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Central retina vein occlusion: visual acuity correlate with focal electroretinogram, but not with optical coherence tomography

2011· article· en· W2007212576 on OpenAlexaff
Giulio Ruberto, Carmine Tinelli, Mirella Lizzano, P. Piccinini, F CALMA, Jessica Dispinseri

Bibliographic record

VenueActa Ophthalmologica · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsMedicineOphthalmologyCentral retinal vein occlusionVisual acuityOptical coherence tomographyRetinalElectroretinographyRetinaBranch retinal vein occlusionMacular edemaOptics

Abstract

fetched live from OpenAlex

Abstract Purpose central retina vein occlusion(CRVO) is a retinal vascular disorder associated with various degrees of retinal ischemia leading to macular oedema and visual acuity loss. The standard method to detect and measure the macular oedema is the Optical Coherence Tomography(OCT). The focal electroretinogram (FERG) is a part of the electroretinography that investigate functionally the macula.The aim of our study was to investigate the relationship between visual acuity, morphologic aspects and functional results in CRVO. Methods we examined 24 eyes affected by CRVO. All the patients had complete survey comprehending ETDRS visual acuity(VA), FERG, OCT. The FERG was performed via ERG dome, using a background light of 300 cd/m2 and a led stimulus alternating at 5,1 hz. The OCT values of macular volume and thickness, the a and b wave values of latency and amplitude were collected and analyzed. The results were matched with 19 eyes not affected of the same sample and with 20 eyes of healthy subjects. Multiple statistical relationship analysis of the r and p were done by mean of Kruskal‐Wallis test. The sensitivity and specificity were analyzed with Roc curve. Results we do not found correlations between VA and OCT macular volume and thickness. A significant correlation with VA was found in a and b FERG amplitudes between the CRVO group, healthy subjects and the healthy eyes of CRVO group and also between the healthy eyes of CRVO and healthy subjects.Significant sensitivity and specificity (72.1 and 80 respectively) were found in Roc curve Conclusion in our study functional alterations of the FERG correlate and probably precede VA loss

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score1.000

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 head0.238
Teacher spread0.223 · 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 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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Citations0
Published2011
Admission routes1
Has abstractyes

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