Retinal arterial occlusion with multiple retinal emboli and carotid artery occlusion disease. Haemodynamic changes and pathways of embolism
Bibliographic record
Abstract
OBJECTIVE: To introduce a special subgroup, retinal artery occlusion (RAO) with multiple emboli, which is highly associated with ipsilateral carotid artery occlusion disease (CAOD). METHODS AND ANALYSIS: This is a cohort study. Cases of RAO with multiple retinal emboli were consecutively enrolled. All patients underwent at least one of the carotid/cerebral evaluations: carotid arteriography, orbital/carotid colour Doppler ultrasonography and CT angiography to demonstrate haemodynamic changes and to discuss possible mechanisms and pathways of the emboli. RESULTS: Among 208 RAO eyes, 12 eyes (5.7%) in 11 patients had multiple emboli were recruited in this study. Eleven eyes (91.6%) had ipsilateral carotid plaques and atherosclerosis with high-grade stenosis; among them, five were total carotid occlusion. Haemodynamic changes were found in nine patients with RAO (81.8%) with carotid stenosis 60% or greater. Most compensatory intracranial circulations were re-established via the circle of Willi with antegrade ophthalmic flows, but the direction of ophthalmic flow reversed in three eyes indicating the recruitment of external collaterals. Two cases underwent carotid stent successfully. CONCLUSION: RAOs with multiple emboli are rare but highly associated with severe CAOD with haemodynamic flow changes, warning critical condition in carotid/cerebral circulations. Either direct embolism from the carotid or cardiac lesions or indirect embolism via the collateral pathways is the mechanism of pathogenesis. Immediate action should start to manage these patients to prevent further deterioration.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".