Review – Epidemiology of Helicobacter pylori infection
Bibliographic record
Abstract
We encompassed recent data related to Helicobacter pylori epidemiology. Infection prevalence was low (<20%) in countries, such as Canada, Sweden, Korea and Taiwan, but still high (>50%) in other countries, such as Cameroon, Chile and Bangladesh. Among positive subjects, CagA frequency ranged from ≤33.3% in Japan and Italy to >90% in Chile. In Bulgaria, the infection was frequent (>76%) in children with anemia and weight loss. Huge racial differences in infection prevalence were observed. In the USA, African Americans were 2- and 3-fold more likely to be H. pylori- and CagA-positive than the Caucasians, respectively. Canadian endoscopy patients of Asian/South American origin were 3.8-fold more often infected than the Caucasians. Overall, the infection affected ≥62.0% of diabetics in studies from Europe and Africa and was also more frequent in patients with autoimmune thyroid diseases, arteriosclerosis, glaucoma, osteoporosis and various neurological and skin diseases than in controls. Recent data concerning infection transmission, including H. pylori DNA in oral samples, food, animals, and yeasts were added. H. pylori DNA was found in one-half of vaginal yeasts and one-third of oral yeasts. In addition to the well-known risk factors for the infection, contact with dogs and sheep was reported. Annual recurrence rate of the infection was 0.2-4.8%, although the rate was higher (>18%) in Chinese children. Preservation and variegation of H. pylori genes in numerous American countries were revealed by whole genome sequencing. Briefly, H. pylori infection remains a concern in several countries and in certain subpopulations, as well as in patient groups with some non-gastric diseases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".