Risk of dementia in bipolar disorder and the interplay of lithium: a systematic review and meta‐analyses
Bibliographic record
Abstract
OBJECTIVES: To assess whether bipolar disorder (BD) increases the rate of dementia and whether lithium is related to a lower risk of dementia in BD. METHODS: A total of 10 studies (6859 BD; 487 966 controls) were included in the meta-analysis to test whether BD is a risk factor for dementia. In addition, five studies (6483 lithium; 43 496 non-lithium) were included in the meta-analysis about the potential protective effect of lithium in BD. RESULTS: BD increases the risk of dementia (odds ratio (OR): 2.96 [95% CI: 2.09-4.18], P < 0.001), and treatment with lithium decreases the risk of dementia in BD (OR: 0.51 [95% CI: 0.36-0.72], P < 0.0001). In addition, secondary findings from our systematic review showed that the risk of progression to dementia is higher in BD than in major depressive disorder (MDD). Moreover, the number of mood episodes predicted the development of dementia in BD. CONCLUSION: Individuals with BD are at higher risk of dementia than both the general population or those with MDD. Lithium appears to reduce the risk of developing dementia in BD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.023 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".