Association of microaneurysms with retinal vascular alterations in patients with retinal vein occlusion
Bibliographic record
Abstract
Objective To investigate the localization, distribution, and type of central microaneurysms (MAs) and their relationship with retinal vascular alterations in patients with retinal vein occlusion (RVO). Methods In this cross-sectional study, ultra-widefield color fundus photography (UWF-CF), standard and single-capture 65° widefield (WF) optical coherence tomography angiography (OCTA) were performed in consecutive patients with RVO treated at the Department of Ophthalmology and Optometry, Medical University of Vienna. UWF-CF, en face and B-Scans in 6 mm × 6 mm OCTA were examined for detection of MAs. Nonperfusion areas (NPA) and collateral vessels (CV) were evaluated on WF-OCTA, ghost vessels (GV), and tortuous vessels (TV) on UWF-CF. Results One-hundred-and-twelve patients were included in the study, and data from 59 eyes of 59 patients with disease duration longer than 3 months, good image quality, and without relevant ocular comorbidities were eligible for statistical analysis. Fifty-six of 59 (94.9%) patients were previously treated with anti-vascular endothelial growth factor agents for macular edema, 31 of 59 (52.5%) patients presented with MAs in the central 6 mm and 60 MAs were found in total using multimodal imaging. There was no statistically significant difference in the greatest diameter of fluid-associated versus non-fluid-associated MAs ( p = 0.53). Eyes with MAs were associated with CV, TV, and GV (χ 2 -test; p < 0.001, p = 0.0498, and p = 0.001). Median NPA was 27.3 mm 2 (quartiles 1.3–62.8 mm 2 ) in eyes with MAs and 0 mm 2 (quartiles 0–36.2 mm 2 ) in eyes without MAs (Mann-Whitney- U -test; p = 0.018). Conclusion MAs were associated with extensive NPA, the presence of CV, GV, and TV. There was no correlation between the diameter of the MA and the adjacent intraretinal fluid in our predominantly pretreated RVO study patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".