Prevalence and determinants of serological evidence of atrophic gastritis among Arab and Jewish residents of Jerusalem: a cross-sectional study
Bibliographic record
Abstract
Objective Understanding the correlates of premalignant gastric lesions is essential for gastric cancer prevention. We examined the prevalence and correlates of serological evidence of atrophic gastritis, a premalignant gastric condition, using serum pepsinogens (PGs) in two populations with differing trends in gastric cancer incidence. Methods In a cross-sectional study, using ELISA we measured serum PGI and PGII concentrations (Biohit, Finland), Helicobacter pylori serum IgG and cytotoxin-associated gene A (CagA) antigen IgG antibodies in archived sera of 692 Jews and 952 Arabs aged 25–78 years, randomly selected from Israel’s population registry in age–sex and population strata. Multivariable logistic regression analyses were performed. Results Using cut-offs of PGI <30µg/L or PGI:PGII <3.0, the prevalence of atrophic gastritis was higher among Arab than Jewish participants: 8.8% (95% CIs 7.2% to 10.8%) vs 5.9% (95% CI 4.4% to 7.9%), increasing with age in both groups (p<0.001 for trend). Among Jewish participants, infection with H. pylori CagA phenotype was positively related to atrophic gastritis: adjusted OR (aOR) 2.16 (95% CI 0.94 to 4.97), but not to non-CagA infections aOR 1.17 (95% CI 0.53 to 2.55). The opposite was found among Arabs: aOR 0.09 (95% CI 0.03 to 0.24) for CagA positive and aOR 0.15 (95% CI 0.06 to 0.41) for Cag A negative phenotypes (p<0.001 for interaction). Women had a higher atrophic gastritis prevalence than men. Obesity and smoking were not significantly related to atrophic gastritis; physical activity tended to be inversely associated in Arabs (p=0.08 for interaction). Conclusions The prevalence of atrophic gastritis was higher among Arabs than Jews and was differently associated with the CagA phenotype.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".