Helicobacter pylori and gastroesophageal reflux disease: a cross sectional study.
Bibliographic record
Abstract
UNLABELLED: BACKGROUND\ AIMS: Helicobacter Pylori (H. Pylori) is a key pathogenetic factor in gastritis, peptic ulcer disease, gastric carcinoma and lymphoma but its relationship with gastroesophageal reflux disease (GERD) is controversial. The aim of the study is to estimate the possible association between the presence of H. pylori and GERD. METHODOLOGY: In this retrospective study we examined the endoscopy and pathology reports of all the 638 consecutive patients who had upper gastrointestinal endoscopy and adequate mucosal sampling in 2005 in our department at the University of Padova. Yates corrected chi2 test was used to compare the H. Pylori frequency in the different histological groups. Multinomial logistic regression was used to identify possible predictors of H. Pylori infection. RESULTS: In this selected population 133 patients were affected by H. Pylori infection (20.8%) and 107 were affected by GERD according to Montreal definition. No significant relation between H. Pylori infection and GERD or NERD (non erosive reflux disease) was evidenced. As expected histological gastritis at the examination confirmed to be the strongest predictor of infection with a odds ratio of 39.4 (95% CI 5.4-287.4, p < 0.01). Upper abdominal pain showed to be the only clinical independent predictors for the presence of H. Pylori infection with a odds ratio of 1.5 (95% CI 1.0-2.3, p = 0.04). CONCLUSIONS: Our study showed that in north eastern Italy there is no association between H. Pylori infection and GERD. On the contrary presence of histological gastritis and upper abdominal pain were confirmed to be significant predictors of H. Pylori infection. No endoscopic characteristic is significantly related to the presence of H. Pylori.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".