Disease manifestations of <i>Helicobacter pylori</i> infection in Arctic Canada: using epidemiology to address community concerns
Bibliographic record
Abstract
OBJECTIVES: Helicobacter pylori infection, linked to gastric cancer, is responsible for a large worldwide disease burden. H pylori prevalence and gastric cancer rates are elevated among indigenous Arctic communities, but implementation of prevention strategies is hampered by insufficient information. Some communities in northern Canada have advocated for H pylori prevention research. As a first step, community-driven research was undertaken to describe the H pylori-associated disease burden in concerned communities. DESIGN: Participants in this cross-sectional study completed a clinical interview and gastroscopy with gastric biopsies taken for histopathological examination in February 2008. SETTING: Study procedures were carried out at the health centre in Aklavik, Northwest Territories, Canada (population ∼600). PARTICIPANTS: All residents of Aklavik were invited to complete a clinical interview and gastroscopy; 194 (58% female participants; 91% Aboriginal; age range 10-80 years) completed gastroscopy and had gastric biopsies taken. PRIMARY AND SECONDARY OUTCOME MEASURES: This analysis estimates the prevalence of gastric abnormalities detected by endoscopy and histopathology, and associations of demographic and clinical variables with H pylori prevalence. RESULTS: Among 194 participants with evaluable gastric biopsies, 66% were H pylori-positive on histology. Among H pylori-positive participants, prevalence was 94% for acute gastritis, 100% for chronic gastritis, 21% for gastric atrophy and 11% for intestinal metaplasia of the gastric mucosa, while chronic inflammation severity was mild in 9%, moderate in 47% and severe in 43%. In a multivariable model, H pylori prevalence was inversely associated with previous gastroscopy, previous H pylori therapy and aspirin use, and was positively associated with alcohol consumption. CONCLUSIONS: In this population, H pylori-associated gastric histopathology shows a pattern compatible with elevated risk of gastric cancer. These findings demonstrate that local concern about health risks from H pylori is warranted and provide an example of how epidemiological research can address health priorities identified by communities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".