Prevalence of Helicobacter pylori in type 2 diabetic patients: a meta-analysis
Bibliographic record
Abstract
Objective To systematically assess the prevalence of Helicobacter pylori in patients with type 2 diabetes mellitus. Methods Medline (PubMed) and EMBASE data-bases were searched from January 1990 to May 2015. Studies that provided data on Helicobacter pylori infection rate in both type 2 diabetes and control groups were selected. The quality of these studies was assessed using the Newcastle-Ottawa Quality Assessment Scale by two researchers, respectively. Meta-analysis was performed using the random effects model. Odd ratios (OR) and 95% Confidence Interval (CI) were calculated by STATA 12.0. Results Thirteen studies were included, OR of Helicobacter pylori infection rate was 1.70 (95% CI: 1.30-2.22, P=0.013) in patients with type 2 diabetes compared with control group. In subgroup analysis, the prevalence of Helicobacter pylori was higher in patients in Asia compared with control group(OR = 1.81, 95% CI: 1.25-2.61, P=0.025). The prevalence of Helicobacter pylori was higher in diabetic patients in gastric mucosal biopsy group compared with control group(OR=1.65, 95% CI: 1.10-2.46, P=0.002). Conclusion Patients with type 2 diabetes mellitus may have a higher risk of Helicobacter pylori infection. Key words: Type 2 diabetes mellitus; Helicobacter pylori; Prevalence; Meta-analysis
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.039 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".