Efficacy, effectiveness, and safety/tolerability of lithium in children and adolescents up to 18 years of age with conditions other than mood disorders: A scoping review
Bibliographic record
Abstract
In youth, lithium is an effective medication for mood disorders, particularly for mixed and manic episodes of bipolar disorder, and is generally well-tolerated. In some clinical contexts, lithium is used off-label to manage other conditions. We conducted a scoping review of studies on the efficacy/effectiveness and safety/tolerability of lithium for treating youths with psychiatric conditions other than mood disorders or neurological disorders. We searched EMBASE, MEDLINE, PsycINFO, PubMed, and ClinicalTrials.gov up to March 31, 2025, with no restrictions on language or document type. We included studies of any design involving children and adolescents (mean age up to 18) treated with lithium, either as monotherapy or in combination with other psychotropic agents. We assessed study quality using the appropriate NHLBI tools and visually summarized the results with a heat map displaying sample size by study design and conditions, as well as the timeline of included studies' publication years. From 2687 records initially identified, after de-duplication removal and screening, 367 full-text reports were assessed, and 41 studies were included in the review, grouped by type of psychiatric or neurological disorder, most of which had a small sample. Among the assessed studies, 60 % of were considered of "fair" quality and 40 % of "poor" quality. Overall, although the clinical use of lithium beyond bipolar disorder in youth is increasing, the underlying evidence base remains limited. More rigorous research based on RCTs and observational studies with designs aimed at reducing confounding are needed to guide clinical practice.
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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 | 0.015 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".