Prescribed psychostimulants and other pro‐cognitive medications in bipolar disorder: A systematic review and meta‐analysis of recurrence of manic symptoms
Bibliographic record
Abstract
Abstract Objectives Clinicians are often hesitant to prescribe psychostimulants in bipolar disorder (BD) due to concerns of inducing (hypo)mania, despite limited published evidence on associations between prescribed psychostimulant use and recurrence of mood episodes in BD. The current systematic review and meta‐analysis evaluated the emergence of (hypo)manic symptoms in patients with BD receiving prescribed psychostimulants or other pro‐cognitive medications in euthymic or depressive states. Methods A systematic search was performed of MEDLINE, Embase, and PsychINFO from inception to April 5, 2023 and search of Clinicaltrials.gov and Clinicaltrialsregister.eu for unpublished data. References of included studies were hand‐searched. Randomized trials and prospective longitudinal studies that evaluated psychostimulants and non‐stimulant medications recommended for the treatment of ADHD by the Canadian ADHD practice guidelines were included. The review was reported in line with PRISMA guidelines and was preregistered on PROSPERO (CRD42022358588). Results After screening 414 unique records, we included 27 studies, of which five reported data that was quantitatively synthesized ( n = 1653). The use of psychostimulants in BD was not associated with increased scores on the Young Mania Rating Scale in patients who were in a euthymic or depressed state (SMD IV −0.17; 95% CI, −0.40 to 0.06) compared to placebo. There was a high degree of study‐level heterogeneity ( I 2 = 80%). A qualitative synthesis of studies revealed a limited risk of medication‐induced manic symptoms. Conclusions Our review provides preliminary evidence to suggest psychostimulants and non‐stimulant ADHD medications have a limited risk of precipitating (hypo)mania symptoms. More extensive studies evaluating the safety and efficacy of these medications are warranted.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".