Meta‐analysis: <i>Helicobacter pylori</i> eradication treatment efficacy in children
Bibliographic record
Abstract
BACKGROUND: Several meta-analyses assessing the efficacy of anti-Helicobacter pylori treatment in adults have been published but a comparable meta-analysis in children is lacking. AIMS: To summarize the efficacy of treatments aimed at eradicating H. pylori in children and to identify sources of variation in treatment efficacy across studies. METHODS: We searched Medline, reference lists from published study reports, and conference proceedings for anti-H. pylori treatment trials in children. Weighted meta-regression models were used to find sources of variation in efficacy. RESULTS: Eighty studies (127 treatment arms) with 4436 children were included. Overall, methodological quality of these studies was poor with small sample sizes and few randomized-controlled trials. The efficacy of therapies varied across treatment arms, treatment duration, method of post-treatment assessment and geographic location. Among the regimens tested, 2-6 weeks of nitroimidazole and amoxicillin, 1-2 weeks of clarithromycin, amoxicillin and a proton pump inhibitor, and 2 weeks of a macrolide, a nitroimidazole and a proton pump inhibitor or bismuth, amoxicillin and metronidazole were the most efficacious in developed countries. CONCLUSIONS: Before worldwide treatment recommendations are given for eradication of H. pylori, additional well-designed randomized placebo-controlled paediatric trials are needed, especially in developing countries where both drug resistance and disease burden is high.
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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 | 0.025 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.045 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".