MétaCan
Menu
Back to cohort
Record W4319294125 · doi:10.2147/opth.s367089

Emerging Treatment Options for Geographic Atrophy (GA) Secondary to Age-Related Macular Degeneration

2023· review· en· W4319294125 on OpenAlexaff
Hannah Khan, Aamir Aziz, Humza Sulahria, Huma Khan, Abrahim Ahmed, Netan Choudhry, Raja Narayanan, Carl J. Danzig, Arshad M. Khanani

Bibliographic record

VenueClinical ophthalmology · 2023
Typereview
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsOctane (Canada)START ClinicUniversity of Toronto
Fundersnot available
KeywordsMacular degenerationGeographic atrophyMedicineClinical trialAtrophyOphthalmologyDiseaseBlindnessBioinformaticsLesionOncologyPathologyOptometry

Abstract

fetched live from OpenAlex

Abstract: Age-related macular degeneration (AMD) is characterized as a chronic, multifactorial disease and is the leading cause of irreversible blindness. Advanced AMD is classified as neovascular (wet) AMD and non-neovascular (dry) AMD. Dry AMD can progress to a more advanced form that manifests as geographic atrophy (GA), which significantly threatens vision, leading to progressive and irreversible loss of visual function. There are currently no approved therapeutics commercially available for GA patients. However, data from various clinical trials have demonstrated favorable results with significant reduction in GA lesion growth. Approaches to GA treatment vary from complement inhibitors to ocular gene therapy, some of which may delay disease progression, while others may reverse the disease. This review furthers the understanding of the pathophysiology of GA, as well as current clinical trial data on investigational therapeutics. Keywords: complement system, gene therapy, neuroprotective agents, personalized treatment, anti-inflammatory agents, intravitreal injection

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.205
GPT teacher head0.503
Teacher spread0.298 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations58
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueClinical ophthalmologySame topicRetinal Diseases and TreatmentsFrench-language works237,207