Pharmacological interventions for non-ulcer dyspepsia
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND: The commonest cause of upper gastrointestinal symptoms is non-ulcer dyspepsia (NUD) and yet the pathophysiology of this condition has been poorly characterised and the optimum treatment is uncertain. It is estimated that pound 450 million is spent on dyspepsia drugs in the UK each year. OBJECTIVES: This review aims to determine the effectiveness of six classes of drugs (antacids, histamine H2 antagonists, proton pump inhibitors, prokinetics, mucosal protecting agents and antimuscarinics) in the improvement of either the individual or global dyspepsia symptom scores and also quality of life scores patients with non-ulcer dyspepsia. SEARCH STRATEGY: Trials were located through electronic searches of the Cochrane Controlled Trials Register (CCTR), MEDLINE, EMBASE, CINAHL and SIGLE, using appropriate subject headings and text words, searching bibliographies of retrieved articles, and through contacts with experts in the fields of dyspepsia and pharmaceutical companies. SELECTION CRITERIA: All randomised controlled trials (RCTs) comparing drugs of any of the six groups with each other or with placebo for non-ulcer dyspepsia (NUD). DATA COLLECTION AND ANALYSIS: Data were collected on dyspeptic symptom scores either individual or global symptom assessments and also quality of life scores and adverse effects. MAIN RESULTS: A total of 11796 citations were obtained. 155 trials were retrieved and 96 trials fulfilled our eligibility criteria. However, subsequent data extraction was not possible in 31 trials. The final 65 trials were included in the meta-analysis. Prokinetics (14 trials with dichotomous outcomes generating 1053 patients; relative risk reduction [RRR] = 48%; 95% confidence intervals [CI] = 27% to 63%), H2RAs (11 trials generating 2,164 patients; RRR = 22%; 95% CI = 7% to 35%) and PPIs (7 trials generating 3,031 patients; RRR = 14%; 95% CI = 5% to 23%) were significantly more effective than placebo. Bismuth salts (6 trials generating 311 patients; RRR = 40%; 95% CI = -3 to 65%) were superior to placebo but this was of marginal statistical significance. Antacids (one trial generating 109 patients; RRR = -2%; 95% CI = -36% to 24%) and sucralfate (two trials generating 246 patients; RRR = 29%; 95% CI = -40% to 64%) were not statistically significantly superior to placebo. A funnel plot suggested that the prokinetic and H2RA results could be due to publication bias. REVIEWER'S CONCLUSIONS: There is evidence that anti-secretory therapy may be effective in NUD. The trials evaluating prokinetic therapy are difficult to interpret as the meta-analysis result could have been due to publication bias. The effect of these drugs is likely to be small and many patients will need to take them on a long-term basis so economic analyses would be helpful and ideally the therapies assessed need to be inexpensive and well tolerated.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".