Endoscopic Assessment of Helicobacter pylori Infection: Validation of a Modified Kyoto Classification System in Real-world Clinical Practice

Endoscopic Assessment of Helicobacter pylori Infection: Validation of a Modified Kyoto Classification System in Real-world Clinical Practice | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Endoscopic Assessment of Helicobacter pylori Infection: Validation of a Modified Kyoto Classification System in Real-world Clinical Practice Junkui Wu, Tao Yang, Qiuning Wu, Yanan Liu, Jiancong Hu, Minhui Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8376050/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background: While Helicobacter pylori remains a cornerstone pathogen in gastric disease pathogenesis, current diagnostic approaches face practical limitations in routine endoscopic practice. The original Kyoto classification system, though valuable, requires refinement for optimal real-world clinical utility in diverse populations. Methods: We retrospectively analyzed endoscopic findings from 276 patients who underwent both gastroscopy and confirmatory H. pylori testing (urea breath test or histopathological examination) between January 2020 and December 2023. Two experienced endoscopists independently scored gastric mucosal features using this modified Kyoto classification system, with discrepancies resolved through consensus review. Results: This modified scoring system demonstrated moderate correlation with laboratory-confirmed H. pylori status (r = 0.366, p < 0.001). ROC analysis revealed an AUC of 0.74, with optimal diagnostic threshold at 6.0 points yielding 59.8% sensitivity and 74.6% specificity. Feature-specific analysis revealed that enlarged gastric folds (r = 0.265) and spotty redness (r = 0.258) were correlated with H. pylori infection status. Interpretation: Despite inherent limitations in endoscopic assessment, this modified classification system offers practical value for real-time H. pylori evaluation during routine gastroscopy. However, clinicians should recognize its complementary rather than replacement role alongside established diagnostic methods. Helicobacter pylori endoscopy gastritis classification diagnostic accuracy clinical validation Figures Figure 1 Figure 2 Introduction The relationship between Helicobacter pylori and gastric pathology represents one of medicine's most compelling examples of how a single microorganism can fundamentally alter disease understanding [ 1 ]. Since Warren and Marshall's groundbreaking work in the 1980s, we have witnessed a paradigm shift from viewing peptic ulcers as stress-related conditions to recognizing them as infectious diseases [ 2 – 3 ]. Yet despite decades of research, the practical challenge of accurately diagnosing H. pylori infection during routine endoscopy remains frustratingly elusive [ 4 – 5 ]. Current diagnostic strategies present a familiar clinical dilemma. Non-invasive methods like urea breath testing, while convenient, suffer from well-documented interference by proton pump inhibitors and antibiotics—medications commonly used [ 6 ]. Yet despite decades of research, the practical challenge of accurately examining, though considered the gold standard, introduces sampling bias and delays that can compromise clinical decision-making [ 7 – 8 ]. More importantly, these approaches often disconnect the diagnostic process from the endoscopic procedure itself, missing opportunities for immediate clinical correlation. The Japanese Gastroenterological Endoscopy Society's introduction of the Kyoto Classification in 2013 represented an ambitious attempt to bridge this gap [ 9 ]. By systematically cataloguing endoscopic features associated with H. pylori infection, the classification promised to transform routine gastroscopy into a diagnostic tool capable of real-time pathogen assessment [ 10 ]. The appeal is obvious: imagine being able to determine infection status while the patient remains on the examination table, enabling immediate therapeutic discussions and eliminating the anxiety of waiting for laboratory results. However, early enthusiasm for the Kyoto system has been tempered by practical realities. Studies across different color imaging scores have yielded inconsistent results [ 11 ]. The subjective nature of many endoscopic features has raised questions about inter-observer reliability, while the complexity of the original 19-feature system has limited widespread adoption in busy clinical settings [ 12 – 14 ]. These limitations have sparked numerous attempts at modification and simplification. Wang and colleagues proposed a streamlined scoring system specifically validated in populations [ 15 ] while Japanese studies have suggested different weighting schemes to improve diagnostic accuracy [ 16 – 17 ]. Yet despite these efforts, no consensus has emerged regarding optimal scoring methodology or diagnostic thresholds. Our institution's experience with the original Kyoto classification mirrored these broader challenges [ 9 ]. While we appreciated the systematic approach to gastric mucosal assessment, we found certain features difficult to standardize and others less relevant to our patient population. This prompted us to further validate this modified scoring system that retained the conceptual framework of the original classification while addressing practical implementation concerns. The present study represents our attempt to validate this modified approach in a real-world clinical setting. Rather than pursuing perfect diagnostic accuracy—an unrealistic goal given the inherent limitations of visual assessment—we sought to determine whether this modified system could provide clinically useful information to complement existing diagnostic methods. Our focus was on practical utility: could this scoring system help endoscopists make more informed decisions about H. pylori testing and treatment during routine procedures? We approached this validation with appropriate skepticism, recognizing that endoscopic assessment alone cannot replace established diagnostic methods. However, we also acknowledged the potential value of any tool that could enhance clinical decision-making during gastroscopy, particularly in settings where immediate laboratory confirmation is unavailable or impractical. Methods Study Design and Participants We conducted a retrospective analysis of patients who underwent upper endoscopy at our institution between January 2020 and December 2023. The gastroscopic operation was performed using the Evis Lucera with a CV-290 endoscope (Olympus, Tokyo, Japan). Our inclusion criteria were deliberately broad to reflect real-world clinical practice: adults aged 18–75 years who completed both endoscopic examination and confirmatory H. pylori testing within a 30-day window. No matter H. pylori treatment or PPI use before 30-days ago. We excluded patients with known gastric malignancy, active gastrointestinal bleeding, or incomplete endoscopic documentation. Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research. The application of exemption from informed consent was obtained from the Ethics Committee, and the study protocol was reviewed and approved by the Ethics Committee of The Sixth Affiliated Hospital, Sun Yat-Sen University (No. E2025109). Endoscopic Assessment Protocol All examinations were performed using standard upper endoscopes (Olympus GIF-HQ290) by staff endoscopists with at least five years of experience in gastric mucosal assessment. We established a standardized imaging protocol requiring systematic documentation of the gastric antrum, corpus, and fundus, with particular attention to areas typically affected by H. pylori-associated changes. This modified Kyoto classification system was developed through iterative refinement, building on the original framework proposed by Wang et al. [ 15 ]. We retained eight key features that demonstrated good inter-observer reliability in our preliminary assessments: mucosal atrophy (0–2 points), enlarged gastric folds (0–2 points), nodularity (0–3 points), diffuse redness (0–3 points), turbid mucus lake (0–2 points), spotty redness (0–2 points), regular arrangement of collecting venules (RAC) visibility (0- -2 points), and fundic gland polyps (0–2 points). The total score ranged from − 4 to 14 points, with negative values indicating features suggestive of non-infection (Table 1 ). Two senior endoscopists independently reviewed all stored images, blinded to clinical information and laboratory results. When scoring discrepancies exceeded one point for any feature, a consensus review was conducted with a third experienced endoscopist (> 10 years of experience) serving as arbitrator. This approach balanced the need for standardization with practical considerations of clinical workflow. Reference Standard Testing We accepted either positive urea breath testing or histopathological confirmation as evidence of active H. pylori infection. Urea breath tests were performed using 13C-labeled urea with mass spectrometry analysis, following standard protocols with appropriate medication washout periods. Histopathological assessment involved examination of antrum and corpus biopsies using both hematoxylin-eosin staining and immunohistochemistry when indicated. This dual reference standard approach reflected our clinical reality, where patient preferences, medication history, and clinical circumstances often dictate the choice of confirmatory testing. While acknowledging the theoretical superiority of histopathological diagnosis, we recognized that breath testing remains the most practical option for many patients in routine practice. Statistical Analysis We approached our statistical analysis with careful attention to the limitations inherent in diagnostic accuracy studies. Continuous variables were assessed for normality using the Shapiro-Wilk test, with appropriate parametric or non-parametric methods applied accordingly. Correlation analysis employed Pearson's coefficient for normally distributed data and Spearman's test otherwise. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis, with the area under the curve (AUC) serving as our primary measure of discriminatory ability. We determined optimal diagnostic thresholds using Youden's index, while acknowledging that clinical utility might favor different thresholds depending on the specific clinical scenario. Inter-observer agreement was assessed using Cohen's kappa coefficient, with standard interpretations: values below 0.2 indicating slight agreement, 0.21–0.40 fair agreement, 0.41–0.60 moderate agreement, and above 0.61 substantial agreement. We recognized that perfect agreement was unrealistic given the subjective nature of endoscopic assessment. All analyses were performed using Python 3.9 (pandas, scikit-learn libraries), with statistical significance set at p < 0.05. We report 95% confidence intervals for all point estimates and acknowledge the exploratory nature of our subgroup analyses. Results Patient Characteristics and H. pylori Prevalence Our cohort comprised 276 patients, mirroring the demographic patterns commonly seen among patients undergoing diagnostic gastroscopy in The Sixth Affiliated Hospital, Sun Yat-Sen University. The slight male predominance (56.9%) and mean age of 45.2 years aligned with epidemiological data for H. pylori-related gastric disease in our region (Table 2 ). Table 2 Patient Basic Information Category Value Gender (Male) % 157 (56.9%) Age (M, P25-P75) years 44.96 (34, 55) RAC positivity (%) Present (4.3%) Fundic polyp (%) Present (1.1%) Diffuse redness (%) Absent (77.2%) Spotty redness (%) Present (43.8%) Enlarged fold (%) Present (80.4%) Sticky mucus (%) Present (93.1%) Nodularity (%) Present (5.4%) Atrophy (%) None-C1 62.70% & C2-C3 32.60% & O1-O3 4.70% Modified Kyoto Gastritis Score (M, P25-P75) 5.27 (4–7) Endoscopic HP positivity (%) 86.20% Urea breath test or endoscopic pathology HP positivity (%) 75.70% This high prevalence rate influenced our subsequent analyses, as it affects the positive and negative predictive values of any diagnostic test. In populations with lower H. pylori prevalence, the same scoring system would likely demonstrate different performance characteristics—a consideration crucial for international applicability. Endoscopic Scoring Distribution and Correlation Analysis The distribution of modified Kyoto scores revealed interesting patterns that challenged some of our initial assumptions. Scores ranged from − 2 to + 12 points, with a median of 5.0 (IQR 3.0–7.0) in H. pylori-positive patients compared to 3 (IQR 1.0–5.0) in negative patients. While this difference was statistically significant (p < 0.001), the substantial overlap between groups highlighted the inherent limitations of visual assessment. The correlation between this modified score and laboratory-confirmed H. pylori status (r = 0.366, p < 0.001) was moderate but encouraging. This correlation, while not exceptional, compared favorably with published data for other endoscopic scoring systems. More importantly, it suggested that this modifications had preserved the diagnostic signal present in the original Kyoto classification while potentially improving practical applicability (Fig. 1 A). Individual feature analysis revealed that nodularity (present in 78% of H. pylori-positive vs. 34% of negative patients) and diffuse redness (82% vs. 41%) were the most discriminatory features. Conversely, fundic gland polyps showed an inverse relationship, being more common in H. pylori-negative patients—a finding consistent with the protective effect of acid suppression in uninfected individuals (Fig. 1 B). ROC analysis yielded an AUC of 0.74 (95% CI 0.68–0.80), indicating fair to good discriminatory ability (Fig. 1 C). While this fell short of the diagnostic accuracy achieved by laboratory methods, it represented a clinically meaningful improvement over chance alone. The optimal threshold of 6.0 points, determined by Youden's index, provided the best balance between sensitivity (53.7%) and specificity (87.5%) (Fig. 1 D). These performance metrics deserve careful interpretation. The moderate sensitivity suggests that relying solely on endoscopic assessment would miss approximately 40% of H. pylori infections—clearly unacceptable for definitive diagnosis. However, the reasonable specificity indicates that high scores (≥ 6 points) provide useful confirmatory evidence when clinical suspicion is already present. We explored alternative thresholds to understand how diagnostic performance might vary with different clinical priorities. A lower threshold of 4.0 points improved sensitivity to 90.0% but reduced specificity to 37.5%, while a higher threshold of 8.0 points achieved 98.1% specificity at the cost of only 17.9% sensitivity. These trade-offs illustrate why no single threshold can optimize performance across all clinical scenarios (Fig. 1 D). Inter-observer Agreement and Reliability The kappa coefficient of 0.341 indicated moderate inter-observer agreement, falling within the range reported for other endoscopic classification systems. While this level of agreement might seem disappointing, it reflects the inherent subjectivity of visual assessment and the challenge of standardizing complex morphological features (Fig. 2 A). Feature-specific analysis revealed varying associations with H. pylori infection status. Among the endoscopic features examined, enlarged gastric folds showed the strongest correlation with laboratory-confirmed infection (r = 0.265), followed by spotty redness (r = 0.258). These findings suggest that certain endoscopic features are more reliable indicators of H. pylori infection than others (Fig. 2 B). Discussion Clinical Significance and Practical Implications Rather than replacing established diagnostic methods, these tools might serve as real-world clinical decision aids, helping endoscopists determine when additional testing is most warranted or when empirical treatment might be considered. In resource-limited settings where immediate laboratory confirmation is unavailable, even moderate diagnostic accuracy could provide meaningful clinical value. The threshold analysis reveals particularly important insights for practical implementation. Our optimal threshold of 6.0 points represents a compromise between sensitivity and specificity that may not suit all clinical scenarios. In screening situations where missing infections carries high consequences, a lower threshold might be preferable despite increased false positives. Conversely, when confirming suspected infection before treatment, a higher threshold might reduce unnecessary interventions. Feature-specific analysis revealed that enlarged gastric folds and spotty redness were correlated with H. pylori infection status in real-world clinical practice. Comparison with Existing Literature Our results align reasonably well with previous validation studies of Kyoto-based scoring systems, though direct comparisons are complicated by methodological differences and population variations. The AUC of 0.74 falls within the range reported by most studies (0.63–0.82), suggesting that this modifications preserved the diagnostic signal of the original classification while potentially improving practical applicability [ 18 – 19 ]. The moderate inter-observer agreement we observed (κ = 0.54) mirrors findings from other endoscopic classification studies and highlights a persistent challenge in this field [ 20 ]. Methodological Considerations and Limitations Several aspects of our study design deserve critical examination. Our retrospective approach, while practical, introduced potential selection bias since we could only include patients who had undergone both endoscopy and confirmatory testing. This might have enriched our sample with patients having higher clinical suspicion for H. pylori infection, potentially inflating our prevalence estimates and affecting diagnostic performance metrics. The use of stored images for scoring, rather than real-time assessment, represents both a strength and limitation. While this approach ensured standardized evaluation conditions and enabled blinded assessment, it may not fully reflect the diagnostic accuracy achievable during live endoscopy, where additional visual cues and dynamic assessment might be available. Future Directions and Research Opportunities The moderate performance of our modified scoring system suggests several avenues for improvement. Machine learning approaches might help optimize feature weighting and identify subtle patterns not apparent to human observers. Computer-aided diagnosis systems could potentially reduce inter-observer variability while maintaining or improving diagnostic accuracy. Prospective validation in diverse populations represents another critical need. Our single-center, retrospective design limits generalizability, particularly to populations with different H. pylori prevalence rates or genetic backgrounds in real-world clinical practice. Multi-center studies incorporating real-time scoring would provide more robust evidence for clinical implementation. The integration of advanced endoscopic techniques, such as narrow-band imaging or magnification endoscopy, might enhance the discriminatory power of morphological assessment. However, such approaches would need to balance improved accuracy against increased complexity and cost. Clinical Implementation Considerations Despite its limitations, this modified scoring system offers several practical advantages that might facilitate clinical adoption. The simplified feature set reduces scoring complexity compared to the original Kyoto classification, while the numerical output provides an intuitive framework for clinical decision-making. Training requirements represent a crucial consideration for widespread implementation. Our finding that experienced endoscopists achieved only moderate inter-observer agreement suggests that systematic training programs would be essential for consistent application. Standardized image libraries and scoring exercises might help improve reliability across different practitioners and institutions. The economic implications of endoscopic scoring also merit consideration. While the scoring itself adds minimal cost to routine endoscopy, its value depends on how it influences subsequent testing and treatment decisions. We must acknowledge several important limitations that temper enthusiasm for our findings. The moderate diagnostic accuracy means that endoscopic scoring cannot replace established diagnostic methods, and the substantial inter-observer variability raises questions about consistency in clinical practice. Our single-center design and retrospective approach limit generalizability, while the high H. pylori prevalence in our population may not reflect patterns in other regions. The use of stored images, though methodologically sound, may not fully capture the diagnostic accuracy achievable during live endoscopy. Perhaps most importantly, we have not demonstrated that using this scoring system actually improves patient outcomes compared to standard diagnostic approaches. While diagnostic accuracy is important, the ultimate test of any clinical tool is whether it enhances patient care in meaningful ways. Conclusion Our validation of a modified Kyoto gastritis classification system yields a nuanced picture of endoscopic assessment's role in H. pylori diagnosis. While the moderate diagnostic accuracy (AUC = 0.74) falls short of laboratory methods, it suggests potential value as a complementary clinical tool rather than a replacement for established diagnostic approaches. The practical implications are clear: endoscopic scoring can provide useful information during routine gastroscopy, particularly when immediate laboratory confirmation is unavailable. However, clinicians must recognize its limitations and use it judiciously as part of a comprehensive diagnostic strategy. The moderate inter-observer agreement underscores the need for standardized training if widespread implementation is contemplated. Perhaps most importantly, our study highlights the ongoing challenge of bridging the gap between research observations and clinical practice. While endoscopic features clearly correlate with H. pylori infection, translating these associations into reliable diagnostic tools remains complex. Future research should focus on prospective validation, cost-effectiveness analysis, and ultimately, demonstration of improved patient outcomes. Declarations Conflict of interest The authors declare that they have no conflict of interest. Author contributions These authors contributed equally: Junkui Wu, Tao Yang Ethics Committee The application of exemption from informed consent was obtained from the Ethics Committee, and the study protocol was reviewed and approved by the Ethics Committee of The Sixth Affiliated Hospital, Sun Yat-Sen University (No. E2025109). Disclosure statement Junkui Wu, Tao Yang, Yanan Liu, Qiuning Wu, Jiancong Hu, Minhui Hu have no conflicts of interest or financial ties to disclose. References Moss SF. The Clinical Evidence Linking Helicobacter pylori to Gastric Cancer. Cell Mol Gastroenterol Hepatol. 2016;3(2):183–91. 10.1016/j.jcmgh.2016.12.001 . Marshall BJ, Warren RM. Unidentified curved bacilli in the stomach of patients with gastritis and peptic ulceration. Lancet. 1984;16:1311–5. 10.1016/S0140-6736(84)91816-6 . Marshall BJ, Armstrong JA, McGechie DB. Attempt to fulfill Koch's postulates for pyloric campylobacter. Med J Australia. 1985;142:436–9. 10.5694/j.1326-5377.1985.tb113443.x . Gong EJ, Jung K. Endoscopic diagnosis of Helicobacter pylori infection. Kosin Med J. 2025;40(1):4–14. Ji R, Li YQ. Diagnosing Helicobacter pylori infection in vivo by novel endoscopic techniques. World J Gastroenterol. 2014;20(28):9314–20. 10.3748/wjg.v20.i28.9314 . Kayali S, Aloe R, Bonaguri C. Non-invasive tests for the diagnosis of helicobacter pylori: state of the art. Acta Biomed. 2018;89(8–S):58–64. 10.23750/abm.v89i8-S.7910 . Liao EC, Yu CH, Lai JH. A pilot study of non-invasive diagnostic tools to detect Helicobacter pylori infection and peptic ulcer disease. Sci Rep. 2023;13(1):22800. 10.1038/s41598-023-50266-2 . Mégraud F, Lehours P. Helicobacter pylori detection and antimicrobial susceptibility testing. Clin Microbiol Rev. 2007;20(2):280–322. 10.1128/CMR.00033-06 . Kato M, Kamada T. Endoscopic Findings for Risk Stratification of Gastric Cancer. In: Haruma K, Kato M, Inoue K, Murakami K, Kamada T, editors. Kyoto Classification of Gastritis. 1st ed. Tokyo: Nihon Medical Center; 2017. pp. 97–110. Seo JY, Ahn JY, Kim S. et.al. Predicting Helicobacter pylori infection from endoscopic features. Korean J Intern Med. 2024;39(3):439–447. 10.3904/kjim.2023.300 . Epub 2024 Apr 30. PMID: 38715232. Jiang ZX, Nong B, Liang LX. Differential diagnosis of Helicobacter pylori-associated gastritis with the linked-color imaging score. Dig Liver Dis. 2019;51(12):1665–70. 10.1016/j.dld.2019.06.024 . Epub 2019 Aug 13. Sugano K, Tack J, Kuipers EJ. et.al; faculty members of Kyoto Global Consensus Conference. Kyoto global consensus report on Helicobacter pylori gastritis. Gut. 2015;64(9):1353-67. 10.1136/gutjnl-2015-309252 . Epub 2015 Jul 17. Toyoshima O, Nishizawa T, Koike K. Endoscopic Kyoto classification of Helicobacter pylori infection and gastric cancer risk diagnosis. World J Gastroenterol. 2020;26(5):466–77. 10.3748/wjg.v26.i5.466 . Sugano K, Tack J et al. Kuipers EJ on behalf of faculty members of Kyoto Global Consensus Conference, Kyoto global consensus report on Helicobacter pylori gastritis Gut 2015;64:1353–1367. Wang K et al. Establishment of a modified Kyoto classification scoring model and its significance in the diagnosis of Helicobacter pylori current infection. Gastrointestinal Endoscopy, Volume 97, Issue 4, 684–93. Toyoshima O, Nishizawa T. Kyoto classification of gastritis: Advances and future perspectives in endoscopic diagnosis of gastritis. World J Gastroenterol. 2022;28(43):6078–89. 10.3748/wjg.v28.i43.6078 . Sugimoto M, Ban H, Ichikawa H. Efficacy of the Kyoto Classification of Gastritis in Identifying Patients at High Risk for Gastric Cancer. Intern Med. 2017;56(6):579–86. 10.2169/internalmedicine.56.7775 . Epub 2017 Mar 17. PMID: 28321054; PMCID: PMC5410464. Zhang Mengjiao W, Lianlian X, Daqi, et al. Artificial intelligence–assisted diagnosis system of Helicobacter pyloriinfection based on deep learning[J]. Chin J Dig Endosc. 2023;40(2):109–14. 10.3760/cma.j.cn321463-20211021-00473 . Zhang Mengjiao W, Lianlian X, Ming, et al. Evaluationof Kyoto gastritis score for Helicobacterpyloriinfection under gastroscopy[J]. Chin J Dig Endosc. 2022;39(9):707–13. Quach DT, Aoki R, Iga A, et.al. Diagnostic Accuracy of H. pylori Status by Conventional Endoscopy: Time-Trend Change After Eradication and Impact of Endoscopic Image Quality. Front Med. 2022;8:830730. 10.3389/fmed.2021.830730 . Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Dec, 2025 Editor assigned by journal 21 Dec, 2025 Submission checks completed at journal 21 Dec, 2025 First submitted to journal 16 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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12:30:41","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47459,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8376050/v1/8ec6eb1f5162967c53833080.png"},{"id":98780875,"identity":"6b5f8398-c9cf-4322-a08e-9f8e411c8d39","added_by":"auto","created_at":"2025-12-22 12:31:47","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":23199,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8376050/v1/985804568ea82d94760d72e0.png"},{"id":98765695,"identity":"2defc995-5f5a-428d-ada0-9381a7c48159","added_by":"auto","created_at":"2025-12-22 10:12:59","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66785,"visible":true,"origin":"","legend":"","description":"","filename":"48d05845a3784067a8cc160f650b2f261structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8376050/v1/f0cd63d5adaacfd4f298260d.xml"},{"id":98779445,"identity":"378b3ac4-ae43-4c0b-8bf2-c9bd974edf60","added_by":"auto","created_at":"2025-12-22 12:30:21","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":75663,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8376050/v1/e982810e6045170ee9964b99.html"},{"id":98765688,"identity":"ea6cbed3-5635-4d8d-bc61-67d9ef4b9e47","added_by":"auto","created_at":"2025-12-22 10:12:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":428203,"visible":true,"origin":"","legend":"\u003cp\u003eEndoscopic Scoring Distribution and Correlation Analysis. A: Kyoto Score Distribution by H. pylori Diagnosis. B: Distribution of Modified Kyoto Gastritis Classification Score by H. pylori Diagnosis. C: The ROC curve of modified Kyoto gastritis classification score. D: Threshold performance analysis of modified Kyoto gastritis classification score.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8376050/v1/8c0e8888931c060e5a8bf773.png"},{"id":98780313,"identity":"c8f98ae4-e64d-488d-8b30-02678e4f3cf3","added_by":"auto","created_at":"2025-12-22 12:31:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90998,"visible":true,"origin":"","legend":"\u003cp\u003eInter-observer Agreement and Reliability. A: Confusion Matrix: Laboratory vs. Endoscopic Diagnosis. B: Correlations Between Features and H. pylori Infection\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8376050/v1/c7d00ac6a9562d14eedef5e9.png"},{"id":98786405,"identity":"956462ba-3cd4-4697-97ee-3ac63d248175","added_by":"auto","created_at":"2025-12-22 12:43:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":887249,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8376050/v1/56841702-0642-4c69-9313-e471ce2f81bc.pdf"},{"id":98765685,"identity":"1128d4de-ceb5-4d72-9889-a151bec7c274","added_by":"auto","created_at":"2025-12-22 10:12:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15219,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8376050/v1/2b67e69ed84a74cf1ce852cb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Endoscopic Assessment of Helicobacter pylori Infection: Validation of a Modified Kyoto Classification System in Real-world Clinical Practice","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe relationship between Helicobacter pylori and gastric pathology represents one of medicine's most compelling examples of how a single microorganism can fundamentally alter disease understanding [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Since Warren and Marshall's groundbreaking work in the 1980s, we have witnessed a paradigm shift from viewing peptic ulcers as stress-related conditions to recognizing them as infectious diseases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e–\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Yet despite decades of research, the practical challenge of accurately diagnosing H. pylori infection during routine endoscopy remains frustratingly elusive [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCurrent diagnostic strategies present a familiar clinical dilemma. Non-invasive methods like urea breath testing, while convenient, suffer from well-documented interference by proton pump inhibitors and antibiotics—medications commonly used [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Yet despite decades of research, the practical challenge of accurately examining, though considered the gold standard, introduces sampling bias and delays that can compromise clinical decision-making [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e–\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. More importantly, these approaches often disconnect the diagnostic process from the endoscopic procedure itself, missing opportunities for immediate clinical correlation.\u003c/p\u003e \u003cp\u003eThe Japanese Gastroenterological Endoscopy Society's introduction of the Kyoto Classification in 2013 represented an ambitious attempt to bridge this gap [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. By systematically cataloguing endoscopic features associated with H. pylori infection, the classification promised to transform routine gastroscopy into a diagnostic tool capable of real-time pathogen assessment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The appeal is obvious: imagine being able to determine infection status while the patient remains on the examination table, enabling immediate therapeutic discussions and eliminating the anxiety of waiting for laboratory results.\u003c/p\u003e \u003cp\u003eHowever, early enthusiasm for the Kyoto system has been tempered by practical realities. Studies across different color imaging scores have yielded inconsistent results [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The subjective nature of many endoscopic features has raised questions about inter-observer reliability, while the complexity of the original 19-feature system has limited widespread adoption in busy clinical settings [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e–\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese limitations have sparked numerous attempts at modification and simplification. Wang and colleagues proposed a streamlined scoring system specifically validated in populations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] while Japanese studies have suggested different weighting schemes to improve diagnostic accuracy [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e–\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Yet despite these efforts, no consensus has emerged regarding optimal scoring methodology or diagnostic thresholds.\u003c/p\u003e \u003cp\u003eOur institution's experience with the original Kyoto classification mirrored these broader challenges [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. While we appreciated the systematic approach to gastric mucosal assessment, we found certain features difficult to standardize and others less relevant to our patient population. This prompted us to further validate this modified scoring system that retained the conceptual framework of the original classification while addressing practical implementation concerns.\u003c/p\u003e \u003cp\u003eThe present study represents our attempt to validate this modified approach in a real-world clinical setting. Rather than pursuing perfect diagnostic accuracy—an unrealistic goal given the inherent limitations of visual assessment—we sought to determine whether this modified system could provide clinically useful information to complement existing diagnostic methods. Our focus was on practical utility: could this scoring system help endoscopists make more informed decisions about H. pylori testing and treatment during routine procedures?\u003c/p\u003e \u003cp\u003eWe approached this validation with appropriate skepticism, recognizing that endoscopic assessment alone cannot replace established diagnostic methods. However, we also acknowledged the potential value of any tool that could enhance clinical decision-making during gastroscopy, particularly in settings where immediate laboratory confirmation is unavailable or impractical.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eStudy Design and Participants\u003c/p\u003e\n\u003cp\u003eWe conducted a retrospective analysis of patients who underwent upper endoscopy at our institution between January 2020 and December 2023. The gastroscopic operation was performed using the Evis Lucera with a CV-290 endoscope (Olympus, Tokyo, Japan). Our inclusion criteria were deliberately broad to reflect real-world clinical practice: adults aged 18\u0026ndash;75 years who completed both endoscopic examination and confirmatory H. pylori testing within a 30-day window. No matter H. pylori treatment or PPI use before 30-days ago. We excluded patients with known gastric malignancy, active gastrointestinal bleeding, or incomplete endoscopic documentation. Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research. The application of exemption from informed consent was obtained from the Ethics Committee, and the study protocol was reviewed and approved by the Ethics Committee of The Sixth Affiliated Hospital, Sun Yat-Sen University (No. E2025109).\u003c/p\u003e\n\u003cp\u003eEndoscopic Assessment Protocol\u003c/p\u003e\n\u003cp\u003eAll examinations were performed using standard upper endoscopes (Olympus GIF-HQ290) by staff endoscopists with at least five years of experience in gastric mucosal assessment. We established a standardized imaging protocol requiring systematic documentation of the gastric antrum, corpus, and fundus, with particular attention to areas typically affected by H. pylori-associated changes.\u003c/p\u003e\n\u003cp\u003eThis modified Kyoto classification system was developed through iterative refinement, building on the original framework proposed by Wang et al. [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. We retained eight key features that demonstrated good inter-observer reliability in our preliminary assessments: mucosal atrophy (0\u0026ndash;2 points), enlarged gastric folds (0\u0026ndash;2 points), nodularity (0\u0026ndash;3 points), diffuse redness (0\u0026ndash;3 points), turbid mucus lake (0\u0026ndash;2 points), spotty redness (0\u0026ndash;2 points), regular arrangement of collecting venules (RAC) visibility (0- -2 points), and fundic gland polyps (0\u0026ndash;2 points). The total score ranged from \u0026minus;\u0026thinsp;4 to 14 points, with negative values indicating features suggestive of non-infection (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eTwo senior endoscopists independently reviewed all stored images, blinded to clinical information and laboratory results. When scoring discrepancies exceeded one point for any feature, a consensus review was conducted with a third experienced endoscopist (\u0026gt;\u0026thinsp;10 years of experience) serving as arbitrator. This approach balanced the need for standardization with practical considerations of clinical workflow.\u003c/p\u003e\n\u003cp\u003eReference Standard Testing\u003c/p\u003e\n\u003cp\u003eWe accepted either positive urea breath testing or histopathological confirmation as evidence of active H. pylori infection. Urea breath tests were performed using 13C-labeled urea with mass spectrometry analysis, following standard protocols with appropriate medication washout periods. Histopathological assessment involved examination of antrum and corpus biopsies using both hematoxylin-eosin staining and immunohistochemistry when indicated.\u003c/p\u003e\n\u003cp\u003eThis dual reference standard approach reflected our clinical reality, where patient preferences, medication history, and clinical circumstances often dictate the choice of confirmatory testing. While acknowledging the theoretical superiority of histopathological diagnosis, we recognized that breath testing remains the most practical option for many patients in routine practice.\u003c/p\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eWe approached our statistical analysis with careful attention to the limitations inherent in diagnostic accuracy studies. Continuous variables were assessed for normality using the Shapiro-Wilk test, with appropriate parametric or non-parametric methods applied accordingly. Correlation analysis employed Pearson\u0026apos;s coefficient for normally distributed data and Spearman\u0026apos;s test otherwise.\u003c/p\u003e\n\u003cp\u003eDiagnostic performance was evaluated using receiver operating characteristic (ROC) analysis, with the area under the curve (AUC) serving as our primary measure of discriminatory ability. We determined optimal diagnostic thresholds using Youden\u0026apos;s index, while acknowledging that clinical utility might favor different thresholds depending on the specific clinical scenario.\u003c/p\u003e\n\u003cp\u003eInter-observer agreement was assessed using Cohen\u0026apos;s kappa coefficient, with standard interpretations: values below 0.2 indicating slight agreement, 0.21\u0026ndash;0.40 fair agreement, 0.41\u0026ndash;0.60 moderate agreement, and above 0.61 substantial agreement. We recognized that perfect agreement was unrealistic given the subjective nature of endoscopic assessment.\u003c/p\u003e\n\u003cp\u003eAll analyses were performed using Python 3.9 (pandas, scikit-learn libraries), with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. We report 95% confidence intervals for all point estimates and acknowledge the exploratory nature of our subgroup analyses.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003ePatient Characteristics and H. pylori Prevalence\u003c/p\u003e \u003cp\u003eOur cohort comprised 276 patients, mirroring the demographic patterns commonly seen among patients undergoing diagnostic gastroscopy in The Sixth Affiliated Hospital, Sun Yat-Sen University. The slight male predominance (56.9%) and mean age of 45.2 years aligned with epidemiological data for H. pylori-related gastric disease in our region (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Basic Information\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCategory Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (Male) %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (56.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (M, P25-P75) years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.96 (34, 55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAC positivity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePresent (4.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFundic polyp (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePresent (1.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiffuse redness (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbsent (77.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpotty redness (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePresent (43.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnlarged fold (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePresent (80.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSticky mucus (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePresent (93.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNodularity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePresent (5.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrophy (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone-C1 62.70% \u0026amp; C2-C3 32.60% \u0026amp; O1-O3 4.70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModified Kyoto Gastritis Score (M, P25-P75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.27 (4\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndoscopic HP positivity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea breath test or endoscopic pathology HP positivity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThis high prevalence rate influenced our subsequent analyses, as it affects the positive and negative predictive values of any diagnostic test. In populations with lower H. pylori prevalence, the same scoring system would likely demonstrate different performance characteristics\u0026mdash;a consideration crucial for international applicability.\u003c/p\u003e \u003cp\u003eEndoscopic Scoring Distribution and Correlation Analysis\u003c/p\u003e \u003cp\u003eThe distribution of modified Kyoto scores revealed interesting patterns that challenged some of our initial assumptions. Scores ranged from \u0026minus;\u0026thinsp;2 to +\u0026thinsp;12 points, with a median of 5.0 (IQR 3.0\u0026ndash;7.0) in H. pylori-positive patients compared to 3 (IQR 1.0\u0026ndash;5.0) in negative patients. While this difference was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the substantial overlap between groups highlighted the inherent limitations of visual assessment.\u003c/p\u003e \u003cp\u003eThe correlation between this modified score and laboratory-confirmed H. pylori status (r\u0026thinsp;=\u0026thinsp;0.366, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was moderate but encouraging. This correlation, while not exceptional, compared favorably with published data for other endoscopic scoring systems. More importantly, it suggested that this modifications had preserved the diagnostic signal present in the original Kyoto classification while potentially improving practical applicability (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eIndividual feature analysis revealed that nodularity (present in 78% of H. pylori-positive vs. 34% of negative patients) and diffuse redness (82% vs. 41%) were the most discriminatory features. Conversely, fundic gland polyps showed an inverse relationship, being more common in H. pylori-negative patients\u0026mdash;a finding consistent with the protective effect of acid suppression in uninfected individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eROC analysis yielded an AUC of 0.74 (95% CI 0.68\u0026ndash;0.80), indicating fair to good discriminatory ability (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). While this fell short of the diagnostic accuracy achieved by laboratory methods, it represented a clinically meaningful improvement over chance alone. The optimal threshold of 6.0 points, determined by Youden's index, provided the best balance between sensitivity (53.7%) and specificity (87.5%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese performance metrics deserve careful interpretation. The moderate sensitivity suggests that relying solely on endoscopic assessment would miss approximately 40% of H. pylori infections\u0026mdash;clearly unacceptable for definitive diagnosis. However, the reasonable specificity indicates that high scores (\u0026ge;\u0026thinsp;6 points) provide useful confirmatory evidence when clinical suspicion is already present.\u003c/p\u003e \u003cp\u003eWe explored alternative thresholds to understand how diagnostic performance might vary with different clinical priorities. A lower threshold of 4.0 points improved sensitivity to 90.0% but reduced specificity to 37.5%, while a higher threshold of 8.0 points achieved 98.1% specificity at the cost of only 17.9% sensitivity. These trade-offs illustrate why no single threshold can optimize performance across all clinical scenarios (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eInter-observer Agreement and Reliability\u003c/p\u003e \u003cp\u003eThe kappa coefficient of 0.341 indicated moderate inter-observer agreement, falling within the range reported for other endoscopic classification systems. While this level of agreement might seem disappointing, it reflects the inherent subjectivity of visual assessment and the challenge of standardizing complex morphological features (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eFeature-specific analysis revealed varying associations with H. pylori infection status. Among the endoscopic features examined, enlarged gastric folds showed the strongest correlation with laboratory-confirmed infection (r\u0026thinsp;=\u0026thinsp;0.265), followed by spotty redness (r\u0026thinsp;=\u0026thinsp;0.258). These findings suggest that certain endoscopic features are more reliable indicators of H. pylori infection than others (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eClinical Significance and Practical Implications\u003c/p\u003e \u003cp\u003eRather than replacing established diagnostic methods, these tools might serve as real-world clinical decision aids, helping endoscopists determine when additional testing is most warranted or when empirical treatment might be considered. In resource-limited settings where immediate laboratory confirmation is unavailable, even moderate diagnostic accuracy could provide meaningful clinical value.\u003c/p\u003e \u003cp\u003eThe threshold analysis reveals particularly important insights for practical implementation. Our optimal threshold of 6.0 points represents a compromise between sensitivity and specificity that may not suit all clinical scenarios. In screening situations where missing infections carries high consequences, a lower threshold might be preferable despite increased false positives. Conversely, when confirming suspected infection before treatment, a higher threshold might reduce unnecessary interventions. Feature-specific analysis revealed that enlarged gastric folds and spotty redness were correlated with H. pylori infection status in real-world clinical practice.\u003c/p\u003e \u003cp\u003eComparison with Existing Literature\u003c/p\u003e \u003cp\u003eOur results align reasonably well with previous validation studies of Kyoto-based scoring systems, though direct comparisons are complicated by methodological differences and population variations. The AUC of 0.74 falls within the range reported by most studies (0.63\u0026ndash;0.82), suggesting that this modifications preserved the diagnostic signal of the original classification while potentially improving practical applicability [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe moderate inter-observer agreement we observed (κ\u0026thinsp;=\u0026thinsp;0.54) mirrors findings from other endoscopic classification studies and highlights a persistent challenge in this field [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMethodological Considerations and Limitations\u003c/p\u003e \u003cp\u003eSeveral aspects of our study design deserve critical examination. Our retrospective approach, while practical, introduced potential selection bias since we could only include patients who had undergone both endoscopy and confirmatory testing. This might have enriched our sample with patients having higher clinical suspicion for H. pylori infection, potentially inflating our prevalence estimates and affecting diagnostic performance metrics.\u003c/p\u003e \u003cp\u003eThe use of stored images for scoring, rather than real-time assessment, represents both a strength and limitation. While this approach ensured standardized evaluation conditions and enabled blinded assessment, it may not fully reflect the diagnostic accuracy achievable during live endoscopy, where additional visual cues and dynamic assessment might be available.\u003c/p\u003e \u003cp\u003eFuture Directions and Research Opportunities\u003c/p\u003e \u003cp\u003eThe moderate performance of our modified scoring system suggests several avenues for improvement. Machine learning approaches might help optimize feature weighting and identify subtle patterns not apparent to human observers. Computer-aided diagnosis systems could potentially reduce inter-observer variability while maintaining or improving diagnostic accuracy.\u003c/p\u003e \u003cp\u003eProspective validation in diverse populations represents another critical need. Our single-center, retrospective design limits generalizability, particularly to populations with different H. pylori prevalence rates or genetic backgrounds in real-world clinical practice. Multi-center studies incorporating real-time scoring would provide more robust evidence for clinical implementation. The integration of advanced endoscopic techniques, such as narrow-band imaging or magnification endoscopy, might enhance the discriminatory power of morphological assessment. However, such approaches would need to balance improved accuracy against increased complexity and cost.\u003c/p\u003e \u003cp\u003eClinical Implementation Considerations\u003c/p\u003e \u003cp\u003eDespite its limitations, this modified scoring system offers several practical advantages that might facilitate clinical adoption. The simplified feature set reduces scoring complexity compared to the original Kyoto classification, while the numerical output provides an intuitive framework for clinical decision-making.\u003c/p\u003e \u003cp\u003eTraining requirements represent a crucial consideration for widespread implementation. Our finding that experienced endoscopists achieved only moderate inter-observer agreement suggests that systematic training programs would be essential for consistent application. Standardized image libraries and scoring exercises might help improve reliability across different practitioners and institutions.\u003c/p\u003e \u003cp\u003eThe economic implications of endoscopic scoring also merit consideration. While the scoring itself adds minimal cost to routine endoscopy, its value depends on how it influences subsequent testing and treatment decisions.\u003c/p\u003e \u003cp\u003eWe must acknowledge several important limitations that temper enthusiasm for our findings. The moderate diagnostic accuracy means that endoscopic scoring cannot replace established diagnostic methods, and the substantial inter-observer variability raises questions about consistency in clinical practice. Our single-center design and retrospective approach limit generalizability, while the high H. pylori prevalence in our population may not reflect patterns in other regions. The use of stored images, though methodologically sound, may not fully capture the diagnostic accuracy achievable during live endoscopy.\u003c/p\u003e \u003cp\u003ePerhaps most importantly, we have not demonstrated that using this scoring system actually improves patient outcomes compared to standard diagnostic approaches. While diagnostic accuracy is important, the ultimate test of any clinical tool is whether it enhances patient care in meaningful ways.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur validation of a modified Kyoto gastritis classification system yields a nuanced picture of endoscopic assessment's role in H. pylori diagnosis. While the moderate diagnostic accuracy (AUC\u0026thinsp;=\u0026thinsp;0.74) falls short of laboratory methods, it suggests potential value as a complementary clinical tool rather than a replacement for established diagnostic approaches.\u003c/p\u003e \u003cp\u003eThe practical implications are clear: endoscopic scoring can provide useful information during routine gastroscopy, particularly when immediate laboratory confirmation is unavailable. However, clinicians must recognize its limitations and use it judiciously as part of a comprehensive diagnostic strategy. The moderate inter-observer agreement underscores the need for standardized training if widespread implementation is contemplated.\u003c/p\u003e \u003cp\u003ePerhaps most importantly, our study highlights the ongoing challenge of bridging the gap between research observations and clinical practice. While endoscopic features clearly correlate with H. pylori infection, translating these associations into reliable diagnostic tools remains complex. Future research should focus on prospective validation, cost-effectiveness analysis, and ultimately, demonstration of improved patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eConflict of interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eThese authors contributed equally: Junkui Wu, Tao Yang\u003c/p\u003e\n\u003cp\u003eEthics Committee\u003c/p\u003e\n\u003cp\u003eThe application of exemption from informed consent was obtained from the Ethics Committee, and the study protocol was reviewed and approved by the Ethics Committee of The Sixth Affiliated Hospital, Sun Yat-Sen University (No. E2025109).\u003c/p\u003e\n\u003cp\u003eDisclosure statement\u003c/p\u003e\n\u003cp\u003eJunkui Wu, Tao Yang, Yanan Liu, Qiuning Wu, Jiancong Hu, Minhui Hu have no conflicts of interest or financial ties to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMoss SF. The Clinical Evidence Linking Helicobacter pylori to Gastric Cancer. Cell Mol Gastroenterol Hepatol. 2016;3(2):183\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jcmgh.2016.12.001\u003c/span\u003e\u003cspan address=\"10.1016/j.jcmgh.2016.12.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarshall BJ, Warren RM. Unidentified curved bacilli in the stomach of patients with gastritis and peptic ulceration. Lancet. 1984;16:1311\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(84)91816-6\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(84)91816-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarshall BJ, Armstrong JA, McGechie DB. Attempt to fulfill Koch's postulates for pyloric campylobacter. Med J Australia. 1985;142:436\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5694/j.1326-5377.1985.tb113443.x\u003c/span\u003e\u003cspan address=\"10.5694/j.1326-5377.1985.tb113443.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGong EJ, Jung K. Endoscopic diagnosis of Helicobacter pylori infection. Kosin Med J. 2025;40(1):4\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJi R, Li YQ. Diagnosing Helicobacter pylori infection in vivo by novel endoscopic techniques. World J Gastroenterol. 2014;20(28):9314\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3748/wjg.v20.i28.9314\u003c/span\u003e\u003cspan address=\"10.3748/wjg.v20.i28.9314\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKayali S, Aloe R, Bonaguri C. Non-invasive tests for the diagnosis of helicobacter pylori: state of the art. Acta Biomed. 2018;89(8\u0026ndash;S):58\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.23750/abm.v89i8-S.7910\u003c/span\u003e\u003cspan address=\"10.23750/abm.v89i8-S.7910\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiao EC, Yu CH, Lai JH. A pilot study of non-invasive diagnostic tools to detect Helicobacter pylori infection and peptic ulcer disease. Sci Rep. 2023;13(1):22800. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-023-50266-2\u003c/span\u003e\u003cspan address=\"10.1038/s41598-023-50266-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026eacute;graud F, Lehours P. Helicobacter pylori detection and antimicrobial susceptibility testing. Clin Microbiol Rev. 2007;20(2):280\u0026ndash;322. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/CMR.00033-06\u003c/span\u003e\u003cspan address=\"10.1128/CMR.00033-06\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKato M, Kamada T. Endoscopic Findings for Risk Stratification of Gastric Cancer. In: Haruma K, Kato M, Inoue K, Murakami K, Kamada T, editors. Kyoto Classification of Gastritis. 1st ed. Tokyo: Nihon Medical Center; 2017. pp. 97\u0026ndash;110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeo JY, Ahn JY, Kim S. et.al. Predicting Helicobacter pylori infection from endoscopic features. Korean J Intern Med. 2024;39(3):439\u0026ndash;447. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3904/kjim.2023.300\u003c/span\u003e\u003cspan address=\"10.3904/kjim.2023.300\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2024 Apr 30. PMID: 38715232.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang ZX, Nong B, Liang LX. Differential diagnosis of Helicobacter pylori-associated gastritis with the linked-color imaging score. Dig Liver Dis. 2019;51(12):1665\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.dld.2019.06.024\u003c/span\u003e\u003cspan address=\"10.1016/j.dld.2019.06.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2019 Aug 13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSugano K, Tack J, Kuipers EJ. et.al; faculty members of Kyoto Global Consensus Conference. Kyoto global consensus report on Helicobacter pylori gastritis. Gut. 2015;64(9):1353-67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/gutjnl-2015-309252\u003c/span\u003e\u003cspan address=\"10.1136/gutjnl-2015-309252\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2015 Jul 17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eToyoshima O, Nishizawa T, Koike K. Endoscopic Kyoto classification of Helicobacter pylori infection and gastric cancer risk diagnosis. World J Gastroenterol. 2020;26(5):466\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3748/wjg.v26.i5.466\u003c/span\u003e\u003cspan address=\"10.3748/wjg.v26.i5.466\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSugano K, Tack J et al. Kuipers EJ on behalf of faculty members of Kyoto Global Consensus Conference, Kyoto global consensus report on Helicobacter pylori gastritis Gut 2015;64:1353\u0026ndash;1367.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang K et al. Establishment of a modified Kyoto classification scoring model and its significance in the diagnosis of Helicobacter pylori current infection. Gastrointestinal Endoscopy, Volume 97, Issue 4, 684\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eToyoshima O, Nishizawa T. Kyoto classification of gastritis: Advances and future perspectives in endoscopic diagnosis of gastritis. World J Gastroenterol. 2022;28(43):6078\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3748/wjg.v28.i43.6078\u003c/span\u003e\u003cspan address=\"10.3748/wjg.v28.i43.6078\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSugimoto M, Ban H, Ichikawa H. Efficacy of the Kyoto Classification of Gastritis in Identifying Patients at High Risk for Gastric Cancer. Intern Med. 2017;56(6):579\u0026ndash;86. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2169/internalmedicine.56.7775\u003c/span\u003e\u003cspan address=\"10.2169/internalmedicine.56.7775\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2017 Mar 17. PMID: 28321054; PMCID: PMC5410464.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Mengjiao W, Lianlian X, Daqi, et al. Artificial intelligence\u0026ndash;assisted diagnosis system of Helicobacter pyloriinfection based on deep learning[J]. Chin J Dig Endosc. 2023;40(2):109\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3760/cma.j.cn321463-20211021-00473\u003c/span\u003e\u003cspan address=\"10.3760/cma.j.cn321463-20211021-00473\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Mengjiao W, Lianlian X, Ming, et al. Evaluationof Kyoto gastritis score for Helicobacterpyloriinfection under gastroscopy[J]. Chin J Dig Endosc. 2022;39(9):707\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuach DT, Aoki R, Iga A, et.al. Diagnostic Accuracy of H. pylori Status by Conventional Endoscopy: Time-Trend Change After Eradication and Impact of Endoscopic Image Quality. Front Med. 2022;8:830730. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmed.2021.830730\u003c/span\u003e\u003cspan address=\"10.3389/fmed.2021.830730\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Helicobacter pylori, endoscopy, gastritis classification, diagnostic accuracy, clinical validation","lastPublishedDoi":"10.21203/rs.3.rs-8376050/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8376050/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: While Helicobacter pylori remains a cornerstone pathogen in gastric disease pathogenesis, current diagnostic approaches face practical limitations in routine endoscopic practice. The original Kyoto classification system, though valuable, requires refinement for optimal real-world clinical utility in diverse populations.\u003c/p\u003e\n\u003cp\u003eMethods: We retrospectively analyzed endoscopic findings from 276 patients who underwent both gastroscopy and confirmatory H. pylori testing (urea breath test or histopathological examination) between January 2020 and December 2023. Two experienced endoscopists independently scored gastric mucosal features using this modified Kyoto classification system, with discrepancies resolved through consensus review.\u003c/p\u003e\n\u003cp\u003eResults: This modified scoring system demonstrated moderate correlation with laboratory-confirmed H. pylori status (r = 0.366, p \u0026lt; 0.001). ROC analysis revealed an AUC of 0.74, with optimal diagnostic threshold at 6.0 points yielding 59.8% sensitivity and 74.6% specificity. Feature-specific analysis revealed that enlarged gastric folds (r = 0.265) and spotty redness (r = 0.258) were correlated with H. pylori infection status.\u003c/p\u003e\n\u003cp\u003eInterpretation: Despite inherent limitations in endoscopic assessment, this modified classification system offers practical value for real-time H. pylori evaluation during routine gastroscopy. However, clinicians should recognize its complementary rather than replacement role alongside established diagnostic methods.\u003c/p\u003e","manuscriptTitle":"Endoscopic Assessment of Helicobacter pylori Infection: Validation of a Modified Kyoto Classification System in Real-world Clinical Practice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-22 10:12:54","doi":"10.21203/rs.3.rs-8376050/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-23T11:32:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-22T01:40:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-22T01:40:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2025-12-16T12:02:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b24c014c-7e1a-4bd3-8e66-acecb716464b","owner":[],"postedDate":"December 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-30T05:39:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-22 10:12:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8376050","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8376050","identity":"rs-8376050","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}