Systematic review and network meta‐analysis: efficacy of drugs for functional dyspepsia
Bibliographic record
Abstract
BACKGROUND: Functional dyspepsia (FD) is a relapsing and remitting condition affecting between 5% and 10% of people. Efficacious therapies are available, but their relative efficacy is unknown. AIM: To perform a systematic review with network meta-analysis to resolve this uncertainty. METHODS: We searched the medical literature through July 2020 for randomised controlled trials (RCTs) assessing efficacy of drugs for adults with FD, compared with each other, or placebo. Trials reported a dichotomous assessment of symptom status after completion of therapy. We pooled data using a random effects model. Efficacy was reported as a pooled relative risk (RR) of remaining symptomatic with a 95% confidence interval (CI) to summarise efficacy of each comparison tested. Relative ranking was assessed with surface under the cumulative ranking curve (SUCRA) probabilities. RESULTS: We identified 71 eligible RCTs (19 243 participants). Tricyclic antidepressants (TCAs) were ranked second for efficacy (RR of remaining symptomatic = 0.71; 95% CI 0.58-0.87, SUCRA 0.87), and first when only low risk of bias trials were included. Most RCTs that used TCAs recruited patients who were refractory to other drugs included in the network. Although sulpiride or levosulpiride were ranked first for efficacy (RR = 0.49; 95% CI 0.36-0.69, SUCRA 0.99), trial quality was low and only 86 patients received active therapy. TCAs were more likely to cause adverse events than placebo. CONCLUSIONS: receptor antagonists, standard- and low-dose proton pump inhibitors, sulpiride or levosulpiride, itopride and acotiamide were all more efficacious than placebo for FD.
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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 | 0.042 | 0.105 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.043 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".