Longitudinal Changes in Disc and Retinal Lesions Among Highly Myopic Adolescents in Singapore Over a 10-Year Period
Bibliographic record
Abstract
OBJECTIVES: To examine the progression pattern of disc and retinal lesions in highly myopic Chinese adolescents over a 10-year period in Singapore. METHODS: This longitudinal study included Chinese participants who showed high myopia (spherical equivalent [SE] worse than or equal to -5 diopters [D]), no history of refractive surgery, and available fundus photographs at both 2006 (baseline) and 2016 (10-year follow-up) visits. Forty-four adolescents (aged 12-16 years at baseline) who were re-examined later at follow-up were included. Cycloplegic refraction, biometry, and fundus photography were performed at both visits. A trained grader classified myopic macular degeneration (MMD) based on the Meta-pathologic myopia classification and disc lesions from fundus photographs. Choroidal thickness (CT) measurements were performed at 10-year follow-up using swept-source optical coherence tomography. The ocular parameters and lesions were compared between baseline and follow-up. RESULTS: There was a significant worsening of high myopia at follow-up to -7.5±1.8 D (mean SE±SD) in 2016 versus -6.2±1.3 D in 2006; (P<0.001). The 10-year changes included increased degree of tessellation (26 eyes, 29.5%), development of new tessellated fundus (19 eyes, 21.6%), disc tilt (7 eyes, 8.0%), and expansion of peripapillary atrophy size (33 eyes, 37.5%). Eyes with early-onset tessellation (present at baseline, 48 eyes) showed significantly thinner CT (P<0.05), compared with eyes with late-onset tessellation (incident at 10-year follow-up, 19 eyes). No cases of MMD were recorded at baseline or 10-year follow-up. CONCLUSIONS: Although there was no incident MMD, the retinal and disc lesions worsened over the follow-up period. Early-onset fundus tessellation was associated with thinner CT.
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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 | 0.000 | 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".