Do patients with non-ulcer dyspepsia respond differently to<i>Helicobacter pylori</i>eradication treatments from those with peptic ulcer disease? A systematic review
Bibliographic record
Abstract
AIM: It is controversial whether patients with non-ulcer dyspepsia (NUD) respond differently to Helicobacter pylori (H pylori) eradication treatment than those with peptic ulcer disease (PUD). To review the evidence for any difference in H pylori eradication rates between PUD and NUD patients. METHODS: A literature search for full articles and meeting abstracts to July 2004 was conducted. We included studies evaluating the efficacy of a proton pump inhibitor (P) or ranitidine bismuth citrate (RBC) plus two antibiotics of clarithromycin (C), amoxicillin (A), metronidazole (M), or P-based quadruple therapies for eradicating the infection. RESULTS: Twenty-two studies met the criteria. No significant difference in eradication rates was found between PUD and NUD patients when treated with 7-d RBCCA, 10-d PCA or P-based quadruple therapies. When the 7-d PCA was used, the pooled H pylori eradication rate was 82.1% (431/525) and 72.6% (448/617) for PUD and NUD patients, respectively, yielding a RR of 1.15 (95%CI 1.01-1.29). However, the statistically significant difference was seen only in meeting abstracts, but not in full publications. CONCLUSION: There is no convincing evidence to suggest that NUD patients respond to H pylori eradication treatments differently from those with PUD, although a trend exists with the 7-d PCA therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".