STATIN USE AND THE INCIDENCE OF AGE-RELATED MACULAR DEGENERATION
Bibliographic record
Abstract
PURPOSE: Age-related macular degeneration (AMD) shares many of the same risk factors with atherosclerosis. There is a postulated role of lipid-lowering agents in preventing AMD. This meta-analysis investigates the possible role of statins in the prevention of AMD onset and progression. METHODS: MEDLINE, EMBASE, Cochrane CENTRAL, and the reference lists of included studies were systematically searched from inception to September 2020. Studies were included if they measured the risk of AMD development or progression with statin use. The primary outcomes assessed were AMD incidence and progression. Secondary outcomes were the incidence of early AMD, late AMD, choroidal neovascularization, and geographic atrophy. RESULTS: Twenty-one articles (1 randomized control trial and 20 observational studies) collectively reporting on 1,460,989 participants were included. The pooled risk ratios (95% confidence interval) for statin use on any, early, and late AMD incidence were 1.05 (0.85-1.29) (P = 0.44), 0.99 (0.88-1.11) (P = 0.86), and 1.15 (0.90-1.47) (P = 0.27), respectively. In patients with existing AMD, the respective risk ratios for statin use on incidence of AMD progression, choroidal neovascularization, and geographic atrophy were 1.04 (0.70-1.53) (P = 0.85), 0.99 (0.66-1.48) (P = 0.95), and 0.84 (0.58-1.22) (P = 0.36). CONCLUSION: This meta-analysis found that there was no significant difference in the incidence or progression of AMD based on statin use.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".