Use of statins and the risk of dementia and mild cognitive impairment: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract We conducted a systematic review and meta-analysis to investigate whether the use of statins could be associated with the risk of all-caused dementia, Alzheimer’s disease (AD), vascular dementia (VaD), and mild cognitive impairment (MCI). Major electronic databases were searched until December 27th, 2017 for studies investigating use of statins and incident cognitive decline in adults. Random-effects meta-analyses calculating relative risks (RRs) were conducted to synthesize effect sizes of individual studies. Twenty-five studies met eligibility criteria. Use of statins was significantly associated with a reduced risk of all-caused dementia (k = 16 studies, adjusted RR (aRR) = 0.849, 95% CI = 0.787–0.916, p = 0.000), AD (k = 14, aRR = 0.719, 95% CI = 0.576–0.899, p = 0.004), and MCI (k = 6, aRR = 0.737, 95% CI = 0.556–0.976, p = 0.033), but no meaningful effects on incident VaD (k = 3, aRR = 1.012, 95% CI = 0.620–1.652, p = 0.961). Subgroup analysis suggested that hydrophilic statins were associated with reduced risk of all-caused dementia (aRR = 0.877; CI = 0.818–0.940; p = 0.000) and possibly lower AD risk (aRR = 0.619; CI = 0.383–1.000; p = 0.050). Lipophilic statins were associated with reduced risk of AD (aRR = 0.639; CI = 0.449–0.908; p = 0.013) but not all-caused dementia (aRR = 0.738; CI = 0.475–1.146; p = 0.176). In conclusion, our meta-analysis suggests that the use of statins may reduce the risk of all-type dementia, AD, and MCI, but not of incident VaD.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.040 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".