Quantitative detection of macular microvascular abnormalities identified by optical coherence tomography angiography in different hematological diseases
Bibliographic record
Abstract
It is now understood that hematological diseases can have detrimental effects on the retina, reducing retinal capillaries, compromising visual function, and potentially causing irreversible visual impairment. Over the years, there has been limited research on macular microvascular abnormalities, such as changes in vessel density and the foveal avascular zone (FAZ) and variations in the severity of these effects across different types of blood disorders. This study aims to quantitatively assess the impact of various hematological disorders on the retina using optical coherence tomography angiography (OCTA). Compared with healthy eyes, patients with different blood diseases exhibited reductions in linear vessel density (LVD), perfusion vessel density (PVD), FAZ area, and FAZ perimeter. Notably, patients with erythrocyte diseases showed more significant abnormalities in LVD and PVD, while patients with lymphocytic diseases demonstrated more pronounced abnormalities in the FAZ area and perimeter. OCTA imaging could potentially reflect changes of the retinal microvascular of patients with hematological diseases and may serve as a valuable tool for distinguishing abnormalities affecting different blood cell lines. This approach offers a novel avenue for assessing, treating, and monitoring blood disorders.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".