Effects of Beta-zone Peripapillary Atrophy and Focal Lamina Cribrosa Defects on Peripapillary Vessel Parameters in Young Myopic Eyes
Bibliographic record
Abstract
PRECIS: The development of beta-zone peripapillary atrophy (β-PPA) and focal lamina cribrosa defect (FLD) was significantly associated with decreased peripapillary optical coherence tomography angiography (OCTA) vessel parameters in young myopic eyes. PURPOSE: The purpose of this study was to investigate whether β-PPA and FLD affect peripapillary vessel density (VD) or perfusion density (PD) from OCTA in young myopic eyes. MATERIALS AND METHODS: In a cross-sectional study, 330 eyes of 165 healthy volunteers with myopia were involved. Eyes underwent OCTA to measure peripapillary PD and VD. Eyes were grouped according to the presence of β-PPA or FLD: eyes without β-PPA or FLD (group A), eyes with β-PPA but without FLD (group B), and eyes with both β-PPA and FLD (group C). PD and VD were compared among 3 groups, and linear mixed-effect regression model was used to investigate the determinants of PD. RESULTS: β-PPA was found in 219 eyes (66.4%), and FLD was detected in 27 eyes (8.2%). The average VD and PD were greatest in group A (19.13±2.04 mm-1 and 0.375±0.038), followed by group B (18.34±2.26 mm-1 and 0.363±0.042) and group C (16.71±2.81 mm-1 and 0.330±0.052) (P<0.001). The linear mixed-effect model demonstrated that presence of FLD (P=0.001) or β-PPA (P<0.001), FLD count (P=0.004), and maximal β-PPA width (P<0.001) were significantly associated with average PD after controlling for multiple confounding factors. CONCLUSIONS: Development of β-PPA and FLD, which is closely related with axial elongation in myopic eyes, was significantly associated with reduced OCTA vessel parameters in young myopic eyes. OCTA may help to detect vascular changes and assess glaucoma risk in these eyes.
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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 | 0.000 |
| 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) | 0.001 | 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".