Efficacy and safety of psychostimulants for amphetamine and methamphetamine use disorders: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Amphetamine and methamphetamine use disorders are associated with severe health and social consequences. No pharmacological therapy has been approved for the treatment of these disorders. Psychostimulants can act as maintenance-like therapies for managing substance use among these patients. The aim of this study is to evaluate the literature examining the efficacy and safety of psychostimulant agents for increasing abstinence and treatment retention among patients with amphetamine and methamphetamine use disorders. METHODS: We searched MEDLINE, EMBASE, PsycInfo, Cochrane Central, and CINAHL from inception to August 2016. Selection of studies, data extraction, and risk of bias assessment were conducted independently by two reviewers. We conducted meta-analyses to provide a pooled summary estimate for included trials and report the review according to PRISMA guidelines. RESULTS: We identified and selected 17 studies with 1387 participants. Outcome reporting across trials was inconsistent, and the overall quality of evidence was very low due to high risk of bias and indirectness. A meta-analysis of five trials (642 participants) found no effect of psychostimulants for end-of-study abstinence (odds ratio = 0.97, 95% confidence interval 0.65 to 1.45). Additionally, the pooled estimate from 14 studies (1184 participants) showed no effect of psychostimulants for treatment retention (odds ratio = 1.20, 95% confidence interval = 0.91 to 1.58). The incidence of serious adverse events did not differ between intervention and placebo groups based on qualitative reports from trials. CONCLUSIONS: Quantitative analyses showed no effect of psychostimulants for sustained abstinence or treatment retention. We also identified the need for more rigorous studies in this research area with clinician and patient important outcomes.
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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 | 0.019 | 0.048 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.045 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".