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Pharmacological interventions for non-ulcer dyspepsia

2006· review· en· W2158354121 on OpenAlexaff
Paul Moayyedi, Shelly Soo, Jonathan J Deeks, Brendan Delaney, Michael Innes, David Forman

Post-publication record

NatureRetraction
ReasonRetract and Replace;
Date2/16/2011 0:00
Flagged by OpenAlex?Yes

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

VenueCochrane Database of Systematic Reviews · 2006
Typereview
Languageen
Field
Topic
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsMedicineCochrane LibraryPlaceboMEDLINECINAHLInternal medicineRelative riskMeta-analysisConfidence intervalClinical trialPsychological interventionAlternative medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

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 pound450 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 H(2) 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: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library Issue 4, 2005), MEDLINE (1966 to January 2006), EMBASE (1988 to January 2006), CINAHL (1982 to January 2006), SIGLE, and reference lists of articles. We also contacted experts in the field and pharmaceutical companies. 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: Two review authors independently assessed eligibility, trial quality and extracted data. MAIN RESULTS: We included 73 trials: prokinetics (19 trials with dichotomous outcomes evaluating 3178 participants; relative risk reduction (RRR) 33%; 95% confidence intervals (CI) 18% to 45%), H(2)RAs (12 trials evaluating 2,183 participants; RRR 23%; 95% CI 8% to 35%) and PPIs (10 trials evaluating 3,347 participants; RRR 13%; 95% CI 4% to 20%) were significantly more effective than placebo. Bismuth salts (six trials evaluating 311 participants; RRR 40%; 95% CI -3 to 65%) were superior to placebo but this was of marginal statistical significance. Antacids (one trial evaluating 109 participants; RRR -2%; 95% CI -36% to 24%) and sucralfate (two trials evaluating 246 participants; RRR 29%; 95% CI -40% to 64%) were not statistically significantly superior to placebo. A funnel plot suggested that the prokinetic results could be due to publication bias or other small study effects. AUTHORS' 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.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0050.004
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0150.001

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.

Opus teacher head0.286
GPT teacher head0.486
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations378
Published2006
Admission routes1
Has abstractyes

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