Ocular and Systemic Risk Factors and Clinical Implications in Glaucoma Patients With Retinal Vein Occlusion
Bibliographic record
Abstract
PRÉCIS: Ocular factors such as worse visual acuity, increased optic disc cupping, and peak IOP-commonly associated with advanced glaucoma-have been identified as risk factors for concurrent RVO in glaucoma. PURPOSE: This study aimed to identify ocular and systemic factors associated with concurrent retinal vein occlusion (RVO) in glaucoma and to examine their clinical significance. PATIENTS AND METHODS: This retrospective study analyzed glaucoma patients with RVO, which was compared with a matched control group of glaucoma without RVO. Various ocular and systemic factors were identified as increasing the risk of RVO. RVO subgroup analyses were performed in central retinal vein occlusion (CRVO) and branch retinal vein occlusion. The RVO group was then categorized into correspondence and noncorrespondence groups based on the synchronicity of RVO location and glaucomatous defect. RESULTS: A total of 86 eyes in the RVO group and 70 eyes in the control group were included. Multivariate analysis identified significant risk factors for RVO, including worse visual acuity (VA) (HR=4.887, P =0.011), higher peak intraocular pressure (IOP) (HR=4.140, P =0.005), and increased vertical cup-to-disc ratio (CDR) (HR=3.061, P =0.020). Subgroup analysis revealed that higher peak IOP ( P =0.030) and lower peripapillary retinal nerve fiber layer thickness ( P =0.019) were associated with CRVO. In the RVO group, 68.6% were categorized into the correspondence group, of which the ocular and systemic profiles were similar to the noncorrespondence group. CONCLUSION: These findings suggest that glaucoma and RVO may share common pathophysiologic mechanisms, with elevated IOP potentially contributing to the development of RVO. The majority of RVO locations in glaucoma were synchronous with existing glaucomatous defects, which highlights the need for regular fundus examinations in high-risk individuals.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".