Relationship Between Posterior Vitreous Detachment and Macular Dimensions in Myopic Eyes
Bibliographic record
Abstract
Background: Posterior vitreous detachment (PVD) can result in serious pathologic events at the vitreoretinal interface. This study aims to assess the relationship between PVD, macular thickness (MT), and the foveal avascular zone (FAZ) in myopic eyes. Methods: This retrospective study evaluated 63 myopic subjects' data who were examined between January 1 and June 30, 2019. The myopes were grouped on a severity scale, namely mild, moderate, high, and very high using their spherical equivalent (SE). The PVD classification was based on OCT images. The status of the PVD and MT were evaluated with the Macular Cube 200×200 images, the FAZ with an OCTA Angioplex, and the dimensions were calculated using a customized algorithm. Results: The study population (114 eyes) had a median (range) age was 26.00 (22.00-28.00) years and the females constituted 62.3% of the dataset. In this population, 10 eyes had no PVD in any quadrant, and 73 eyes had incomplete PVD in all four quadrants. The inferior quadrant had the maximum rate of PVD occurrences and the nasal quadrant had the least number of occurrences. High myopic eyes exhibited significantly increased low foveal volume (p = <0.01). The inferior part of the para- and perimacular area showed a significant thinning in very high myopic eyes (p = <0.050). The very high myopic eyes showed a significant alteration of FAZ's circularity index (p = 0.002). Conclusion: In high and very high myopic eyes, an increasing trend of partial PVD is seen, most commonly in the inferior quadrant. A significant alteration in foveal volume and circularity index of the FAZ is seen in high and very high myopic 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 | 0.001 | 0.003 |
| 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".