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Record W3136527718 · doi:10.1016/j.ajo.2021.03.004

KCNV2-Associated Retinopathy: Detailed Retinal Phenotype and Structural Endpoints—KCNV2 Study Group Report 2

2021· article· en· W3136527718 on OpenAlexaff
Michalis Georgiou, Kaoru Fujinami, Ajoy Vincent, Fadi Nasser, Samer Khateb, Mauricio E. Vargas, Alberta A. H. J. Thiadens, Emanuel R. de Carvalho, Xuan‐Thanh‐An Nguyen, Thales A. C. de Guimarães, Anthony G. Robson, Omar A. Mahroo, Nikolas Pontikos, Gavin Arno, Yu Fujinami‐Yokokawa, Shaun M. Leo, Xiao Liu, Kazushige Tsunoda, Takaaki Hayashi, Belén Jimenez‐Rolando, María Inmaculada Martín-Mérida, Almudena Ávila‐Fernández, Ester Carreño, Blanca Garcı́a-Sandoval, Carmen Ayuso, Dror Sharon, Susanne Kohl, Rachel M. Huckfeldt, Camiel J.F. Boon, Eyal Banin, Mark E. Pennesi, Bernd Wissinger, Andrew R. Webster, Elise Héon, Arif O. Khan, Eberhart Zrenner, Michel Michaelides

Bibliographic record

VenueAmerican Journal of Ophthalmology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersJanssen PharmaceuticalsNational Eye InstituteInstituto de Salud Carlos IIIUCL Institute of Ophthalmology, University College LondonProQR TherapeuticsNovartisAlimera SciencesMoorfields Eye Hospital NHS Foundation TrustMoorfields Eye CharityAstellas PharmaNational Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of OphthalmologyDeutsche ForschungsgemeinschaftWellcome TrustTistou and Charlotte Kerstan StiftungA.G. Leventis FoundationRetina UKAlexander S. Onassis Public Benefit FoundationSpark TherapeuticsAbbVieFight for Sight UKBundesministerium für Bildung und ForschungNational Institute for Health and Care ResearchFundación Ramón ArecesBiogenResearch to Prevent BlindnessNational Institutes of HealthFoundation Fighting BlindnessNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
KeywordsRetinalPhenotypeOphthalmologyMedicineRetinopathyGeneticsBiologyEndocrinologyGene

Abstract

fetched live from OpenAlex

•KCNV2-associated retinopathy is a slowly progressive disease with early retinal changes, which are predominantly symmetric between eyes.•Disease course can be unpredictable and may severely affect children and young adults.•Findings suggest a potential window for intervention until 40 years of age, albeit with variability between patients due to macular atrophy. PurposeTo describe the detailed retinal phenotype of KCNV2-associated retinopathy.Study designMulticenter international retrospective case series.MethodsReview of retinal imaging including fundus autofluorescence (FAF) and optical coherence tomography (OCT), including qualitative and quantitative analyses.ResultsThree distinct macular FAF features were identified: (1) centrally increased signal (n = 35, 41.7%), (2) decreased autofluorescence (n = 27, 31.1%), and (3) ring of increased signal (n = 37, 44.0%). Five distinct FAF groups were identified based on combinations of those features, with 23.5% of patients changing the FAF group over a mean (range) follow-up of 5.9 years (1.9-13.1 years). Qualitative assessment was performed by grading OCT into 5 grades: (1) continuous ellipsoid zone (EZ) (20.5%); (2) EZ disruption (26.1%); (3) EZ absence, without optical gap and with preserved retinal pigment epithelium complex (21.6%); (4) loss of EZ and a hyporeflective zone at the foveola (6.8%); and (5) outer retina and retinal pigment epithelium complex loss (25.0%). Eighty-six patients had scans available from both eyes, with 83 (96.5%) having the same grade in both eyes, and 36.1% changed OCT grade over a mean follow-up of 5.5 years. The annual rate of outer nuclear layer thickness change was similar for right and left eyes.ConclusionsKCNV2-associated retinopathy is a slowly progressive disease with early retinal changes, which are predominantly symmetric between eyes. The identification of a single OCT or FAF measurement as an endpoint to determine progression that applies to all patients may be challenging, although outer nuclear layer thickness is a potential biomarker. Findings suggest a potential window for intervention until 40 years of age. To describe the detailed retinal phenotype of KCNV2-associated retinopathy. Multicenter international retrospective case series. Review of retinal imaging including fundus autofluorescence (FAF) and optical coherence tomography (OCT), including qualitative and quantitative analyses. Three distinct macular FAF features were identified: (1) centrally increased signal (n = 35, 41.7%), (2) decreased autofluorescence (n = 27, 31.1%), and (3) ring of increased signal (n = 37, 44.0%). Five distinct FAF groups were identified based on combinations of those features, with 23.5% of patients changing the FAF group over a mean (range) follow-up of 5.9 years (1.9-13.1 years). Qualitative assessment was performed by grading OCT into 5 grades: (1) continuous ellipsoid zone (EZ) (20.5%); (2) EZ disruption (26.1%); (3) EZ absence, without optical gap and with preserved retinal pigment epithelium complex (21.6%); (4) loss of EZ and a hyporeflective zone at the foveola (6.8%); and (5) outer retina and retinal pigment epithelium complex loss (25.0%). Eighty-six patients had scans available from both eyes, with 83 (96.5%) having the same grade in both eyes, and 36.1% changed OCT grade over a mean follow-up of 5.5 years. The annual rate of outer nuclear layer thickness change was similar for right and left eyes. KCNV2-associated retinopathy is a slowly progressive disease with early retinal changes, which are predominantly symmetric between eyes. The identification of a single OCT or FAF measurement as an endpoint to determine progression that applies to all patients may be challenging, although outer nuclear layer thickness is a potential biomarker. Findings suggest a potential window for intervention until 40 years of age.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.055
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.008
GPT teacher head0.268
Teacher spread0.259 · 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".

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Citations28
Published2021
Admission routes1
Has abstractyes

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