Effects of Aging on Anterior and Posterior Corneal Astigmatism
Bibliographic record
Abstract
PURPOSE: To evaluate age-related changes in astigmatism of both corneal surfaces and the whole cornea. METHODS: The right eyes of 370 subjects were measured with a rotating Scheimpflug camera (Pentacam). Astigmatisms of the anterior and posterior corneal surfaces were determined. The total corneal astigmatism was derived using power vector summation and vergence tracing. Age-related changes to corneal astigmatism were evaluated using polar value analysis (both in diopter and millimeter). RESULTS: For the anterior and total cornea, the proportion of with-the-rule astigmatisms decreased and those of oblique and against-the-rule astigmatisms increased with age. For the posterior cornea, most eyes displayed against-the-rule astigmatisms in all age groups. There was a significant trend toward against-the-rule astigmatism associated with increasing age for both anterior and total corneal astigmatisms (mean changes of -0.18 and -0.16 diopters/5 years, respectively), and toward with the rule in posterior corneal astigmatism (a mean change of 0.022 diopters/5 years). Regarding shape changes, a "flat meridian toward a more vertical orientation" trend with increasing age for both the anterior and posterior corneal surfaces was observed (mean changes of 0.0295 and 0.0224 mm/5 years, respectively). The posterior corneal surface compensated for the astigmatism arising from the anterior corneal surface in 91.4% and 47.7% of eyes in the 21-30 and > or =71 years groups, respectively. CONCLUSIONS: There were age-related shifts toward against-the-rule and with-the-rule astigmatisms for the anterior and posterior corneal surfaces, respectively. The compensating effects of the posterior corneal surface on anterior corneal astigmatism decreased with advancing age.
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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 | 0.000 | 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".