Prevalence of Helicobacter Pylori in Iranian Children: A Systematic Review and Meta-Analysis Study
Bibliographic record
Abstract
Background: The prevalence of infection is reported variously in different studies in Iran. These study aimed to determine the prevalence of infection in children in Iran. Materials and Methods: In this systematic review and meta-analysis, we searched Medline, Scopus, EMBASE, Web of Science, and Google scholar systematically from Jan 1990 to up to December 2020. Helicobacter pylori, Child, pylori, Campylobacter pylori and were used for search. All English-language articles associated with the prevalence of H. performed in Iran were evaluated, and after passing the qualification assessment (Newcastle –Ottawa Quality Assessment Scale), these were entered into the analysis. The prevalence of H. in children at a 95% confidence interval was estimated using a random-effect model. Results: The search initially identified a total of 778 publications, and finally, 43 studies involving 16,939 children were included. The pooled prevalence of H. infection in Iranian children is estimated as 43% (I2=98.1, p=0.001). Based on the diagnostic methods, the pooled prevalence in the group with stool antigen evaluation was 44% (I2=99%, p=0.001), the pooled prevalence in the serology evaluation group was 40% (I2=96%, p=0.001), in the biopsy group, 50%, in Rapid urease test/ urea breath test 40%, and in combined diagnostic tests group 56% (I2=84.5%, p=0.001), and in the not determined group the pooled estimate was 26%. The heterogeneity between groups was significant (p <0.001). Conclusion: The pooled prevalence of H. infection in children in Iran is estimated as 43%, which has been higher than the global prevalence. Also, a higher prevalence rate was reported in studies in which the diagnostic test was a biopsy.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".