Efficacy of central nervous system stimulant treatment for cocaine dependence: a systematic review and meta‐analysis of randomized controlled clinical trials
Bibliographic record
Abstract
AIMS: To evaluate the efficacy of central nervous system (CNS) stimulants compared with placebo for the treatment of cocaine dependence. METHODS: A systematic review and meta-analysis was carried out. Bibliographic databases were searched, reference lists of retrieved studies were hand-searched and the first authors of each study were contacted. All randomized controlled clinical trials (RCCT) comparing the efficacy of any CNS stimulant with placebo in cocaine-dependent patients were included. Quantitative data synthesis was performed for each single CNS stimulant and for all CNS stimulants. RESULTS: Nine RCCT met the inclusion criteria. These RCCT included 640 patients and compared five CNS stimulants: mazindol, dextroamphetamine, methylphenidate, modafinil and bupropion with placebo. No CNS stimulant improved study retention [RR = 0.94 (0.81-1.09)] or cocaine use [RR = 0.90 (0.79-1.02)]. An exploratory analysis using indirect estimations of cocaine use showed that the proportion of cocaine-positive urine screens was lower with dexamphetamine than with placebo [RR = 0.73 (0.60-0.90)] and that all CNS stimulants pooled together also suggested a significant decrease of cocaine use [RR = 0.87 (0.77-0.99)]. Data on craving could not be meta-analysed due to heterogeneity, but no RCCT found differences in cocaine craving between active drug and placebo except one, whose outcome favoured dexamphetamine. No serious adverse event (AE) was reported. Average of AE-induced dropouts was low and was greater for CNS stimulants than placebo: 4.4% versus 1.3% (P = 0.03). CONCLUSION: The main outcomes of this study do not support the use of CNS stimulants for cocaine dependence. Nevertheless, secondary analyses provide some hopeful results that encourage further research with these drugs, mainly with dexamphetamine and modafinil.
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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 | 0.022 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.041 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".