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Record W4391188712 · doi:10.1016/j.ophtha.2024.01.027

Best Vitelliform Macular Dystrophy Natural History Study Report 1

2024· article· en· W4391188712 on OpenAlexfundno aff
Yannik Laich, Michalis Georgiou, Kaoru Fujinami, Malena Daich Varela, Yu Fujinami‐Yokokawa, Shaima Awadh Hashem, Thales A. C. de Guimarães, Omar A. Mahroo, Andrew R. Webster, Michel Michaelides

Bibliographic record

VenueOphthalmology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsnot available
FundersUCL Institute of Ophthalmology, University College LondonMoorfields Eye Hospital NHS Foundation TrustAlexander S. Onassis Public Benefit FoundationMinistry of Health, Labour and WelfareFight for Sight UKJapan Agency for Medical Research and DevelopmentNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer ResearchFoundation Fighting BlindnessSantenA.G. Leventis FoundationNational Institute for Health and Care ResearchAstellas PharmaWellcome Trust
KeywordsMedicineChoroidal neovascularizationOphthalmologyNatural historyVisual acuityCohortMacular degenerationRetrospective cohort studyFamily historyFluorescein angiographySurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To analyze the genetic findings, clinical spectrum, and natural history of Best vitelliform macular dystrophy (BVMD) in a cohort of 222 children and adults. DESIGN: Single-center retrospective, consecutive, observational study. PARTICIPANTS: Patients with a clinical diagnosis of BVMD from pedigrees with a likely disease-causing monoallelic sequence variant in the BEST1 gene. METHODS: Data were extracted from electronic and physical case notes. Electrophysiologic assessment and molecular genetic testing were analyzed. MAIN OUTCOME MEASURES: Molecular genetic test findings and clinical findings including best-corrected visual acuity (BCVA), choroidal neovascularization (CNV) rates, and electrophysiologic parameters. RESULTS: Two hundred twenty-two patients from 141 families were identified harboring 69 BEST1 variants. Mean age at presentation was 26.8 years (range, 1.3-84.8 years) and most patients (61.5%) demonstrated deterioration of central vision. Major funduscopic findings included 128 eyes (30.6%) with yellow vitelliform lesions, 78 eyes (18.7%) with atrophic changes, 49 eyes (11.7%) with fibrotic changes, 48 eyes (11.5%) with mild pigmentary changes, and 43 eyes (10.3%) showing a vitelliruptive appearance. Mean BCVA was 0.37 logarithm of the minimum angle of resolution (logMAR; Snellen equivalent, 20/47) for the right eye and 0.33 logMAR (Snellen equivalent, 20/43) for the left eye at presentation, with a mean annual loss rate of 0.013 logMAR and 0.009 logMAR, respectively, over a mean follow-up of 9.7 years. Thirty-seven patients (17.3%) received a diagnosis of CNV over a mean follow-up of 8.0 years. Eyes with CNV that received treatment with an anti-vascular endothelial growth factor (VEGF) agent showed better mean BCVA compared with eyes that were not treated with an anti-VEGF agent (0.28 logMAR [Snellen equivalent, 20/38] vs. 0.62 logMAR [Snellen equivalent, 20/83]). Most eyes exhibited a hyperopic refractive error (78.7%), and 13 patients (6.1%) received a diagnosis of amblyopia. Among the 3 most common variants, p.(Ala243Val) was associated with a later age of onset, better age-adjusted BCVA, and less advanced Gass stages compared with p.(Arg218Cys) and p.(Arg218His). CONCLUSIONS: BVMD shows a wide spectrum of phenotypic variability. The disease is very slowly progressive, and the observed phenotype-genotype correlations allow for more accurate prognostication and counselling. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.276
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2024
Admission routes1
Has abstractyes

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