The Relation of Corneal Arcus With Cardiovascular Diseases: A Systematic Review
Bibliographic record
Abstract
The prognostic value of corneal arcus (arcus senilis) for cardiovascular disease (CVD) remains debated. We evaluated associations of arcus with cardiometabolic risk, prevalent CVD, and incident events, and summarized how consistently studies adjusted for standard risk factors. We systematically reviewed observational studies (1960-2017) from Asia, Europe, and North America. Designs included cross-sectional, case-control, and prospective cohorts. Risk of bias was appraised using the Newcastle-Ottawa Scale (cohort/case-control) and the Joanna Briggs Institute checklist (cross-sectional). Twelve studies met the inclusion criteria. The prevalence of arcus increased with age and was higher in men. Cross-sectional and case-control evidence showed consistent associations with atherogenic lipid profiles and a higher burden of prevalent CVD. Prospective findings were mixed: arcus predicted incident events in targeted subgroups (notably younger men and some Asian male populations) but offered limited independent prognostic value and minimal incremental discrimination in general, older populations once age, sex, and lipids were considered. Overall risk of bias was low in most cohorts; moderate ratings reflected limited confounder control, non-slit-lamp exposure assessment, or sampling constraints. Corneal arcus appears to primarily reflect cumulative lipid exposure. In adults under 50 years or select higher-risk men, its presence should prompt lipid evaluation and risk review; however, its low sensitivity means the absence of arcus does not exclude CVD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".