Associations of statin use with the onset and progression of open-angle glaucoma: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Statins, the first-line therapy for hyperlipidemia, have received considerable attention as candidates for glaucoma treatments given its neuroprotective effects. In this systematic review and meta-analysis, we intended to assess the association of statin use with the onset and progression of open-angle glaucoma (OAG). Methods: Databases including PubMed, Embase and Web of Science Core Collection were searched for longitudinal studies reporting the association between statin use and OAG onset or progression on Feb 3, 2021. A meta-analysis was performed for the association between statin use and OAG onset. Relative risks (RRs) with 95% confidential intervals (CIs) were retrieved from included studies and pooled using random-effects models. Potential risks of bias were evaluated by the Newcastle-Ottawa Quality Assessment Scale for all eligible studies. This study had been registered on PROSPERO (CRD 42021232172). Findings: =0.199;). No significant heterogeneity or publication bias was found for studies included in the meta-analysis. There were inconsistent evidences for the association between statin use and OAG progression. Interpretation: Statin use is associated with a slightly lower risk of OAG onset based on existing evidences from longitudinal observational studies, the association between statin use and OAG progression remains inconclusive. The included evidences were typically weak due to poor study design and under-powered studies. Current findings should be interpreted cautiously and still need to be validated in further research. Funding: The National Key R&D Program of China (2018YFC0116500), Science and Technology Planning Project of Guangdong Province (2013B20400003), the China Postdoctoral Science Foundation (2019TQ0365), the National Natural Science Foundation of China (82000901 and 82101171).
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.036 |
| Bibliometrics | 0.007 | 0.008 |
| 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".