Evaluating the Accuracy of the Endoscopic ABC Classification System in Diagnosing Helicobacter pylori-Infected Gastritis

Inui, Masayuki; Ohwada, Susumu; Inui, Yoshikatsu; Kondô, Yûkô; Moro, Amika; Sasaki, Kazunari

doi:10.1159/000498966

Cited by 12 publications

(12 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Two studies used retrospective image collection but were deemed only medium risk of bias; these were therefore included in the analysis. 37,38 Overall, the studies showed low risk of bias and good applicability. The results are displayed in Figure 2.…”

Section: Quality Assessmentmentioning

confidence: 85%

“…47 This has encouraged the development of classification systems such as the Endoscopic ABC 48 which show a high degree of accuracy for prediction of H pylori status. 37 The interpretation of endoscopic findings remains complex however, and a simple identification system for the general endoscopist would be of use to allow rapid diagnosis of H pylori status in a less specialist setting.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

The endoscopic predictors of Helicobacter pylori status: a meta-analysis of diagnostic performance

Glover

Teare

Ashrafian

et al. 2020

Clin Med Insights Gastroenterol

View full text Add to dashboard Cite

Objective: The endoscopic findings associated with Helicobacter pylori–naïve status, current infection or past infection are an area of ongoing interest. Previous studies have investigated parameters with a potential diagnostic value. The aim of this study was to perform meta-analysis of the available literature to validate the diagnostic accuracy of mucosal features proposed in the Kyoto classification. Data sources: The databases of MEDLINE and Embase, clinicalTrials.gov and the Cochrane Library were systematically searched for relevant studies from October 1999 to October 2019. Methods: A bivariate random effects model was used to produce pooled diagnostic accuracy calculations for each of the studied endoscopic findings. Diagnostic odds ratios and sensitivity and specificity characteristics were calculated to identify significant predictors of H pylori status. Results: Meta-analysis included 4380 patients in 15 studies. The most significant predictor of an H pylori-naïve status was a regular arrangement of collecting venules (diagnostic odds ratio 55.0, sensitivity 78.3%, specificity 93.8%). Predictors of active H pylori infection were mucosal oedema (18.1, 63.7%, 91.1%) and diffuse redness (14.4, 66.5%, 89.0%). Map-like redness had high specificity for previous H pylori eradication (99.0%), but poor specificity (13.0%). Conclusion: The regular arrangement of collecting venules, mucosal oedema, diffuse redness and map-like redness are important endoscopic findings for determining H pylori status. This meta-analysis provides a tentative basis for developing future endoscopic classification systems.

show abstract

Section: Quality Assessmentmentioning

confidence: 85%

Section: Discussionmentioning

confidence: 99%

The endoscopic predictors of Helicobacter pylori status: a meta-analysis of diagnostic performance

Glover

Teare

Ashrafian

et al. 2020

Clin Med Insights Gastroenterol

View full text Add to dashboard Cite

show abstract

“…However, we selected the gastric site for assessment of the GC risk based on the assumption that premalignant changes in the stomach could spread from one part to another. To differentiate the moderate‐ and low‐risk groups, we restricted the images to the antrum and lesser curvature of the gastric body because the initial change of H. pylori infection appears in these regions of the gastric body . To differentiate the moderate‐ and high‐risk groups, we restricted the images to the gastric body and fornix because morphological changes in these regions may be more closely related to the risk of GC than those in the antrum .…”

Section: Discussionmentioning

confidence: 99%

Stratification of gastric cancer risk using a deep neural network

Nakahira

Ishihara

Aoyama³

et al. 2019

JGH Open

View full text Add to dashboard Cite

Background and Aim Stratifying gastric cancer (GC) risk and endoscopy findings in high‐risk individuals may provide effective surveillance for GC. We developed a computerized image‐ analysis system for endoscopic images to stratify the risk of GC. Methods The system was trained using images taken during endoscopic examinations with non‐magnified white‐light imaging. Patients were classified as high‐risk (patients with GC), moderate‐risk (patients with current or past Helicobacter pylori infection or gastric atrophy), or low‐risk (patients with no history of H. pylori infection or gastric atrophy). After selection, 20,960, 17,404, and 68,920 images were collected as training images for the high‐, moderate‐, and low‐risk groups, respectively. Results Performance of the artificial intelligence (AI) system was evaluated by the prevalence of GC in each group using an independent validation dataset of patients who underwent endoscopic examination and H. pylori serum antibody testing. In total, 12,824 images from 454 patients were included in the analysis. The time required for diagnosing all the images was 345 seconds. The AI system diagnosed 46, 250, and 158 patients as low‐, moderate‐, and high risk, respectively. The prevalence of GC in the low‐, moderate‐, and high‐risk groups was 2.2, 8.8, and 16.4%, respectively (P = 0.0017). Three experienced endoscopists also successfully stratified the risk; however, interobserver agreement was not satisfactory (kappa value of 0.27, indicating fair agreement). Conclusion The current AI system detected significant differences in the prevalence of GC among the low‐, moderate‐, and high‐risk groups, suggesting its potential for stratifying GC risk.

show abstract

“…Previous H pylori‐ induced gastritis could be detected using Endo E with an accuracy of 97% and a PPV of 100%, and using Endo D with an accuracy of 87%. The data presented defined new endoscopic tools as potential alternatives for detection of H pylori‐ induced gastritis without further diagnostic measures …”

Section: Gastric Diseasesmentioning

confidence: 99%

Review: Helicobacter pylori and non‐malignant upper gastrointestinal diseases

et al. 2019

View full text Add to dashboard Cite

This review covers recent publications investigating the relationship between Helicobacter pylori infection and gastroesophageal reflux disease, Barrett's esophagus, eosinophilic esophagitis, peptic ulcer disease (PUD), H pylori gastritis, and functional dyspepsia. In the area of gastroesophageal reflux disease, new data suggest that reflux may have a role in the transmission of H pylori infection. In addition to several observational studies, data on alterations in esophageal physiology in patients with H pylori infection are presented. Further evidence for the inverse relationship between H pylori infection and Barrett's esophagus is available in the form of a meta‐analysis from the North American Barrett's and Esophageal Carcinoma Consortium. The relationship between H pylori infection and eosinophilic esophagitis remains uncertain. Although new data do not indicate a significantly lower prevalence of H pylori among patients with eosinophilic esophagitis, a meta‐analysis showed a 37% reduced risk of eosinophilic esophagitis among H pylori‐infected patients. Novel data are presented on the genetic variability of bacterial virulence factors and their relationship with PUD. We also report data on plasma biomarkers, which may detect progression to gastric cancer in H pylori‐associated PUD. A new meta‐analysis was published, which assessed the risk of PUD in low‐dose aspirin users with H pylori infection. Finally, we report on the ongoing attempts to stratify patients with gastritis using endoscopic methods when compared to standard biopsy examination.

show abstract

Evaluating the Accuracy of the Endoscopic ABC Classification System in Diagnosing Helicobacter pylori-Infected Gastritis

Cited by 12 publications

References 21 publications

The endoscopic predictors of Helicobacter pylori status: a meta-analysis of diagnostic performance

The endoscopic predictors of Helicobacter pylori status: a meta-analysis of diagnostic performance

Stratification of gastric cancer risk using a deep neural network

Review: Helicobacter pylori and non‐malignant upper gastrointestinal diseases

Contact Info

Product

Resources

About