Age-Related Vitamin D Deficiency Is Associated with Reduced Macular Ganglion Cell Complex: A Cross-Sectional High-Definition Optical Coherence Tomography Study
Bibliographic record
Abstract
BACKGROUND: Vitamin D deficiency is associated with smaller volume of optic chiasm in older adults, indicating a possible loss of the visual axons and their cellular bodies. Our objective was to determine whether vitamin D deficiency in older adults is associated with reduced thickness of the ganglion cell complex (GCC) and of the retinal nerve fibre layer (RNFL), as measured with high-definition optical coherence tomography (HD-OCT). METHODS: Eighty-five French older community-dwellers without open-angle glaucoma and patent age-related macular degeneration (mean, 71.1±4.7 years; 45.9% female) from the GAIT study were separated into 2 groups according to serum 25OHD level (i.e., deficient≤25 nmol/L or sufficient>25 nmol/L). Measurements of GCC and RNFL thickness were performed using HD-OCT. Age, gender, body mass index, number of comorbidities, dementia, functional autonomy, intracranial volume, visual acuity, serum calcium concentration and season of testing were considered as potential confounders. RESULTS: Mean serum 25OHD concentration was 58.4±26.8 nmol/L. Mean logMAR visual acuity was 0.03±0.06. Mean visual field mean deviation was -1.25±2.29 dB. Patients with vitamin D deficiency (n=11) had a reduced mean GCC thickness compared to those without vitamin D deficiency (72.1±7.4 μm versus 77.5±7.5 μm, P=0.028). There was no difference of the mean RNFL thickness in these two groups (P=0.133). After adjustment for potential confounders, vitamin D deficiency was associated with reduced GCC thickness (ß=-5.12, P=0.048) but not RNFL thickness (ß=-9.98, P=0.061). Specifically, vitamin D deficiency correlated with the superior medial GCC area (P=0.017) and superior temporal GCC area (P=0.010). CONCLUSIONS: Vitamin D deficiency in older patients is associated with reduced mean GCC thickness, which can represent an early stage of optic nerve damage, prior to RNFL loss.
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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 | 0.001 |
| 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 | 0.001 | 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".