Prevalence of Helicobacter pylori in a First Nations population in northwestern Ontario.
Bibliographic record
Abstract
OBJECTIVE: To assess prevalence of Helicobacter pylori infection, reasons for referral for gastroscopy, and clinical findings of gastroscopy in a symptomatic First Nations population in northwestern Ontario from 2009 to 2011. DESIGN: Three hundred four hospital charts of symptomatic patients who underwent upper endoscopy between June 2009 and March 2011 were reviewed. SETTING: Meno Ya Win Health Centre in Sioux Lookout, Ont. PARTICIPANTS: First Nations patients with dyspepsia undergoing gastroscopy. MAIN OUTCOME MEASURES: Reason for referral, and clinical and histologic findings on gastroscopy. RESULTS: The most common reasons for referral for gastroscopy were dyspepsia (59.2%) and undiagnosed anemia (18.1%). Overall, 66.8% of patients underwent biopsies; 37.9% of these patients tested positive for H pylori. Gastritis was encountered the most often, in 46.1% of patients; gastric ulcers in 6.9% of patients; and normal gastric mucosa was seen 36.8% of the time. The rate of H pylori infection is higher than in urban Canadian populations, but lower than in previous aboriginal prevalence estimates, particularly those based on seroprevalence values. CONCLUSION: This study raises the clinical question of how eradication testing and treatment protocols should be addressed in remote regions with high disease prevalence. As more is learned about the role H pylori infection plays in serious gastrointestinal diseases, rural and aboriginal populations might need a special focus on testing availability and treatment close to home.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".