{"paper_id":"4e4d0d81-86a1-42ed-a3be-3587842b87be","body_text":"Rapid Urease Test Performance in Advanced Gastric Atrophy: A Diagnostic Accuracy Study Using OLGA Staging | 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 Rapid Urease Test Performance in Advanced Gastric Atrophy: A Diagnostic Accuracy Study Using OLGA Staging Alejandro Pedraza Mayorga, Cristian Olivares Peña, Daniel Briceño Muñoz, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9490483/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The rapid urease test (RUT) is widely used for Helicobacter pylori (H. pylori) diagnosis, but its diagnostic performance in advanced gastric atrophy remains poorly characterized. Aims To evaluate RUT accuracy against histopathology and to determine whether gastric atrophy severity, assessed by the Operative Link on Gastritis Assessment (OLGA) staging system, independently predicts false-negative results. Methods Single-center retrospective cross-sectional diagnostic accuracy study of 744 adult patients undergoing upper gastrointestinal endoscopy with simultaneous RUT (read at 30 minutes) and updated Sydney protocol biopsies. RUT use was at endoscopist discretion (non-consecutive sample). Histopathology served as the reference standard. Sensitivity, specificity, predictive values, likelihood ratios, and Cohen’s kappa were calculated overall and by OLGA risk category. Among histopathology-positive patients, Firth penalized logistic regression identified factors independently associated with false-negative RUT results. Results The prevalence of H. pylori was 28.2% (210/744). Overall, the RUT showed a sensitivity of 89.5% (95% CI: 84.6–93.0), specificity of 91.9% (95% CI: 89.3–94.0), and Cohen’s kappa of 0.79. Among patients with available OLGA classification (742/744), sensitivity declined from 97.1% in OLGA 0 to 64.7% in OLGA III–IV (Fisher’s exact test, p = 0.004). In multivariable analysis, OLGA III–IV was independently associated with false-negative RUT results (adjusted OR 4.41; 95% CI 1.25–14.99; p = 0.022). Conclusions The RUT demonstrates good overall diagnostic accuracy for H. pylori detection. However, sensitivity declines substantially with increasing gastric atrophy severity, and OLGA III–IV independently predicts false-negative results. A negative RUT should not be used as the sole criterion to exclude H. pylori infection in patients with advanced atrophy; complementary or histopathological confirmation is warranted in this population to prevent missed diagnoses with implications for gastric cancer prevention. Gastroenterology & Hepatology Helicobacter pylori rapid urease test gastric atrophy OLGA staging diagnostic accuracy histopathology Figures Figure 1 Figure 2 Figure 3 Introduction Helicobacter pylori (H. pylori) infection affects approximately half of the global population and is the principal etiological agent of chronic gastritis, peptic ulcer disease, and gastric adenocarcinoma ( 1 ). Accurate detection is essential for guiding eradication therapy and stratifying cancer risk, particularly in high-prevalence regions such as Latin America, where infection rates exceed 50% in most population-based series ( 2 , 3 ). Among invasive diagnostic methods, the rapid urease test (RUT) is one of the most frequently used in clinical practice owing to its simplicity, low cost, and rapid turnaround ( 4 , 5 ). The test relies on the hydrolysis of urea by the bacterial urease enzyme, producing ammonia and a consequent pH change detected by a colorimetric indicator. Commercial kits typically recommend a reading time of 30 minutes and report a dichotomous result (positive or negative). Despite its widespread adoption, the diagnostic performance of the RUT is known to vary across clinical settings. Factors such as bacterial load, prior use of proton pump inhibitors (PPIs) or antibiotics, active upper gastrointestinal bleeding, and the biopsy sampling site have been shown to influence test sensitivity and specificity ( 4 , 6 , 7 ). Of particular interest is the potential impact of gastric mucosal atrophy on RUT accuracy. Gastric atrophy results in the loss of specialized glands and may be accompanied by intestinal metaplasia, creating a hostile microenvironment for H. pylori colonization ( 8 ). As bacterial density decreases in atrophic mucosa, urease production may fall below the detection threshold of the RUT, leading to false-negative results ( 9 ). The Operative Link on Gastritis Assessment (OLGA) staging system provides a standardized histopathological framework for grading the severity and topographic extent of gastric atrophy ( 8 ). Patients classified as OLGA stages III–IV are at the highest risk for gastric cancer progression ( 10 , 11 ). Paradoxically, these are the very patients in whom accurate H. pylori detection is most clinically consequential, as eradication may slow or halt preneoplastic progression ( 1 ). To date, few studies have systematically evaluated the relationship between RUT diagnostic accuracy and atrophy severity using a validated histological staging system. Most available data rely on non-standardized endoscopic or histological atrophy descriptors, precluding quantification of this relationship and cross-center comparison. The present study was designed to address this gap: we evaluated the diagnostic performance of the RUT against histopathology as the reference standard in a large endoscopy cohort, stratified results by OLGA stage, and used multivariable analysis to identify factors independently associated with false-negative results. Methods Study design and setting This was a retrospective cross-sectional diagnostic accuracy study conducted at the Department of Gastroenterology, Clínica Dávila, Santiago, Chile, between January 2024 and October 2025. The study was approved by the institutional ethics committee of Clínica Dávila, which waived the requirement for informed consent given the retrospective, observational design and the use of de-identified data. The study was conducted in accordance with the Declaration of Helsinki and reported following the Standards for Reporting of Diagnostic Accuracy (STARD) guidelines ( 12 ); a completed STARD 2015 checklist is provided as Supplementary Material. Study population We retrospectively identified adult patients (≥ 18 years) who underwent elective upper gastrointestinal endoscopy and in whom both the RUT and gastric biopsies following the updated Sydney protocol were performed during the same procedure. In routine care, the decision to perform the RUT was made by the treating endoscopist rather than by a study protocol, so the analytic sample was non-consecutive. Source-population counts used in the study flow diagram were obtained from the institutional endoscopy and pathology registries used for case ascertainment, whereas the analytic dataset contained the final included patients with complete index and reference standard data. The indications for endoscopy included dyspepsia or abdominal pain, gastric cancer screening, gastroesophageal reflux disease, follow-up of known gastric lesions, pre-bariatric surgery evaluation, and other clinical indications. As part of standard institutional protocol, patients were instructed to discontinue proton pump inhibitors at least 7 days prior to the endoscopic procedure; however, this interval was shorter than the 14-day washout recommended in contemporary guidance, and adherence was not individually verified ( 1 ). Patients with missing histopathological H. pylori assessment were excluded from the analysis. Endoscopic procedure and biopsy protocol All endoscopies were performed by 13 experienced endoscopists using high-definition white-light endoscopes. During each procedure, endoscopic findings were recorded, including the presence or absence of erosive, congestive, and atrophic gastropathy and visible intestinal metaplasia. Gastric biopsies were obtained according to the updated Sydney protocol from five standardized sites: two from the antrum, one from the incisura angularis, and two from the corpus. An additional biopsy from the antrum was placed in the RUT kit. Rapid urease test The RUT was performed using HelicotecUT® Plus (Strong Biotech Corporation, Taipei, Taiwan). A single antral biopsy specimen was placed in the test medium immediately after collection. The result was read at 30 minutes as recommended by the manufacturer and recorded as positive (color change to pink/magenta) or negative (no color change). The endoscopist performing the procedure recorded the RUT result, and this result was not disclosed to the pathologist. Histopathological analysis Biopsy specimens were fixed in 10% buffered formalin, embedded in paraffin, sectioned, and stained with hematoxylin-eosin and modified Giemsa stain for enhanced detection of H. pylori organisms. Histopathological assessment was performed by gastrointestinal pathologists blinded to the RUT result. H. pylori status was determined by direct visualization of characteristic curved bacilli on the mucosal surface or within the gastric pits. Gastritis was graded and staged according to the updated Sydney system ( 13 ), and each case was assigned OLGA and OLGIM stages based on the combined atrophy and intestinal metaplasia scores from antral/incisura and corpus biopsies ( 8 , 14 ). OLGA stage 0 was classified as no atrophy, stages I–II as low risk, and stages III–IV as high risk. Statistical analysis Histopathology was used as the reference standard. The 2 × 2 contingency table was constructed by cross-classifying the RUT result (positive/negative) against histopathological H. pylori status (positive/negative). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR−) were calculated with 95% Wilson score confidence intervals. Agreement between the two methods was assessed using Cohen’s kappa coefficient, interpreted as slight (0–0.20), fair (0.21–0.40), moderate (0.41–0.60), substantial (0.61–0.80), or almost perfect (0.81–1.00). Primary subgroup analyses of diagnostic accuracy were performed stratified by OLGA risk category (no atrophy, low risk, high risk) and by endoscopic atrophy (present/absent). To maintain stage-consistent grouping and minimize avoidable missingness, OLGA risk categories were derived from numeric OLGA stage when available and otherwise from the recorded risk category. Descriptive subgroup summaries were also tabulated by sex, age group, and clinical indication. The association between OLGA stage and the false-negative rate among histopathology-positive patients with available numeric OLGA stage was evaluated using Spearman’s rank correlation. Among histopathology-positive patients with available OLGA stage, we fitted multivariable Firth penalized logistic regression models with false-negative RUT result as the dependent variable and age, sex, endoscopic atrophic gastropathy, and either advanced OLGA category (III–IV vs 0–II) or numeric OLGA stage as covariates. Firth penalization was used to reduce small-sample bias given the limited number of false-negative events and the small OLGA III–IV stratum. Differences in sensitivity between the primary subgroup contrasts of interest (OLGA 0 vs OLGA III–IV and endoscopic atrophy absent vs present) were compared using Fisher’s exact test. No imputation was performed; subgroup analyses and regression models used complete-case data for the variables required in each analysis. Because the study used all available cases meeting the inclusion criteria during the study period, no formal sample size calculation was performed. Baseline continuous variables were compared using the independent-samples t test and categorical variables using the chi-square test, as appropriate. All tests were two-sided with a significance level of 0.05. Statistical analyses were performed using R (version 4.2.2). Results Study population During the study period, 5,924 upper gastrointestinal endoscopies were performed, of which 1,933 included biopsies following the updated Sydney protocol. Of these, 902 patients had a RUT performed simultaneously. These upstream screening counts were obtained from the institutional endoscopy/pathology registries used for case ascertainment. After excluding patients with missing histopathological H. pylori assessment, 744 patients (454 female [61.0%]; mean age 56.6 ± 12.0 years) had complete index and reference standard data and were included in the analysis (Fig. 1 ). Clinical indication was coded as other/unspecified in 341 patients (45.8%). Among the categorized indications, the most common were dyspepsia/abdominal pain (22.8%), gastric cancer screening (15.3%), and gastroesophageal reflux (7.3%). Endoscopic atrophic gastropathy was observed in 237 patients (31.9%), erosive gastropathy in 117 (15.7%), and endoscopically visible intestinal metaplasia in 59 (7.9%). Histopathological findings H. pylori was identified on histopathology in 210 of 744 patients, yielding an overall prevalence of 28.2%. Infection was significantly more common in males than in females (32.6% vs 25.3%, p = 0.044) and in younger patients (mean age 52.5 ± 11.4 vs 58.2 ± 11.9 years, p = < 0.001). Table 1: Baseline characteristics of the study population (n = 744). Characteristic Overall H. pylori + H. pylori − p-value n 744 210 534 Age, years (mean ± SD) 56.6 ± 12.0 52.5 ± 11.4 58.2 ± 11.9 < 0.001 Female sex, n (%) 454 (61.0) 115 (54.8) 339 (63.5) 0.044 Endoscopic findings, n (%) Atrophic gastropathy 237 (31.9) 60 (28.6) 177 (33.1) 0.264 Erosive gastropathy 117 (15.7) 21 (10.0) 96 (18.0) 0.011 Intestinal metaplasia 59 (7.9) 20 (9.5) 39 (7.3) 0.391 Congestive gastropathy 64 (8.6) 22 (10.5) 42 (7.9) 0.289 OLGA risk category, n (%) No atrophy (stage 0) 171 (23.0) 34 (16.2) 137 (25.7) Low risk (I–II) 528 (71.0) 158 (75.2) 370 (69.3) High risk (III–IV) 43 (5.8) 17 (8.1) 26 (4.9) Missing/Unavailable 2 (0.3) 1 (0.5) 1 (0.2) Overall diagnostic accuracy of the RUT The RUT yielded 188 true-positive, 491 true-negative, 43 false-positive, and 22 false-negative results (Table 2). Overall sensitivity was 89.5% (95% CI: 84.6–93.0), specificity 91.9% (95% CI: 89.3–94.0), PPV 81.4% (95% CI: 75.9–85.9), and NPV 95.7% (95% CI: 93.6–97.2). The positive likelihood ratio was 11.1 and the negative likelihood ratio was 0.11. The overall agreement between the RUT and histopathology was substantial, with a Cohen’s kappa of 0.79. Table 2: Overall diagnostic performance of the rapid urease test (n = 744). Parameter Value 95% CI True positives 188 False positives 43 False negatives 22 True negatives 491 Sensitivity 89.5% 84.6–93.0 Specificity 91.9% 89.3–94.0 PPV 81.4% 75.9–85.9 NPV 95.7% 93.6–97.2 Positive likelihood ratio 11.1 Negative likelihood ratio 0.11 Youden’s index 0.815 Cohen’s kappa 0.79 Overall accuracy 91.3% Impact of gastric atrophy on RUT performance Among patients with available OLGA classification (742/744), RUT sensitivity decreased progressively with increasing atrophy severity. In patients with no atrophy (OLGA 0), sensitivity was 97.1% (95% CI: 85.1–99.5); in the low-risk group (OLGA I–II), 91.1% (95% CI: 85.7–94.6); and in the high-risk group (OLGA III–IV), 64.7% (95% CI: 41.3–82.7). The difference in sensitivity between OLGA 0 and OLGA III–IV was statistically significant (Fisher’s exact test, p = 0.004). The false-negative rate among histopathology-positive patients correlated positively with OLGA stage (Spearman ρ = 0.21, p = 0.002) (Table 3; Fig. 2 ). Table 3: Diagnostic performance of the rapid urease test stratified by OLGA risk category among patients with available OLGA data (n = 742). Parameter No atrophy (OLGA 0) Low risk (OLGA I–II) High risk (OLGA III–IV) n 171 528 43 H. pylori prevalence 19.9% 29.9% 39.5% True positives 33 144 11 False positives 4 38 1 False negatives 1 14 6 True negatives 133 332 25 Sensitivity, % (95% CI) 97.1% (85.1–99.5) 91.1% (85.7–94.6) 64.7% (41.3–82.7) Specificity, % (95% CI) 97.1% (92.7–98.9) 89.7% (86.2–92.4) 96.2% (81.1–99.3) PPV, % 89.2% 79.1% 91.7% NPV, % 99.3% 96.0% 80.6% False-negative rate, % 2.9% 8.9% 35.3% Consistent with the OLGA findings, patients with endoscopic atrophic gastropathy had lower RUT sensitivity than those without endoscopic atrophy (78.3% vs 94.0%, p = 0.002). Multivariable analysis of false-negative RUT results To assess whether the association between gastric atrophy and false-negative RUT results persisted after covariate adjustment, we performed multivariable Firth penalized logistic regression restricted to 202 histopathology-positive patients with available OLGA and covariate data, among whom 21 had a false-negative RUT result. Firth penalization was used because false-negative events were relatively few and the OLGA III–IV stratum was small. In the primary binary model, OLGA III–IV remained independently associated with higher odds of a false-negative RUT result after adjustment for age, sex, and endoscopic atrophic gastropathy (adjusted OR 4.41; 95% CI 1.25–14.99; p = 0.022). Endoscopic atrophic gastropathy was also independently associated with false-negative results (adjusted OR 3.41; 95% CI 1.31–9.09; p = 0.012) (Supplementary Table S1). In the ordinal trend model, each one-stage increase in OLGA stage was associated with a higher probability of a false-negative result (adjusted OR 2.03; 95% CI 1.13–3.85; p = 0.018) (Fig. 3 ). Other subgroup analyses Exploratory descriptive subgroup summaries are shown in Supplementary Tables S2A-S2C. Sensitivity was numerically similar by sex and broad age group, whereas clinical-indication strata showed wider variation that should be interpreted cautiously given the small number of H. pylori-positive patients in several subgroups. Discussion In this single-center retrospective cross-sectional diagnostic accuracy study of 744 patients undergoing upper gastrointestinal endoscopy at a South American referral center, with a non-consecutive, endoscopist-selected sample, the RUT demonstrated good overall accuracy for H. pylori detection: sensitivity 89.5%, specificity 91.9%, and substantial agreement with histopathology (Cohen’s kappa 0.79). The principal finding, however, is that RUT sensitivity declined systematically with increasing atrophy severity and that advanced OLGA stage remained independently associated with false-negative results after multivariable adjustment, with a dose-response gradient confirmed by the ordinal model. Our overall sensitivity falls within the 85%–95% range consistently reported across prospective and retrospective RUT validation series using histopathology as the reference standard ( 4 , 5 , 7 ). Specificity was somewhat lower than that reported in some classic single-center validation studies, a pattern attributable to real-world practice conditions: a routine 7-day rather than 14-day PPI washout, reliance on a single antral biopsy, and a heterogeneous referral population spanning a wide range of indications ( 1 , 4 , 6 ). Nonetheless, the positive likelihood ratio remained strong, preserving the clinical value of a positive RUT result, and the overall performance metrics place this cohort within the established performance envelope for commercial rapid urease kits. The principal contribution of this study is the demonstration that OLGA staging identifies a clinically important subgroup in whom RUT reliability is substantially compromised. Sensitivity declined from 97.1% in patients without atrophy to 64.7% in those with OLGA III–IV disease (Fisher’s exact test, p = 0.004), and the false-negative rate rose monotonically across OLGA stages (Spearman ρ = 0.21, p = 0.002). Crucially, this gradient persisted after multivariable adjustment: each one-stage increase in OLGA score was associated with an adjusted 2.03-fold increase in the odds of a false-negative result (95% CI 1.13–3.85; p = 0.018). Most earlier studies evaluating this phenomenon relied on non-standardized endoscopic or histological atrophy descriptors; the application of OLGA staging here provides a reproducible, internationally validated framework that permits direct cross-center comparison and prospective replication. The biological rationale is well established. Progressive gland loss and intestinal metaplasia reduce the mucosal surface available for H. pylori colonization, depleting the bacterial reservoir ( 8 , 10 ). As total bacterial burden falls, urease enzymatic output decreases proportionally, and the concentration of ammonia generated by hydrolysis of the RUT substrate may drop below the colorimetric detection threshold of the indicator medium ( 9 , 15 ). This mechanism predicts a continuous, density-dependent decline in RUT sensitivity across the atrophy spectrum, which is precisely the dose-response gradient confirmed by our ordinal model. By quantifying this relationship against a validated staging system, this study moves beyond the binary atrophy-present/absent characterization of prior work and establishes OLGA stage as a clinically actionable predictor of RUT underperformance. A complementary spatial mechanism warrants consideration. In advanced atrophy, particularly when pangastric or corpus-predominant, the topographic distribution of H. pylori shifts: bacterial density in the antrum (the sole site sampled for the index test) may decline disproportionately as specialized antral glands are replaced by atrophic or intestinal-type epithelium, while residual colonization persists in less-affected corpus mucosa. Under this scenario, part of the observed sensitivity decline reflects inadequate antral sampling rather than globally reduced bacterial burden. Distinguishing between these two mechanisms (reduced overall density versus topographic redistribution) would require prospective parallel RUT testing with additional corpus biopsies in OLGA III–IV patients, which was not feasible in the present retrospective dataset. The clinical consequence is identical under either mechanism: a negative antral RUT does not exclude infection in the presence of advanced atrophy. Several strengths support the internal validity of this study. The sample is large for a single-center invasive diagnostic accuracy study with OLGA-staged biopsies. All patients underwent the standardized five-site updated Sydney protocol, and pathologists were blinded to the RUT result, minimizing differential verification bias. The use of numeric OLGA staging, rather than an atrophy-present/absent dichotomy, enables the ordinal model to detect a dose-response gradient and provides a granular, reproducible phenotypic characterization. Firth penalized regression avoids the inflated estimates and convergence failures that ordinary logistic regression would produce in the sparse OLGA III–IV false-negative stratum, improving the reliability of the multivariable estimates. Clinical Implications These findings carry a direct practice-changing implication. The subgroup at highest risk for gastric cancer progression (patients with OLGA III–IV gastritis) is precisely the subgroup in whom a missed H. pylori diagnosis is most consequential: international guidelines endorse H. pylori eradication as a primary preventive strategy in the context of preneoplastic gastric lesions, and failure to identify infection forfeits a potentially cancer-modifying intervention ( 1 , 10 , 11 ). Based on our findings, we propose that a negative RUT should not be accepted as the sole criterion to exclude active H. pylori infection in patients with OLGA III–IV gastritis or endoscopic evidence of advanced atrophy. In such patients, confirmatory testing should be performed before H. pylori negativity is concluded: options include the 13 C-urea breath test, stool antigen test, or systematic histopathological evaluation of all five Sydney-protocol biopsy sites. The independent association of endoscopic atrophic gastropathy with false-negative RUT results in our multivariable model provides an accessible, real-time trigger for this more thorough diagnostic approach at the time of endoscopy. A proposed decision algorithm integrating OLGA stage into the post-endoscopy H. pylori diagnostic pathway is shown in Supplementary Figure S1. Our study was conducted in Santiago, Chile, a high-prevalence setting where H. pylori infects more than half the adult population ( 2 , 3 ), and the observed prevalence of 28.2% is representative of referral gastroenterology centers across Latin America. The sensitivity gradient across OLGA strata reflects the biophysical test-tissue interaction rather than local prevalence, and is therefore expected to generalize to other high-prevalence settings where atrophic gastritis is common, including East and Southeast Asia and Eastern Europe. Predictive values, however, are prevalence-dependent and should be recalibrated before applying these findings to clinical algorithms in low-prevalence settings. Limitations First, the retrospective design restricts causal inference and limits verification of key clinical covariates. The institutional pre-procedural PPI washout interval was 7 days, shorter than the 14-day period endorsed by current guidance ( 1 ), and individual adherence was not confirmed. Residual PPI suppression of bacterial urease activity may have contributed to false-negative RUT results across strata; however, this effect would be expected to affect all OLGA strata proportionally and cannot alone account for the stage-graded sensitivity gradient we observed. Second, the analytic sample was non-consecutive, as RUT use was at endoscopist discretion. This introduces potential spectrum bias: if endoscopists selectively omitted the RUT in patients with the most severe endoscopic atrophy (for instance, because they planned to rely on histopathology alone), the OLGA III–IV stratum may have been enriched for patients with milder macroscopic findings, potentially attenuating the true magnitude of the sensitivity deficit in advanced atrophy. The direction and magnitude of this bias cannot be quantified without individual-level data from the excluded patients. Third, a single antral biopsy was used for the index test. In atrophic and metaplastic stomachs, H. pylori may redistribute toward the corpus; a single antral sample may therefore underrepresent bacterial burden even when infection is present, independently of global bacterial density ( 6 ). Multi-site RUT sampling incorporating corpus biopsies could not be evaluated in this dataset and merits prospective investigation in OLGA III–IV patients. Fourth, histopathology is not a perfect reference standard in the setting of low-density infection. In OLGA III–IV stomachs, where bacterial load is intrinsically reduced, Giemsa staining may fail to detect sparse organisms, generating reference-standard false negatives. Misclassification of such cases as true negatives would lead to underestimation of the true false-negative rate of the RUT in advanced atrophy; our sensitivity estimates for this stratum are therefore likely conservative. Fifth, the OLGA III–IV subgroup comprised relatively few patients, with only four classified as OLGA stage IV, limiting the precision of the high-risk stratum estimates and precluding a stable comparison of OLGA III and IV separately. Conclusions The RUT demonstrates good overall diagnostic accuracy for H. pylori in routine clinical practice. However, sensitivity declines substantially and in a dose-dependent manner with increasing gastric atrophy severity, and OLGA III–IV independently predicts false-negative results. A negative RUT should not be accepted as sufficient evidence to exclude H. pylori infection in patients with advanced gastric atrophy. Incorporating OLGA staging into the endoscopic workflow identifies patients who require confirmatory or complementary testing, a step with direct consequences for gastric cancer prevention in the highest-risk population. Abbreviations RUT, rapid urease test; OLGA, Operative Link on Gastritis Assessment; OLGIM, Operative Link on Gastric Intestinal Metaplasia Assessment; PPV, positive predictive value; NPV, negative predictive value; LR, likelihood ratio; CI, confidence interval; PPI, proton pump inhibitor Declarations Competing interests: All authors declare no competing interests relevant to this manuscript. Ethics approval: This study was a retrospective analysis of anonymized clinical data collected during routine clinical care. It was approved by the Institutional Ethics Committee of Clínica Dávila and was conducted in accordance with the Declaration of Helsinki. The requirement for individual informed consent was waived by the ethics committee given the retrospective, observational design and use of de-identified data. Consent to participate: Waived by the Institutional Ethics Committee of Clínica Dávila (see Ethics approval above). Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author contributions: Alejandro Pedraza Mayorga: Conceptualization, methodology, formal analysis, investigation, data curation, writing – original draft, writing – review and editing, project administration. Cristian Olivares Peña: Investigation, data curation, writing – review and editing. Daniel Briceño Muñoz: Data curation, formal analysis, writing – review and editing. Rodrigo Irarrázaval del Campo: Investigation, data curation, writing – review and editing. All authors have read and approved the final version of the manuscript. Acknowledgments: The authors thank the endoscopy and pathology staff of Clínica Dávila for their contributions to clinical care and data collection. Data availability: The data that support the findings of this study are available from the corresponding author upon reasonable request. 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BMJ 351:h5527. 10.1136/bmj.h5527 Dixon MF, Genta RM, Yardley JH, Correa P (1996) Classification and grading of gastritis: The updated Sydney system. Am J Surg Pathol 20(10):1161–1181. 10.1097/00000478-199610000-00001 Capelle LG, de Vries AC, Haringsma J, Ter Borg F, de Vries RA, Bruno MJ et al (2010) The staging of gastritis with the OLGA system by using intestinal metaplasia as an accurate alternative for atrophic gastritis. Gastrointest Endosc 71(7):1150–1158. 10.1016/j.gie.2009.12.029 Kato T, Yagi N, Kamada T, Shimbo T, Watanabe H, Ida K (2013) Diagnosis of Helicobacter pylori infection in gastric mucosa by endoscopic features: A multicenter prospective study. Dig Endosc 25(5):508–518. 10.1111/den.12031 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-9490483\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":640595850,\"identity\":\"96ead4a0-3979-4c81-b3f3-262d5bca231f\",\"order_by\":0,\"name\":\"Alejandro Pedraza Mayorga\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"https://orcid.org/0009-0001-4593-2931\",\"institution\":\"Department of Gastroenterology, Clínica Dávila, Santiago, Chile\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Alejandro\",\"middleName\":\"Pedraza\",\"lastName\":\"Mayorga\",\"suffix\":\"\"},{\"id\":640595851,\"identity\":\"dcf780fe-d603-4fd0-8b07-2b173cda76d9\",\"order_by\":1,\"name\":\"Cristian Olivares Peña\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Department of Gastroenterology, Clínica Dávila, Santiago, Chile\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Cristian\",\"middleName\":\"Olivares\",\"lastName\":\"Peña\",\"suffix\":\"\"},{\"id\":640595852,\"identity\":\"db8f48e4-cdf2-41a0-ade1-1db8aee48bd3\",\"order_by\":2,\"name\":\"Daniel Briceño Muñoz\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Department of Gastroenterology, Clínica Dávila, Santiago, Chile\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Daniel\",\"middleName\":\"Briceño\",\"lastName\":\"Muñoz\",\"suffix\":\"\"},{\"id\":640595853,\"identity\":\"da875ed8-7ebc-4539-accc-64ceeea10ba9\",\"order_by\":3,\"name\":\"Rodrigo Irarrázaval del Campo,\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Department of Gastroenterology, Clínica Dávila, Santiago, Chile\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"\",\"middleName\":\"Rodrigo Irarrázaval del\",\"lastName\":\"Campo\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-04-22 04:03:15\",\"currentVersionCode\":1,\"declarations\":{\"humanSubjects\":true,\"vertebrateSubjects\":true,\"conflictsOfInterestStatement\":false,\"humanSubjectEthicalGuidelines\":true,\"humanSubjectConsent\":true,\"humanSubjectClinicalTrial\":false,\"humanSubjectCaseReport\":false,\"vertebrateSubjectEthicalGuidelines\":true},\"doi\":\"10.21203/rs.3.rs-9490483/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9490483/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":109759938,\"identity\":\"8a95f156-17f5-4f79-8d93-da217d116942\",\"added_by\":\"auto\",\"created_at\":\"2026-05-22 07:27:57\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":98299,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eFlow diagram of patient selection and final analytic cohort\\u003c/em\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9490483/v1/54f9120ddd147108c1574323.png\"},{\"id\":109435537,\"identity\":\"47054df3-16b1-4b60-a68a-ec79c8e0c024\",\"added_by\":\"auto\",\"created_at\":\"2026-05-18 06:06:19\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":31028,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eFalse-negative rate of the rapid urease test among H. pylori-positive patients stratified by OLGA stage. Numbers above bars indicate false-negative/total H. pylori-positive cases\\u003c/em\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9490483/v1/b5be36c5a418c367fcfd6a97.png\"},{\"id\":109759372,\"identity\":\"3e3aded6-ed11-4cb7-b0a5-cfc2dc9b5fd8\",\"added_by\":\"auto\",\"created_at\":\"2026-05-22 07:26:49\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":36880,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cem\\u003eAdjusted predicted probability of a false-negative rapid urease test according to OLGA stage, derived from the ordinal Firth model at the median age, female sex, and absence of endoscopic atrophic gastropathy. Error bars represent 95% confidence intervals.\\u003c/em\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9490483/v1/49cf496b5ddc02c46d89f668.png\"},{\"id\":109763818,\"identity\":\"7b53333c-9cf8-4bfc-985b-3070ab45c2ec\",\"added_by\":\"auto\",\"created_at\":\"2026-05-22 07:35:56\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":447469,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9490483/v1/589f96ca-2751-4210-a2f7-cfbfa5cd2cce.pdf\"},{\"id\":109435533,\"identity\":\"080ea044-9421-4fcd-97fc-99926b128874\",\"added_by\":\"auto\",\"created_at\":\"2026-05-18 06:06:18\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":190885,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"supportinginformation.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9490483/v1/5df695d3ca7ba07ded3b826e.docx\"}],\"financialInterests\":\"The authors declare no competing interests.\",\"formattedTitle\":\"\\u003cp\\u003eRapid Urease Test Performance in Advanced Gastric Atrophy: A Diagnostic Accuracy Study Using OLGA Staging\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eHelicobacter pylori (H. pylori) infection affects approximately half of the global population and is the principal etiological agent of chronic gastritis, peptic ulcer disease, and gastric adenocarcinoma (\\u003cspan class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e). Accurate detection is essential for guiding eradication therapy and stratifying cancer risk, particularly in high-prevalence regions such as Latin America, where infection rates exceed 50% in most population-based series (\\u003cspan class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eAmong invasive diagnostic methods, the rapid urease test (RUT) is one of the most frequently used in clinical practice owing to its simplicity, low cost, and rapid turnaround (\\u003cspan class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e). The test relies on the hydrolysis of urea by the bacterial urease enzyme, producing ammonia and a consequent pH change detected by a colorimetric indicator. Commercial kits typically recommend a reading time of 30 minutes and report a dichotomous result (positive or negative).\\u003c/p\\u003e \\u003cp\\u003eDespite its widespread adoption, the diagnostic performance of the RUT is known to vary across clinical settings. Factors such as bacterial load, prior use of proton pump inhibitors (PPIs) or antibiotics, active upper gastrointestinal bleeding, and the biopsy sampling site have been shown to influence test sensitivity and specificity (\\u003cspan class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e). Of particular interest is the potential impact of gastric mucosal atrophy on RUT accuracy. Gastric atrophy results in the loss of specialized glands and may be accompanied by intestinal metaplasia, creating a hostile microenvironment for H. pylori colonization (\\u003cspan class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e). As bacterial density decreases in atrophic mucosa, urease production may fall below the detection threshold of the RUT, leading to false-negative results (\\u003cspan class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe Operative Link on Gastritis Assessment (OLGA) staging system provides a standardized histopathological framework for grading the severity and topographic extent of gastric atrophy (\\u003cspan class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e). Patients classified as OLGA stages III–IV are at the highest risk for gastric cancer progression (\\u003cspan class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e). Paradoxically, these are the very patients in whom accurate H. pylori detection is most clinically consequential, as eradication may slow or halt preneoplastic progression (\\u003cspan class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eTo date, few studies have systematically evaluated the relationship between RUT diagnostic accuracy and atrophy severity using a validated histological staging system. Most available data rely on non-standardized endoscopic or histological atrophy descriptors, precluding quantification of this relationship and cross-center comparison. The present study was designed to address this gap: we evaluated the diagnostic performance of the RUT against histopathology as the reference standard in a large endoscopy cohort, stratified results by OLGA stage, and used multivariable analysis to identify factors independently associated with false-negative results.\\u003c/p\\u003e \"},{\"header\":\"Methods\",\"content\":\"\\u003cp\\u003eStudy design and setting\\u003c/p\\u003e\\u003cp\\u003eThis was a retrospective cross-sectional diagnostic accuracy study conducted at the Department of Gastroenterology, Clínica Dávila, Santiago, Chile, between January 2024 and October 2025. The study was approved by the institutional ethics committee of Clínica Dávila, which waived the requirement for informed consent given the retrospective, observational design and the use of de-identified data. The study was conducted in accordance with the Declaration of Helsinki and reported following the Standards for Reporting of Diagnostic Accuracy (STARD) guidelines (\\u003cspan class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e); a completed STARD 2015 checklist is provided as Supplementary Material.\\u003c/p\\u003e\\u003cp\\u003eStudy population\\u003c/p\\u003e\\u003cp\\u003eWe retrospectively identified adult patients (≥ 18 years) who underwent elective upper gastrointestinal endoscopy and in whom both the RUT and gastric biopsies following the updated Sydney protocol were performed during the same procedure. In routine care, the decision to perform the RUT was made by the treating endoscopist rather than by a study protocol, so the analytic sample was non-consecutive. Source-population counts used in the study flow diagram were obtained from the institutional endoscopy and pathology registries used for case ascertainment, whereas the analytic dataset contained the final included patients with complete index and reference standard data. The indications for endoscopy included dyspepsia or abdominal pain, gastric cancer screening, gastroesophageal reflux disease, follow-up of known gastric lesions, pre-bariatric surgery evaluation, and other clinical indications. As part of standard institutional protocol, patients were instructed to discontinue proton pump inhibitors at least 7 days prior to the endoscopic procedure; however, this interval was shorter than the 14-day washout recommended in contemporary guidance, and adherence was not individually verified (\\u003cspan class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e). Patients with missing histopathological H. pylori assessment were excluded from the analysis.\\u003c/p\\u003e\\u003cp\\u003eEndoscopic procedure and biopsy protocol\\u003c/p\\u003e\\u003cp\\u003eAll endoscopies were performed by 13 experienced endoscopists using high-definition white-light endoscopes. During each procedure, endoscopic findings were recorded, including the presence or absence of erosive, congestive, and atrophic gastropathy and visible intestinal metaplasia. Gastric biopsies were obtained according to the updated Sydney protocol from five standardized sites: two from the antrum, one from the incisura angularis, and two from the corpus. An additional biopsy from the antrum was placed in the RUT kit.\\u003c/p\\u003e\\u003cp\\u003eRapid urease test\\u003c/p\\u003e\\u003cp\\u003eThe RUT was performed using HelicotecUT® Plus (Strong Biotech Corporation, Taipei, Taiwan). A single antral biopsy specimen was placed in the test medium immediately after collection. The result was read at 30 minutes as recommended by the manufacturer and recorded as positive (color change to pink/magenta) or negative (no color change). The endoscopist performing the procedure recorded the RUT result, and this result was not disclosed to the pathologist.\\u003c/p\\u003e\\u003cp\\u003eHistopathological analysis\\u003c/p\\u003e\\u003cp\\u003eBiopsy specimens were fixed in 10% buffered formalin, embedded in paraffin, sectioned, and stained with hematoxylin-eosin and modified Giemsa stain for enhanced detection of H. pylori organisms. Histopathological assessment was performed by gastrointestinal pathologists blinded to the RUT result. H. pylori status was determined by direct visualization of characteristic curved bacilli on the mucosal surface or within the gastric pits. Gastritis was graded and staged according to the updated Sydney system (\\u003cspan class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e), and each case was assigned OLGA and OLGIM stages based on the combined atrophy and intestinal metaplasia scores from antral/incisura and corpus biopsies (\\u003cspan class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e). OLGA stage 0 was classified as no atrophy, stages I–II as low risk, and stages III–IV as high risk.\\u003c/p\\u003e\\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e\\u003cp\\u003eHistopathology was used as the reference standard. The 2 × 2 contingency table was constructed by cross-classifying the RUT result (positive/negative) against histopathological H. pylori status (positive/negative). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR−) were calculated with 95% Wilson score confidence intervals. Agreement between the two methods was assessed using Cohen’s kappa coefficient, interpreted as slight (0–0.20), fair (0.21–0.40), moderate (0.41–0.60), substantial (0.61–0.80), or almost perfect (0.81–1.00).\\u003c/p\\u003e\\u003cp\\u003ePrimary subgroup analyses of diagnostic accuracy were performed stratified by OLGA risk category (no atrophy, low risk, high risk) and by endoscopic atrophy (present/absent). To maintain stage-consistent grouping and minimize avoidable missingness, OLGA risk categories were derived from numeric OLGA stage when available and otherwise from the recorded risk category. Descriptive subgroup summaries were also tabulated by sex, age group, and clinical indication. The association between OLGA stage and the false-negative rate among histopathology-positive patients with available numeric OLGA stage was evaluated using Spearman’s rank correlation. Among histopathology-positive patients with available OLGA stage, we fitted multivariable Firth penalized logistic regression models with false-negative RUT result as the dependent variable and age, sex, endoscopic atrophic gastropathy, and either advanced OLGA category (III–IV vs 0–II) or numeric OLGA stage as covariates. Firth penalization was used to reduce small-sample bias given the limited number of false-negative events and the small OLGA III–IV stratum. Differences in sensitivity between the primary subgroup contrasts of interest (OLGA 0 vs OLGA III–IV and endoscopic atrophy absent vs present) were compared using Fisher’s exact test. No imputation was performed; subgroup analyses and regression models used complete-case data for the variables required in each analysis. Because the study used all available cases meeting the inclusion criteria during the study period, no formal sample size calculation was performed. Baseline continuous variables were compared using the independent-samples t test and categorical variables using the chi-square test, as appropriate. All tests were two-sided with a significance level of 0.05. Statistical analyses were performed using R (version 4.2.2).\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eStudy population\\u003c/p\\u003e \\u003cp\\u003eDuring the study period, 5,924 upper gastrointestinal endoscopies were performed, of which 1,933 included biopsies following the updated Sydney protocol. Of these, 902 patients had a RUT performed simultaneously. These upstream screening counts were obtained from the institutional endoscopy/pathology registries used for case ascertainment. After excluding patients with missing histopathological H. pylori assessment, 744 patients (454 female [61.0%]; mean age 56.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;12.0 years) had complete index and reference standard data and were included in the analysis (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eClinical indication was coded as other/unspecified in 341 patients (45.8%). Among the categorized indications, the most common were dyspepsia/abdominal pain (22.8%), gastric cancer screening (15.3%), and gastroesophageal reflux (7.3%). Endoscopic atrophic gastropathy was observed in 237 patients (31.9%), erosive gastropathy in 117 (15.7%), and endoscopically visible intestinal metaplasia in 59 (7.9%).\\u003c/p\\u003e \\u003cp\\u003eHistopathological findings\\u003c/p\\u003e \\u003cp\\u003eH. pylori was identified on histopathology in 210 of 744 patients, yielding an overall prevalence of 28.2%. Infection was significantly more common in males than in females (32.6% vs 25.3%, p\\u0026thinsp;=\\u0026thinsp;0.044) and in younger patients (mean age 52.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.4 vs 58.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.9 years, p\\u0026thinsp;=\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"No\\\" id=\\\"Taba\\\" border=\\\"1\\\"\\u003e \\u003ccolgroup cols=\\\"1\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"char\\\" char=\\\".\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTable\\u0026nbsp;1: Baseline characteristics of the study population (n\\u0026thinsp;=\\u0026thinsp;744).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"No\\\" id=\\\"Tabb\\\" border=\\\"1\\\"\\u003e \\u003ccolgroup cols=\\\"5\\\"\\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 \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCharacteristic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eOverall\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eH. pylori +\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eH. pylori \\u0026minus;\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep-value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003en\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e744\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e210\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e534\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge, years (mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e56.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;12.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e52.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e58.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFemale sex, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e454 (61.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e115 (54.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e339 (63.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.044\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEndoscopic findings, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAtrophic gastropathy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e237 (31.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e60 (28.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e177 (33.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.264\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eErosive gastropathy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e117 (15.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e21 (10.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e96 (18.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.011\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIntestinal metaplasia\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e59 (7.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e20 (9.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e39 (7.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.391\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCongestive gastropathy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e64 (8.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22 (10.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e42 (7.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.289\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOLGA risk category, n (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNo atrophy (stage 0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e171 (23.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e34 (16.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e137 (25.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLow risk (I\\u0026ndash;II)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e528 (71.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e158 (75.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e370 (69.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHigh risk (III\\u0026ndash;IV)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e43 (5.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e17 (8.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e26 (4.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMissing/Unavailable\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (0.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1 (0.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1 (0.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003ch2\\u003eOverall diagnostic accuracy of the RUT\\u003c/h2\\u003e\\u003cp\\u003eThe RUT yielded 188 true-positive, 491 true-negative, 43 false-positive, and 22 false-negative results (Table\\u0026nbsp;2). Overall sensitivity was 89.5% (95% CI: 84.6\\u0026ndash;93.0), specificity 91.9% (95% CI: 89.3\\u0026ndash;94.0), PPV 81.4% (95% CI: 75.9\\u0026ndash;85.9), and NPV 95.7% (95% CI: 93.6\\u0026ndash;97.2). The positive likelihood ratio was 11.1 and the negative likelihood ratio was 0.11. The overall agreement between the RUT and histopathology was substantial, with a Cohen\\u0026rsquo;s kappa of 0.79.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"No\\\" id=\\\"Tabc\\\" border=\\\"1\\\"\\u003e \\u003ccolgroup cols=\\\"1\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"char\\\" char=\\\".\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTable\\u0026nbsp;2: Overall diagnostic performance of the rapid urease test (n\\u0026thinsp;=\\u0026thinsp;744).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"No\\\" id=\\\"Tabd\\\" border=\\\"1\\\"\\u003e \\u003ccolgroup cols=\\\"3\\\"\\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 \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eParameter\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eValue\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e95% CI\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTrue positives\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e188\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFalse positives\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e43\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFalse negatives\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTrue negatives\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e491\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSensitivity\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e89.5%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e84.6\\u0026ndash;93.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSpecificity\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e91.9%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e89.3\\u0026ndash;94.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePPV\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e81.4%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e75.9\\u0026ndash;85.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNPV\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e95.7%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e93.6\\u0026ndash;97.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePositive likelihood ratio\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e11.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNegative likelihood ratio\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eYouden\\u0026rsquo;s index\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.815\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCohen\\u0026rsquo;s kappa\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOverall accuracy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e91.3%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e\\u003ch2\\u003eImpact of gastric atrophy on RUT performance\\u003c/h2\\u003e \\u003cp\\u003eAmong patients with available OLGA classification (742/744), RUT sensitivity decreased progressively with increasing atrophy severity. In patients with no atrophy (OLGA 0), sensitivity was 97.1% (95% CI: 85.1\\u0026ndash;99.5); in the low-risk group (OLGA I\\u0026ndash;II), 91.1% (95% CI: 85.7\\u0026ndash;94.6); and in the high-risk group (OLGA III\\u0026ndash;IV), 64.7% (95% CI: 41.3\\u0026ndash;82.7). The difference in sensitivity between OLGA 0 and OLGA III\\u0026ndash;IV was statistically significant (Fisher\\u0026rsquo;s exact test, p\\u0026thinsp;=\\u0026thinsp;0.004). The false-negative rate among histopathology-positive patients correlated positively with OLGA stage (Spearman ρ\\u0026thinsp;=\\u0026thinsp;0.21, p\\u0026thinsp;=\\u0026thinsp;0.002) (Table\\u0026nbsp;3; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eTable\\u0026nbsp;3: Diagnostic performance of the rapid urease test stratified by OLGA risk category among patients with available OLGA data (n = 742).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"100%\\\"\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eParameter\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003eNo atrophy (OLGA 0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003eLow risk (OLGA I\\u0026ndash;II)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"bottom\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003eHigh risk (OLGA III\\u0026ndash;IV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003en\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e171\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e528\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e43\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eH. pylori prevalence\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e19.9%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e29.9%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e39.5%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eTrue positives\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e144\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eFalse positives\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eFalse negatives\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eTrue negatives\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e133\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e332\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eSensitivity, % (95% CI)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e97.1% (85.1\\u0026ndash;99.5)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e91.1% (85.7\\u0026ndash;94.6)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e64.7% (41.3\\u0026ndash;82.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eSpecificity, % (95% CI)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e97.1% (92.7\\u0026ndash;98.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e89.7% (86.2\\u0026ndash;92.4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e96.2% (81.1\\u0026ndash;99.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003ePPV, %\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e89.2%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e79.1%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e91.7%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eNPV, %\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e99.3%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e96.0%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e80.6%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 138px;\\\"\\u003e\\n \\u003cp\\u003eFalse-negative rate, %\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 120px;\\\"\\u003e\\n \\u003cp\\u003e2.9%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 126px;\\\"\\u003e\\n \\u003cp\\u003e8.9%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 143px;\\\"\\u003e\\n \\u003cp\\u003e35.3%\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\u003cp\\u003eConsistent with the OLGA findings, patients with endoscopic atrophic gastropathy had lower RUT sensitivity than those without endoscopic atrophy (78.3% vs 94.0%, p\\u0026thinsp;=\\u0026thinsp;0.002).\\u003c/p\\u003e \\u003cp\\u003eMultivariable analysis of false-negative RUT results\\u003c/p\\u003e \\u003cp\\u003eTo assess whether the association between gastric atrophy and false-negative RUT results persisted after covariate adjustment, we performed multivariable Firth penalized logistic regression restricted to 202 histopathology-positive patients with available OLGA and covariate data, among whom 21 had a false-negative RUT result. Firth penalization was used because false-negative events were relatively few and the OLGA III\\u0026ndash;IV stratum was small. In the primary binary model, OLGA III\\u0026ndash;IV remained independently associated with higher odds of a false-negative RUT result after adjustment for age, sex, and endoscopic atrophic gastropathy (adjusted OR 4.41; 95% CI 1.25\\u0026ndash;14.99; p\\u0026thinsp;=\\u0026thinsp;0.022). Endoscopic atrophic gastropathy was also independently associated with false-negative results (adjusted OR 3.41; 95% CI 1.31\\u0026ndash;9.09; p\\u0026thinsp;=\\u0026thinsp;0.012) (Supplementary Table S1). In the ordinal trend model, each one-stage increase in OLGA stage was associated with a higher probability of a false-negative result (adjusted OR 2.03; 95% CI 1.13\\u0026ndash;3.85; p\\u0026thinsp;=\\u0026thinsp;0.018) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eOther subgroup analyses\\u003c/p\\u003e \\u003cp\\u003eExploratory descriptive subgroup summaries are shown in Supplementary Tables S2A-S2C. Sensitivity was numerically similar by sex and broad age group, whereas clinical-indication strata showed wider variation that should be interpreted cautiously given the small number of H. pylori-positive patients in several subgroups.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003e In this single-center retrospective cross-sectional diagnostic accuracy study of 744 patients undergoing upper gastrointestinal endoscopy at a South American referral center, with a non-consecutive, endoscopist-selected sample, the RUT demonstrated good overall accuracy for H. pylori detection: sensitivity 89.5%, specificity 91.9%, and substantial agreement with histopathology (Cohen\\u0026rsquo;s kappa 0.79). The principal finding, however, is that RUT sensitivity declined systematically with increasing atrophy severity and that advanced OLGA stage remained independently associated with false-negative results after multivariable adjustment, with a dose-response gradient confirmed by the ordinal model.\\u003c/p\\u003e \\u003cp\\u003eOur overall sensitivity falls within the 85%\\u0026ndash;95% range consistently reported across prospective and retrospective RUT validation series using histopathology as the reference standard (\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e). Specificity was somewhat lower than that reported in some classic single-center validation studies, a pattern attributable to real-world practice conditions: a routine 7-day rather than 14-day PPI washout, reliance on a single antral biopsy, and a heterogeneous referral population spanning a wide range of indications (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e). Nonetheless, the positive likelihood ratio remained strong, preserving the clinical value of a positive RUT result, and the overall performance metrics place this cohort within the established performance envelope for commercial rapid urease kits.\\u003c/p\\u003e \\u003cp\\u003eThe principal contribution of this study is the demonstration that OLGA staging identifies a clinically important subgroup in whom RUT reliability is substantially compromised. Sensitivity declined from 97.1% in patients without atrophy to 64.7% in those with OLGA III\\u0026ndash;IV disease (Fisher\\u0026rsquo;s exact test, p\\u0026thinsp;=\\u0026thinsp;0.004), and the false-negative rate rose monotonically across OLGA stages (Spearman ρ\\u0026thinsp;=\\u0026thinsp;0.21, p\\u0026thinsp;=\\u0026thinsp;0.002). Crucially, this gradient persisted after multivariable adjustment: each one-stage increase in OLGA score was associated with an adjusted 2.03-fold increase in the odds of a false-negative result (95% CI 1.13\\u0026ndash;3.85; p\\u0026thinsp;=\\u0026thinsp;0.018). Most earlier studies evaluating this phenomenon relied on non-standardized endoscopic or histological atrophy descriptors; the application of OLGA staging here provides a reproducible, internationally validated framework that permits direct cross-center comparison and prospective replication.\\u003c/p\\u003e \\u003cp\\u003eThe biological rationale is well established. Progressive gland loss and intestinal metaplasia reduce the mucosal surface available for H. pylori colonization, depleting the bacterial reservoir (\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e). As total bacterial burden falls, urease enzymatic output decreases proportionally, and the concentration of ammonia generated by hydrolysis of the RUT substrate may drop below the colorimetric detection threshold of the indicator medium (\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e). This mechanism predicts a continuous, density-dependent decline in RUT sensitivity across the atrophy spectrum, which is precisely the dose-response gradient confirmed by our ordinal model. By quantifying this relationship against a validated staging system, this study moves beyond the binary atrophy-present/absent characterization of prior work and establishes OLGA stage as a clinically actionable predictor of RUT underperformance.\\u003c/p\\u003e \\u003cp\\u003eA complementary spatial mechanism warrants consideration. In advanced atrophy, particularly when pangastric or corpus-predominant, the topographic distribution of H. pylori shifts: bacterial density in the antrum (the sole site sampled for the index test) may decline disproportionately as specialized antral glands are replaced by atrophic or intestinal-type epithelium, while residual colonization persists in less-affected corpus mucosa. Under this scenario, part of the observed sensitivity decline reflects inadequate antral sampling rather than globally reduced bacterial burden. Distinguishing between these two mechanisms (reduced overall density versus topographic redistribution) would require prospective parallel RUT testing with additional corpus biopsies in OLGA III\\u0026ndash;IV patients, which was not feasible in the present retrospective dataset. The clinical consequence is identical under either mechanism: a negative antral RUT does not exclude infection in the presence of advanced atrophy.\\u003c/p\\u003e \\u003cp\\u003eSeveral strengths support the internal validity of this study. The sample is large for a single-center invasive diagnostic accuracy study with OLGA-staged biopsies. All patients underwent the standardized five-site updated Sydney protocol, and pathologists were blinded to the RUT result, minimizing differential verification bias. The use of numeric OLGA staging, rather than an atrophy-present/absent dichotomy, enables the ordinal model to detect a dose-response gradient and provides a granular, reproducible phenotypic characterization. Firth penalized regression avoids the inflated estimates and convergence failures that ordinary logistic regression would produce in the sparse OLGA III\\u0026ndash;IV false-negative stratum, improving the reliability of the multivariable estimates.\\u003c/p\\u003e \\u003cp\\u003eClinical Implications\\u003c/p\\u003e \\u003cp\\u003eThese findings carry a direct practice-changing implication. The subgroup at highest risk for gastric cancer progression (patients with OLGA III\\u0026ndash;IV gastritis) is precisely the subgroup in whom a missed H. pylori diagnosis is most consequential: international guidelines endorse H. pylori eradication as a primary preventive strategy in the context of preneoplastic gastric lesions, and failure to identify infection forfeits a potentially cancer-modifying intervention (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e). Based on our findings, we propose that a negative RUT should not be accepted as the sole criterion to exclude active H. pylori infection in patients with OLGA III\\u0026ndash;IV gastritis or endoscopic evidence of advanced atrophy. In such patients, confirmatory testing should be performed before H. pylori negativity is concluded: options include the \\u003csup\\u003e13\\u003c/sup\\u003eC-urea breath test, stool antigen test, or systematic histopathological evaluation of all five Sydney-protocol biopsy sites. The independent association of endoscopic atrophic gastropathy with false-negative RUT results in our multivariable model provides an accessible, real-time trigger for this more thorough diagnostic approach at the time of endoscopy. A proposed decision algorithm integrating OLGA stage into the post-endoscopy H. pylori diagnostic pathway is shown in Supplementary Figure S1.\\u003c/p\\u003e \\u003cp\\u003eOur study was conducted in Santiago, Chile, a high-prevalence setting where H. pylori infects more than half the adult population (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e), and the observed prevalence of 28.2% is representative of referral gastroenterology centers across Latin America. The sensitivity gradient across OLGA strata reflects the biophysical test-tissue interaction rather than local prevalence, and is therefore expected to generalize to other high-prevalence settings where atrophic gastritis is common, including East and Southeast Asia and Eastern Europe. Predictive values, however, are prevalence-dependent and should be recalibrated before applying these findings to clinical algorithms in low-prevalence settings.\\u003c/p\\u003e \\u003cp\\u003eLimitations\\u003c/p\\u003e \\u003cp\\u003eFirst, the retrospective design restricts causal inference and limits verification of key clinical covariates. The institutional pre-procedural PPI washout interval was 7 days, shorter than the 14-day period endorsed by current guidance (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e), and individual adherence was not confirmed. Residual PPI suppression of bacterial urease activity may have contributed to false-negative RUT results across strata; however, this effect would be expected to affect all OLGA strata proportionally and cannot alone account for the stage-graded sensitivity gradient we observed. Second, the analytic sample was non-consecutive, as RUT use was at endoscopist discretion. This introduces potential spectrum bias: if endoscopists selectively omitted the RUT in patients with the most severe endoscopic atrophy (for instance, because they planned to rely on histopathology alone), the OLGA III\\u0026ndash;IV stratum may have been enriched for patients with milder macroscopic findings, potentially attenuating the true magnitude of the sensitivity deficit in advanced atrophy. The direction and magnitude of this bias cannot be quantified without individual-level data from the excluded patients. Third, a single antral biopsy was used for the index test. In atrophic and metaplastic stomachs, H. pylori may redistribute toward the corpus; a single antral sample may therefore underrepresent bacterial burden even when infection is present, independently of global bacterial density (\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e). Multi-site RUT sampling incorporating corpus biopsies could not be evaluated in this dataset and merits prospective investigation in OLGA III\\u0026ndash;IV patients. Fourth, histopathology is not a perfect reference standard in the setting of low-density infection. In OLGA III\\u0026ndash;IV stomachs, where bacterial load is intrinsically reduced, Giemsa staining may fail to detect sparse organisms, generating reference-standard false negatives. Misclassification of such cases as true negatives would lead to underestimation of the true false-negative rate of the RUT in advanced atrophy; our sensitivity estimates for this stratum are therefore likely conservative. Fifth, the OLGA III\\u0026ndash;IV subgroup comprised relatively few patients, with only four classified as OLGA stage IV, limiting the precision of the high-risk stratum estimates and precluding a stable comparison of OLGA III and IV separately.\\u003c/p\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eThe RUT demonstrates good overall diagnostic accuracy for H. pylori in routine clinical practice. However, sensitivity declines substantially and in a dose-dependent manner with increasing gastric atrophy severity, and OLGA III\\u0026ndash;IV independently predicts false-negative results. A negative RUT should not be accepted as sufficient evidence to exclude H. pylori infection in patients with advanced gastric atrophy. Incorporating OLGA staging into the endoscopic workflow identifies patients who require confirmatory or complementary testing, a step with direct consequences for gastric cancer prevention in the highest-risk population.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003eRUT, rapid urease test; OLGA, Operative Link on Gastritis Assessment; OLGIM, Operative Link on Gastric Intestinal Metaplasia Assessment; PPV, positive predictive value; NPV, negative predictive value; LR, likelihood ratio; CI, confidence interval; PPI, proton pump inhibitor\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e \\u003ch2\\u003eCompeting interests:\\u003c/h2\\u003e \\u003cp\\u003eAll authors declare no competing interests relevant to this manuscript.\\u003c/p\\u003e \\u003c/p\\u003e\\u003cp\\u003e \\u003ch2\\u003eEthics approval:\\u003c/h2\\u003e \\u003cp\\u003eThis study was a retrospective analysis of anonymized clinical data collected during routine clinical care. It was approved by the Institutional Ethics Committee of Cl\\u0026iacute;nica D\\u0026aacute;vila and was conducted in accordance with the Declaration of Helsinki. The requirement for individual informed consent was waived by the ethics committee given the retrospective, observational design and use of de-identified data.\\u003c/p\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cstrong\\u003eConsent to participate:\\u003c/strong\\u003e \\u003cp\\u003e Waived by the Institutional Ethics Committee of Cl\\u0026iacute;nica D\\u0026aacute;vila (see Ethics approval above).\\u003c/p\\u003e \\u003c/p\\u003e\\u003ch2\\u003eFunding:\\u003c/h2\\u003e \\u003cp\\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\\u003c/p\\u003e\\u003ch2\\u003eAuthor contributions:\\u003c/h2\\u003e \\u003cp\\u003eAlejandro Pedraza Mayorga: Conceptualization, methodology, formal analysis, investigation, data curation, writing \\u0026ndash; original draft, writing \\u0026ndash; review and editing, project administration. Cristian Olivares Pe\\u0026ntilde;a: Investigation, data curation, writing \\u0026ndash; review and editing. Daniel Brice\\u0026ntilde;o Mu\\u0026ntilde;oz: Data curation, formal analysis, writing \\u0026ndash; review and editing. Rodrigo Irarr\\u0026aacute;zaval del Campo: Investigation, data curation, writing \\u0026ndash; review and editing. All authors have read and approved the final version of the manuscript.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgments:\\u003c/h2\\u003e \\u003cp\\u003e The authors thank the endoscopy and pathology staff of Cl\\u0026iacute;nica D\\u0026aacute;vila for their contributions to clinical care and data collection.\\u003c/p\\u003e\\u003ch2\\u003eData availability:\\u003c/h2\\u003e \\u003cp\\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request. Due to privacy and ethical restrictions related to patient-level data, the dataset is not publicly available.\\u003c/p\\u003e \"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eMalfertheiner P, Megraud F, Rokkas T, Gisbert JP, Liou J-M, Schulz C et al (2022) Management of Helicobacter pylori infection: The Maastricht VI/Florence consensus report. Gut 71(9):1724\\u0026ndash;1762. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1136/gutjnl-2022-327745\\u003c/span\\u003e\\u003cspan address=\\\"10.1136/gutjnl-2022-327745\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePorras C, Nodora J, Sexton R, Ferreccio C, Jimenez S, Dominguez RL et al (2013) Epidemiology of Helicobacter pylori infection in six Latin American countries (SWOG Trial S0701). 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Cochrane Database Syst Rev 3:CD012080. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1002/14651858.CD012080.pub2\\u003c/span\\u003e\\u003cspan address=\\\"10.1002/14651858.CD012080.pub2\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRugge M, Meggio A, Pennelli G, Piscioli F, Giacomelli L, De Pretis G et al (2007) Gastritis staging in clinical practice: The OLGA staging system. 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Helicobacter 5(2):98\\u0026ndash;103. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1046/j.1523-5378.2000.00016.x\\u003c/span\\u003e\\u003cspan address=\\\"10.1046/j.1523-5378.2000.00016.x\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRugge M, de Boni M, Pennelli G, de Bona M, Giacomelli L, Fassan M et al (2010) Gastritis OLGA-staging and gastric cancer risk: A twelve-year clinico-pathological follow-up study. Aliment Pharmacol Ther 31(10):1104\\u0026ndash;1111. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1111/j.1365-2036.2010.04277.x\\u003c/span\\u003e\\u003cspan address=\\\"10.1111/j.1365-2036.2010.04277.x\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePimentel-Nunes P, Lib\\u0026acirc;nio D, Marcos-Pinto R, Areia M, Leja M, Esposito G et al (2019) Management of epithelial precancerous conditions and lesions in the stomach (MAPS II). Endoscopy 51(4):365\\u0026ndash;388. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1055/a-0859-1883\\u003c/span\\u003e\\u003cspan address=\\\"10.1055/a-0859-1883\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig L et al (2015) STARD 2015: An updated list of essential items for reporting diagnostic accuracy studies. BMJ 351:h5527. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1136/bmj.h5527\\u003c/span\\u003e\\u003cspan address=\\\"10.1136/bmj.h5527\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDixon MF, Genta RM, Yardley JH, Correa P (1996) Classification and grading of gastritis: The updated Sydney system. Am J Surg Pathol 20(10):1161\\u0026ndash;1181. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1097/00000478-199610000-00001\\u003c/span\\u003e\\u003cspan address=\\\"10.1097/00000478-199610000-00001\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCapelle LG, de Vries AC, Haringsma J, Ter Borg F, de Vries RA, Bruno MJ et al (2010) The staging of gastritis with the OLGA system by using intestinal metaplasia as an accurate alternative for atrophic gastritis. Gastrointest Endosc 71(7):1150\\u0026ndash;1158. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.gie.2009.12.029\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.gie.2009.12.029\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKato T, Yagi N, Kamada T, Shimbo T, Watanabe H, Ida K (2013) Diagnosis of Helicobacter pylori infection in gastric mucosa by endoscopic features: A multicenter prospective study. Dig Endosc 25(5):508\\u0026ndash;518. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1111/den.12031\\u003c/span\\u003e\\u003cspan address=\\\"10.1111/den.12031\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"Clínica Dávila\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Helicobacter pylori, rapid urease test, gastric atrophy, OLGA staging, diagnostic accuracy, histopathology\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9490483/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9490483/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eThe rapid urease test (RUT) is widely used for Helicobacter pylori (H. pylori) diagnosis, but its diagnostic performance in advanced gastric atrophy remains poorly characterized.\\u003c/p\\u003e\\u003ch2\\u003eAims\\u003c/h2\\u003e \\u003cp\\u003eTo evaluate RUT accuracy against histopathology and to determine whether gastric atrophy severity, assessed by the Operative Link on Gastritis Assessment (OLGA) staging system, independently predicts false-negative results.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eSingle-center retrospective cross-sectional diagnostic accuracy study of 744 adult patients undergoing upper gastrointestinal endoscopy with simultaneous RUT (read at 30 minutes) and updated Sydney protocol biopsies. RUT use was at endoscopist discretion (non-consecutive sample). Histopathology served as the reference standard. Sensitivity, specificity, predictive values, likelihood ratios, and Cohen\\u0026rsquo;s kappa were calculated overall and by OLGA risk category. Among histopathology-positive patients, Firth penalized logistic regression identified factors independently associated with false-negative RUT results.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eThe prevalence of H. pylori was 28.2% (210/744). Overall, the RUT showed a sensitivity of 89.5% (95% CI: 84.6\\u0026ndash;93.0), specificity of 91.9% (95% CI: 89.3\\u0026ndash;94.0), and Cohen\\u0026rsquo;s kappa of 0.79. Among patients with available OLGA classification (742/744), sensitivity declined from 97.1% in OLGA 0 to 64.7% in OLGA III\\u0026ndash;IV (Fisher\\u0026rsquo;s exact test, p\\u0026thinsp;=\\u0026thinsp;0.004). In multivariable analysis, OLGA III\\u0026ndash;IV was independently associated with false-negative RUT results (adjusted OR 4.41; 95% CI 1.25\\u0026ndash;14.99; p\\u0026thinsp;=\\u0026thinsp;0.022).\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eThe RUT demonstrates good overall diagnostic accuracy for H. pylori detection. However, sensitivity declines substantially with increasing gastric atrophy severity, and OLGA III\\u0026ndash;IV independently predicts false-negative results. A negative RUT should not be used as the sole criterion to exclude H. pylori infection in patients with advanced atrophy; complementary or histopathological confirmation is warranted in this population to prevent missed diagnoses with implications for gastric cancer prevention.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Rapid Urease Test Performance in Advanced Gastric Atrophy: A Diagnostic Accuracy Study Using OLGA Staging\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-05-18 06:06:14\",\"doi\":\"10.21203/rs.3.rs-9490483/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"7d2f4195-7796-491a-8a2b-b70c64891b00\",\"owner\":[],\"postedDate\":\"May 18th, 2026\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":68163055,\"name\":\"Gastroenterology \\u0026 Hepatology\"}],\"tags\":[],\"updatedAt\":\"2026-05-18T06:06:15+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-05-18 06:06:14\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9490483\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9490483\",\"identity\":\"rs-9490483\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}