Corneal Thickness and Endothelial Morphology in Normal Thai Eyes
Bibliographic record
Abstract
Abstract Background: This study aimed to determine the influence of age on central corneal thickness and corneal endothelial morphology as well as to identify the relationship between them in normal Thai eyes.Methods: Non-contact specular microscopy was performed in volunteers stratified into seven age groups ranging from 11-88 years. The corneal endothelial parameters studied included central corneal thickness (CCT), endothelial cell density (ECD), coefficient of variation in cell size (CV), cell area (CA) and percentage of regular hexagonal cells.Results: In a total of 501 subjects (1002 eyes), the mean age was 43.12 ± 18.80 years and 347(69.3%) were females. The mean CCT, ECD, CV, CA, and hexagonality was 533.80 ± 33.00 μm, 2,732±258 cell/mm2, 37.61 ± 6.76%, 369.04 ± 37.90 mm, and 49.03% ± 7.53%, respectively. There was a statistically significant inverse correlation between age and CCT (r = -0.212, P <0.001), ECD (r = -0.484, P <0.001), and hexagonality (r = -0.193, P <0.001). The estimate rate of endothelial cell loss was 0.2% per year, whereas CV and CA had statistically significant correlation with age (r = 0.200, P <0.001 and r = 0.475, P <0.001). CCT correlated directly with ECD (r = 0.177, P <0.001).Conclusion: Normative data for corneal endothelial morphology in healthy Thai eyes showed that ECD, CCT, and hexagonality were significantly decreased, while CV and CA were increased with aging. The central corneal thickness was correlated with the endothelial cell density.
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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) | 0.002 | 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".