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Record W3068863914 · doi:10.1177/2474126420941713

Genetics and Age-Related Eye Disease Study Formulation Interaction in Neovascular Age-Related Macular Degeneration

2020· article· en· W3068863914 on OpenAlexaff
Stephen R. Kaufman, Pradeepa Yoganathan, Kent W. Small, Deepam Rusia, Sophia I. Pachydaki, Stephen M. Conti, Robert E. Wenz, Mark Gersman, Fadi Shaya, Rafal Kustra

Bibliographic record

VenueJournal of VitreoRetinal Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMacular degenerationOdds ratioMedicineLogistic regressionGenotypeRisk factorOphthalmologyPopulationAlleleEpidemiologyInternal medicineDemographyGeneticsBiology

Abstract

fetched live from OpenAlex

Purpose: This work aims to determine whether previously defined genotype risk groups interact with Age-Related Eye Disease Study formulation (AREDS-F) use in progression to neovascular age-related macular degeneration (nvAMD). Methods: We conducted a case-only study of 265 nvAMD patients. Patients were anonymously genotyped at the complement factor H and age-related maculopathy susceptibility 2 loci and segregated into genotype groups (GTGs) defined by specific combinations of risk alleles. Physicians, who were blind to patients’ GTGs, obtained patients’ AREDS-F use history. The facility performing genetic analysis was blind to the AREDS-F use history. We used logistic analysis to estimate the interaction coefficient between AREDS-F use and GTG 2 vs GTG 3 in a general-population model. Results: The odds ratio of numbers of patients reporting prior AREDS-F use to nonuse for GTG 2 vs GTG 3 was 4.18 ( P = .001). Logistic regression, correcting for nongenetic risk factors, gave an estimate of the β for interaction of AREDS-F with genotype of 1.57 ( P = .001). This estimates a corrected odds ratio associated with the effect of interaction of 4.81 between those in GTG 2 compared with those in GTG 3. Conclusions: Our data indicate an interaction between GTGs and AREDS-F use that is consistent in size and direction with previously published reports, which had found that using AREDS-F supplements significantly increases the risk of nvAMD for some users and significantly protects other users.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.018
GPT teacher head0.299
Teacher spread0.281 · 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 designObservational
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

Citations1
Published2020
Admission routes1
Has abstractyes

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