Investigation of the Peripapillary Choriocapillaris in Normal Tension Glaucoma, Primary Open-angle Glaucoma, and Control Eyes
Bibliographic record
Abstract
PRECIS: The peripapillary choriocapillaris (CC) was observed to be significantly impaired in normal tension glaucoma (NTG) subjects compared with normal controls using optical coherence tomography angiography (OCTA). PURPOSE: The aim was to quantitatively evaluate the peripapillary CC in NTG, primary open-angle glaucoma (POAG), and control eyes using OCTA. MATERIALS AND METHODS: Ninety eyes (30 controls, 30 NTG, and 30 POAG) from 73 patients were imaged using the Zeiss Plex Elite 9000. Five repeat 3×3 mm OCTA scans were acquired both nasally and temporally to the optic disc and subsequently averaged. Four CC flow deficit (FD) measures were calculated using the fuzzy C-means approach: FD density (FDD), mean FD size (MFDS), FD number (FDN), and FD area (FDA). RESULTS: Temporal NTG CC parameters were associated with visual field index and mean deviation (P<0.05). The control group showed a significantly lower nasal FDD (nasal: 3.79±1.26%, temporal: 4.48±1.73%, P=0.03), FDN (nasal: 156.43±38.44, temporal: 178.40±45.68, P=0.02), and FDA (nasal: 0.22±0.08, temporal: 0.26±0.10, P=0.03) when compared with temporal optic disc. The NTG group showed a significantly higher FDD (NTG: 5.04±2.38%, control: 3.79±1.26%, P=0.03), FDN (NTG: 185.90±56.66, control: 156.43±38.44, P=0.04), and FDA (NTG: 0.30±0.14 mm2, control: 0.22±0.08 mm2, P=0.03) nasal to the optic disc compared with controls. CONCLUSIONS: Association between CC parameters and glaucoma severity in NTG, but not POAG subjects, suggests vascular abnormalities may be a potential factor in the multifactorial process of glaucoma damage in NTG 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 | 0.001 |
| 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".