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Yoshii, Shinji; Mabe, Katsuhiro; Watano, Keiko; Ohno, Masayoshi; Matsumoto, Mio; Ono, Shoko; Kudo, Takahiko; Nojima, Masanori; Kato, Mototsugu; Sakamoto, Naoya
Digestive endoscopy, January 2020, Letnik: 32, Številka: 1Journal Article
Objectives Evaluation of Helicobacter pylori infection status (non‐infection, past infection, current infection) has become important. This study aimed to determine the usefulness of the Kyoto classification of gastritis for diagnosing H. pylori infection status by endoscopy. Methods In this prospective study, 498 subjects were recruited. Seven well‐experienced endoscopists blinded to the history of eradication therapy performed the examinations. Endoscopic findings were assessed according to the Kyoto classification of gastritis: diffuse redness, regular arrangement of collecting venules (RAC), fundic gland polyp (FGP), atrophy, xanthoma, hyperplastic polyp, map‐like redness, intestinal metaplasia, nodularity, mucosal swelling, white and flat elevated lesion, sticky mucus, depressive erosion, raised erosion, red streak, and enlarged folds. We established prediction models according to a machine learning procedure and compared them with general assessment by endoscopists using the Kyoto classification of gastritis. Results Significantly higher diagnostic odds were obtained for RAC (32.2), FGP (7.7), and red streak (4.7) in subjects with non‐infection, map‐like redness (12.9) in subjects with past infection, and diffuse redness (26.8), mucosal swelling (13.3), sticky mucus (10.2) and enlarged fold (8.6) in subjects with current infection. The overall diagnostic accuracy rate was 82.9% with the Kyoto classification of gastritis. The diagnostic accuracy of the prediction model was 88.6% for the model without H. pylori eradication history and 93.4% for the model with eradication history. Conclusions The Kyoto classification of gastritis is useful for diagnosing H. pylori infection status based on endoscopic findings. Our prediction model is helpful for novice endoscopists. (UMIN000016674).
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Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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in: SICRIS
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