Effects of axial length on retinal nerve fiber layer and macular ganglion cell-inner plexiform layer measured by spectral-domain OCT
Bibliographic record
Abstract
PURPOSE: To evaluate the influence of ocular axial length on circumpapillary retinal nerve fiber layer and ganglion cell-inner plexiform layer thickness in healthy eyes after correcting for ocular magnification effect. METHODS: In this cross-sectional study, we evaluated 120 eyes from 60 volunteer participants (myopes, emmetropes, and hyperopes). The thickness of the circumpapillary retinal nerve fiber layer and ganglion cell-inner plexiform layer were measured using the spectral optical coherence tomography (OCT)-Cirrus HD-OCT and correlated with ocular axial length. Adjustment for ocular magnification was performed by applying Littmann's formula. RESULTS: Before the adjustment for ocular magnification, age-adjusted mixed models analysis demonstrated a significant negative correlation between axial length and average circumpapillary retinal nerve fiber layer thickness (r=-0.43, p<0.001), inferior circumpapillary retinal nerve fiber layer thickness (r=-0.46, p<0.001), superior circumpapillary retinal nerve fiber layer thickness (r=-0.31, p<0.05), nasal circumpapillary retinal nerve fiber layer thickness (r=-0.35, p<0.001), and average ganglion cell-inner plexiform layer thickness (r=-0.35, p<0.05). However, after correcting for magnification effect, the results were considerably different, revealing only a positive correlation between axial length and temporal retinal nerve fiber layer thickness (r=0.42, p<0.001). Additionally, we demonstrated a positive correlation between axial length and average ganglion cell-inner plexiform layer thickness (r=0.48, p<0.001). All other correlations were not found to be statistically significant. CONCLUSIONS: Before adjustment for ocular magnification, axial length was negatively correlated with circumpapillary retinal nerve fiber layer and ganglion cell-inner plexiform layer thickness measured by Cirrus-OCT. We attributed this effect to ocular magnification associated with greater axial lengths, which was corrected with the Littman's formula. Further studies are required to investigate the impact of ocular magnification correction on the diagnostic accuracy of Cirrus-OCT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".