Use of retinal ischemic perivascular lesions (RIPLS) as a biomarker for cardiovascular disease – a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: This study aims to evaluate the association between retinal ischemic perivascular lesions (RIPLs) detected by optical coherence tomography (OCT) and the risk of all-cause cardiovascular morbidity. METHODS: A systematic review and meta-analysis were performed. PubMed MEDLINE, Scopus, and Cochrane CENTRAL were searched for observational studies from January 2015 to March 2025 assessing RIPLs and cardiovascular disease (CVD). Odds ratios (ORs) with 95% confidence intervals (CIs) were pooled using a random-effects model. RESULTS: Of 61 studies screened, six met inclusion criteria and four were included in the meta-analysis (total n = 710). The pooled OR for CVD morbidity associated with RIPLs was 2.8 (95% CI: 1.98–3.95), indicating over a twofold increased risk. Heterogeneity was minimal (I² = 0%). CONCLUSIONS: RIPLs detected by OCT are significantly associated with increased cardiovascular risk. Due to OCT’s non-invasive and accessible nature, RIPLs may be a useful screening biomarker for early detection of 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".