magnifying standard endoscopy alone. Materials and Methods: A total of 617 participants who underwent gastroscopy were prospectively enrolled from August 2011 to January 2012. We performed a careful close examination of the corpus at the greater curvature maintaining a distance ≤10 mm between the endoscope tip and the mucosal surface. We classified gastric mucosal patterns into four categories: normal regular arrangement of collecting venules (numerous minute red dots), mosaic-like appearance (type A; swollen areae gastricae or snakeskin appearance), diffuse homogenous redness (type B), and mixed pattern (type C; irregular redness with groove) to predict H. pylori infection status. Results: The frequencies of H. pylori infection in patients with a normal regular arrangement of collecting venules pattern and types A, B, and C patterns were 9.4%, 87.7%, 98.1%, and 90.9%, respectively. The sensitivity, specificity, and positive and negative predictive values of all abnormal patterns for prediction of H. pylori infection were 93.3%, 89.1%, 92.3%, and 90.6%, respectively. The overall accuracy was 91.6%. Conclusions: Careful close observation of the gastric mucosal pattern with standard endoscopy can predict H. pylori infection status. | - |
dc.language | 한국어 | - |
dc.language.iso | ko | - |
dc.publisher | 대한상부위장관ㆍ헬리코박터학회 | - |
dc.relation.isPartOf | Korean Journal of Helicobacter Upper Gastrointestinal Research | - |
dc.title | 일반 내시경의 위점막 패턴 근접관찰로 Helicobacter pylori 감염 예측 가능성 연구 | - |
dc.title.alternative | Prediction of Helicobacter pylori Infection Status via Close Observation of Gastric Mucosal Pattern by Standard Endoscopy | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 2 | - |
dc.identifier.doi | 10.7704/kjhugr.2014.14.1.45 | - |
dc.identifier.bibliographicCitation | Korean Journal of Helicobacter Upper Gastrointestinal Research, v.14, no.1, pp.45 - 51 | - |
dc.identifier.kciid | ART001960475 | - |
dc.citation.endPage | 51 | - |
dc.citation.startPage | 45 | - |
dc.citation.title | Korean Journal of Helicobacter Upper Gastrointestinal Research | - |
dc.citation.volume | 14 | - |
dc.citation.number | 1 | - |
dc.contributor.affiliatedAuthor | 김권기 | - |
dc.subject.keywordAuthor | Endoscopy | - |
dc.subject.keywordAuthor | Helicobacter pylori | - |
dc.subject.keywordAuthor | Stomach | - |
dc.description.journalRegisteredClass | kci | - |
dc.description.journalRegisteredClass | other | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.