The Role of Lipid‐Lowering Drugs in Cognitive Function: A Meta‐Analysis of Observational Studies
Bibliographic record
Abstract
STUDY OBJECTIVE: To quantify the risk of cognitive impairment with use of lipid-lowering drugs. DESIGN AND DATA SOURCES: Literature search through MEDLINE and EMBASE databases; data from seven observational studies were analyzed. MEASUREMENTS AND MAIN RESULTS: We quantified the risk of cognitive impairment first with the use of any lipid-lowering drug, and then specifically with the statins, using the random effects model. We tested for heterogeneity using the Q statistic as well as quantitatively using the Ri statistic. All seven studies provided data for statin users, and five provided data only on use of lipid-lowering drugs. Compared with patients not receiving lipid-lowering drugs, the relative risk of cognitive impairment with any lipid-lowering drug was 0.62 but was not statistically significant (95% confidence interval [CI] 0.28-1.38), and the relative risk with statins was 0.43 and was statistically significant (95% CI 0.31-0.62). CONCLUSION: Lipid-lowering drugs--in particular, the statins--seem to lower the odds of developing cognitive impairment. Randomized, controlled trials are needed to address the efficacy of these agents specifically in different types of dementia.
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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 | 0.019 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.026 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".