Lipophilic Statin Use and Suicidal Ideation in a Sample of Adults With Mood Disorders
Bibliographic record
Abstract
BACKGROUND: Mood disorders are associated with a high risk of suicide. Statin therapy has been implicated in this relationship. AIMS: To further clarify reported associations between suicide and cholesterol in mental health conditions, we conducted an analysis of dietary, clinical, and suicidal ideation measures in community-living adults with mood disorders. METHOD: Data were used from a cross-sectional study of a randomly selected community-based sample (> 18 years; n = 97) with verified mood disorders. Dietary (e.g., fat, iron, vitamin intakes), clinical (e.g., current depression and mania symptoms, medications), and sociodemographic (age, sex, and income) measures were analyzed using bivariate statistics and Poisson regression with robust variance. RESULTS: Participants were predominantly female (71.1%) with bipolar disorder (59.8%); almost one-third (28.9%) were taking lipophilic statins. The prevalence of suicidal ideation was more than 2.5 times in those taking statins, PR = 2.59, 95% CI 1.27-5.31, p < .05. The prevalence ratio for suicidal ideation was 1.10, 95% CI 1.06-1.15, p < .001, for each unit increase in mania symptom scores. No associations between suicidal ideation and dietary intake measures were identified. CONCLUSION: Individuals with mood disorders may be susceptible to neuropsychiatric effects of cholesterol-lowering drugs, which warrants further research.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".