The Effect of Helicobacter pylori Infection on Overweight: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The association between Helicobacter pylori infection and overweight, as one of the most common health issues, remains controversial. In this study, we systematically reviewed the effect of H. pylori infection and overweight to get a reliable answer. Methods: We used the Preferred Reporting Items for the Systematic Review and Meta-Analysis statement. We searched the association between H. pylori and overweight infection in international databases including Medline, Web of knowledge and Scopus, without any limitations of language, publication type, and publication status in search step of this systematic review from 2000 to 2020. We surveyed the title, abstract and full text of each research studies, and we used Newcastle-Ottawa quality for assessing the quality of each paper. A random effects model was used to calculate the pooled odd ratio with 95% confidence intervals. Results: Fifteen papers were eligible for this review. The selected studies reported different Odd Ratio between overweight and H. pyloriinfection but Odds Ratio (95% confidence interval) in our systematic and meta-analysis study was estimated at 1.42 (95%CI; 1.12, 1.81) and it was statistically significant (P: 0.003). Conclusion: H. pylori infection is significantly associated with overweight, therefore, the eradication of H. pylori infection is suggested because this infectious might be resulted in overweight.
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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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.023 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".