Abstract MP59: Retinal Vascular Metrics Predict Pial Collateral Status in Patients With Acute Ischemic Stroke
Bibliographic record
Abstract
Background: The extent of the pial collateral circulation may determine outcomes in an acute ischemic stroke. Experimental studies suggest that retinal vessel metrics and geometric patterning may predict the pial collateral status. We have undertaken a translational study to quantify and relate retinal vascular metrics to the grade of pial collaterals in patients with acute ischemic stroke. Method: 35 patients admitted with acute stroke underwent computed tomography angiography (OCT) and were graded as having good (n=20)(47.55 ± 10.65 years) or poor (n=15) (48.93 ± 10.91 years) pial collaterals and compared to healthy controls (n=21)(44.26 ± 10.15 years). Retinal images were generated using OCT and central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), artery-to-vein ratio (AVR), segmented fractal analysis and lacunarity, tortuosity index and fractal dimensions (capacity D 0 , information D 1 and correlation D 2 , curve asymmetry, singularity length and f-alfa-max using MONA software) were quantified. Results: Age ( p =0.709), BMI ( p =0.451), total cholesterol ( p =0.845), triglycerides ( p =0.679), LDL ( p =0.953), HDL ( p =0.361) and HbA 1c ( p =0.210) were comparable but the national institute of health stroke scale ( p =0.031) and modified Rankin Scale ( p =0.048) were higher in patients with poor compared to good collaterals. CRAE ( p =0.114), CRVE ( p =0.946), AVR ( p =0.114), lacunarity ( p =0.442), tortuosity index ( p =0.681), fractal analysis ( p =0.656), curve asymmetry ( p =0.619) and singularity length ( p =0.944) did not differ between patients with poor compared to good collaterals. However, fractal capacity D 0 (1.673 ± 0.029 vs 1.654 ± 0.025, p =0.042), fractal information D 1 (1.610 ± 0.027 vs 1.591 ± 0.024, p =0.036), fractal correlation D 2 (1.581± 0.028 vs 1.564 ± 0.024, p =0.060), and f alfa max (1.674 ± 0.027 vs 1.654 ± 0.025, p =0.030) were higher in patients with poor compared to good collaterals. Conclusion: This study shows differences in retinal vessel fractal dimensions between acute stroke patients with poor compared to good pial collaterals. This represents a non-invasive imaging method to define the pial collateral status and develop personalized intervention management strategies in acute ischemic stroke 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 | 0.000 |
| 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".