Association between serum vitamin D levels and retinal vein occlusion: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Purpose: Previous studies found seasonal variations in the incidence of retinal vein occlusion (RVO), with more occurrence in winter. There is increasing evidence linking vitamin D deficiency and RVO. Therefore, we conducted a meta-analysis to evaluate the association between vitamin D levels and RVO. Methods: A comprehensive search of the databases of MEDLINE and EMBASE was performed from inception to February 2024. Observational studies compared 25-hydroxyvitamin D levels [25(OH)D] levels between adult patients with RVO versus non-RVO controls were included. We calculated pooled mean difference (MD) and pooled odds ratio (OR) with 95% confidence intervals (CI) of our data using random-effects model, generic inverse variance method. Results: Five studies involving 528 patients (228 patients with RVO and 300 controls were included in the meta-analysis. 25(OH)D was significantly lower in patients with RVO (pooled MD of -9.65 [95%CI -13.72 to -5.59, I2 = 92.2%). Vitamin D deficiency (serum 25(OH)D < 20) was significantly associated with RVO with the pooled OR of 14.52 (95%CI 1.72 to 122.59, I2 = 90.5). There was no difference in 25(OH)D levels between patients with central RVO and branched RVO (pooled MD of -0.94 [95%CI -3.91 to 2.03, I2 = 59.1%). Conclusion: Our meta-analysis demonstrates that serum vitamin D levels were lower in patients with RVO than non-RVO controls. Clinicians could consider screening for vitamin D deficiency in patients with RVO. Further studies are warranted to determine the correlation between vitamin D levels and disease severity and the role of vitamin D supplements in these populations.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".