Management of Amphetamine and Methamphetamine Use Disorders: A Systematic Review and Network Meta-analysis of Randomized Trials
Bibliographic record
Abstract
The current evidence regarding effective management of methamphetamine and amphetamine (MA/A) use disorders is inconclusive. Therefore, we assessed the comparative benefits and tolerability of pharmacological, psychosocial, and harm reduction interventions for management of MA/A use disorders. We searched six electronic databases for randomized controlled trials of any pharmacological, psychosocial, or harm reduction interventions in adults with MA/A use disorders. We performed a random-effects frequentist network meta-analysis and used the GRADE approach to assess the certainty of evidence. We included 72 randomized trials (6836 participants). Low certainty evidence suggests quetiapine may extend abstinence compared to placebo [risk ratio (RR) 3.17 (95% confidence intervals (CI), 1.24 to 8.07)] and weekly average proportion of patients with negative urine samples [mean difference (MD) 32.17 (95% CI, 14.08 to 50.26)]. Low certainty evidence also suggested that riluzole may be associated with a higher weekly average proportion of patients with negative urine samples [MD 24.10 (95% CI, 5.54 to 42.66)]. Very low certainty evidence suggests methylphenidate alone [compared to placebo MD 10.24 (95% CI, 3.49 to 16.99)] or in combination with matrix model [MD 23.55 (95% CI, 7.64 to 39.46)] may be associated with an increased weekly average proportion of patients with negative urine samples. Compared to placebo, contingency management alone [MD 21.20 (95% CI, 11.39 to 31.00), very low certainty] or in combination with cognitive behavioural therapy [MD 34.85 (95% CI, 19.63 to 50.08), very low certainty] may be associated with longer duration of abstinence. Compared to placebo, venlafaxine [RR 0.27 (95% CI 0.08 to 0.90), low certainty] and citicoline [RR 0.69 (95% CI 0.49 to 0.99), lowcertainty] may be among the most tolerable interventions. Very few interventions may be associated with slight improvement in certain outcomes, but no intervention showed moderate- to high-certainty evidence for important changes across any patient-important outcomes. Supplementary Information: The online version contains supplementary material available at 10.1007/s11469-024-01379-w.
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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 | 0.026 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".