<i>Helicobacter pylori</i>Antibiotic Resistance: Trends Over Time
Bibliographic record
Abstract
Resistance to antibiotics can be a major problem in the treatment of bacterial infections. As the use of antibiotics increases, bacterial resistance to these agents is rising and in many cases is responsible for the failure of treatment regimens. Although the treatment of Helicobacter pylori infection requires the use of more than one antibiotic to obtain adequate eradication rates, the efficacy of the currently used antibiotic combinations has been shown to be decreased by resistance to one of the antibiotics. The use of antibiotics in regiments for the treatment of H pylori is increasing in many countries, including Canada. This increase is both in the use of these antibiotics alone for the treatment of nongastrointestinal infections and in their use in association with proton pump inhibitors for the treatment of H pylori infection. In several European and Asian countries, where resistance to antibiotics is being monitored, it has been demonstrated the H pylori resistance to metronidazole and to clarithromycin increased throughout the 1990s. Thus far, the data available in Canada do not show increased resistance to either of these antibiotics. As for other antibiotics used in the treatment of H pylori infection such as tetracycline and amoxicillin, the rate of resistance to these agents is still very low and does not constitute a significant problem. Because the efficacy of the regimens used in the treatment of H pylori infection is compromised by resistance to the antibiotics used, it is important that H pylori resistance rate in Canada and throughout the world continue to be monitored. Only with such reliable data can the most optimal regimens be recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".