Long-Term Statin Use and Dementia Risk in Taiwan
Bibliographic record
Abstract
BACKGROUND: The effect of statin use on dementia risk remains unclear. This study aims to examine the association between long-term statin use and dementia risk. METHODS: A nest case-control study within a nationwide representative population-based cohort. Individuals aged 50 years and older participating in Taiwan's National Health Insurance program between 1998 and 2009 were enrolled. A total of 9257 patients with at least 3 outpatient or 1 inpatient claims records for dementia were identified. Comparison patients were selected at a 1:2 ratio from age- and sex-matched participants without dementia. The cumulative period and average daily dosages of statins, fibrates, and other lipid-lowering agents were measured. RESULTS: The authors found a duration-response relationship, as dementia risk decreased by 9% per year of treatment of statins (adjusted odds ratio = 0.91; 95% confidence interval, 0.85-0.97). Use of high average dose statins for more than 1 year was associated with a lower risk of dementia than use of low average dose. However, there was no significant difference in dementia risks between lipophilic and hydrophilic statins. Fibrates or other lipid-lowering agents had no significant association with dementia risk. CONCLUSION: Our results suggest that long-term use of statin is associated with a reduced dementia risk.
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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 | 0.001 |
| 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".