Diagnosis and Treatment of <i>Helicobacter Pylori</i> Infection: Korean and Overseas Guidelines
Bibliographic record
Abstract
The Korean College of Helicobacter and Upper Gastrointestinal Research proposed revised guidelines for the diagnosis and treatment of Helicobacter pylori infection in 2013.These new guidelines were developed using an adaptation process, and addressed the revised recommendations especially in the changes of indication and treatment of H. pylori infection in Korea.They included 19 statements: 11 on the indications for tests and treatment, four for the diagnosis, and four for the treatment.A critical difference between the new and previous guidelines was that the proposed treatment regimen was more detailed, in consideration of the increasing resistance to antibiotics in Korea.Although clarithromycin-containing triple therapy was proposed as the first-line treatment option, per the previous guidelines, a bismuth-based quadruple regimen was also proposed as an effective alternative.In the case of treatment failure following bismuth quadruple therapy, second-line treatment should be based on two or more antibiotics that had not been used previously.Several overseas guidelines -from America, Europe, Canada, Japan, and the Asia-Pacific region -have been published concerning H. pylori infection; they indicate regional differences in epidemiology, antibiotic susceptibility, and national health insurance systems.This review compares the guidelines for H. pylori infection among these regions.(Korean
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".