Best Vitelliform Macular Dystrophy Natural History Study Report 2
Bibliographic record
Abstract
PURPOSE: To analyze the retinal imaging findings and natural history of Best vitelliform macular dystrophy (BVMD). DESIGN: Single-center retrospective, consecutive, observational study. PARTICIPANTS: Patients with a clinical diagnosis of BVMD, from pedigrees with a likely disease-causing monoallelic variant in BEST1. METHODS: Data were extracted from electronic and physical case notes. Retinal imaging with OCT and fundus autofluorescence (FAF) was analyzed cross-sectionally and longitudinally. MAIN OUTCOME MEASURES: Qualitative and quantitative OCT and FAF analysis. RESULTS: Two hundred twenty-two patients (127 men) from 141 families were included. Mean central retinal thickness on OCT at baseline was 337.2 μm for the right eye and 341.1 μm for the left eye, with a mean annual thickness loss of 5.7 and 5.2 μm, respectively. The presence of the OCT features: previtelliform lesion, solid vitelliform lesion, vitelliform lesion with subretinal fluid, and focal choroidal excavation were associated with a better mean visual acuity (VA), whereas the presence of intraretinal fluid and atrophy/fibrosis were correlated with a worse mean VA. Fundus autofluorescence showed an area of hyperautofluorescence at the posterior pole in 138 eyes (34.7%), a circumscribed area of hyperautofluorescence superior or superotemporal of the optic nerve head in 53 eyes (13.3%), fibrotic changes in 48 eyes (12.1%), and atrophy in 41 eyes (10.3%). CONCLUSIONS: Best vitelliform macular dystrophy shows a wide spectrum of phenotypes on OCT and FAF imaging. The slow and variable disease course may pose a challenge in identification of early end points for therapeutic trials aimed at altering kinetics of degeneration. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosures may be found in the Footnotes and Disclosures at the end of this article.
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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) | 0.000 | 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) | 0.000 | 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".