Retinal Vessel Analysis as a Novel Screening Tool to Identify Childhood Acute Lymphoblastic Leukemia Survivors at Risk of Cardiovascular Disease
Bibliographic record
Abstract
BACKGROUND: Microvascular endothelial dysfunction is central to the pathogenesis of cardiovascular disease (CVD). The eye offers direct access for endothelial health assessment via the retinal microvasculature. The aim of the study was to investigate whether image-based retinal vessel analysis is a feasible method of assessing endothelial health in survivors of childhood acute lymphoblastic leukemia (cALL). MATERIALS AND METHODS: Cardiovascular risk factors (CRFs) were estimated using the 30-year Framingham Risk Score in 73 childhood leukemia survivors (median age: 25; median years from diagnosis: 19) and 78 healthy controls (median age: 23). Radial arterial stiffness was measured using pulse wave analyzer, while endothelial activation markers were measured by soluble intercellular adhesion molecule 1 (sICAM-1) and soluble vascular cell adhesion molecule 1 (sVCAM-1). Retinal fundus images were analyzed for central retinal artery/vein equivalents (CRAE/CRVE) and arteriolar-venular ratio (AVR). RESULTS: cALL survivors had higher CRF (P<0.0001), arterial stiffness (P=0.001), and sVCAM-1 (P=0.007) compared with controls. Survivors also had significantly higher CRVE (P=0.021) while AVR was significantly lower (P=0.026) in survivors compared with controls, compatible with endothelial dysfunction. In cALL survivors with intermediate risk for CVD, CRAE, and AVR are significantly lower, while sVCAM-1 and sICAM-1 are significantly higher when compared with survivors with low CVD risk after adjusting with covariates (age, sex, and smoking status). CONCLUSIONS: cALL survivors have an increased risk of CVD compared with age-matched peers. The survivors demonstrated microvasculopathy, as measured by retinal vascular analysis, in addition to physical and biochemical evidence of endothelial dysfunction. These changes predate other measures of CVD. Retinal vessel analysis may be utilized as a robust screening tool for identifying survivors at increased risk for developing CVD.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".