One optometrist’s personal experience with age-related macular degeneration (AMD) and nutritional supplementation
Bibliographic record
Abstract
Background: Age-related macular degeneration (AMD) is the leading cause of blindness in ageing western societies and accounts for greater than 50% of all US visual disability. This report describes the 25-year history of a 66-year-old optometrist who has successfully endured AMD. Case Report: Visual acuity and serial retinal photographs from 1983 to 2009 as various nutritional modalities and non-dietary lifestyle changes were introduced. After starting lutein-based nutritional supplements beginning at approximately 15 years from diagnosis, the optometrist’s Snellen visual acuity improved in his right eye from 20/40 to 20/25 with a subjective improvement in distortion, but eventually regressed to 20/70-20/80 with some increase in metamorphopsia. The left eye, initially 20/30, improved to 20/15 and has remained stable at 20/20 with complete resolution of metamorphopsia and near complete resolution of a parafoveal scotoma. Fundus photographs demonstrate a reduction in soft and hard drusen count over time in each retina and possible parafoveal repigmentation of atrophic areas with later addition of higher dose zeaxanthin. Conclusions: AMD is a nutritionresponsive disease. The carotenoids, lutein and zeaxanthin appear to be particularly robust therapeutic components of nutritional supplement formulations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".