Evidence map›Paper›PMID 37367722›Full record

ArticleTranslational vision science & technology2023

High Variation in Inner Retinal Reflectivity Predicts Poor Visual Outcome in Patients With Central Retinal Vein Occlusion: SCORE2 Report 21.

Nitish Mehta, Sachi Patil, Vikram Modi, Rachel Vardi, Kevin Liu, Rishi P Singh, David Sarraf, Neal L Oden, Paul C VanVeldhuisen, Ingrid U Scott and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational vision science & technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Nitish MehtaDepartment of Ophthalmology, NYU Langone Health, New York University, New York, NY, USA.
Sachi PatilDepartment of Ophthalmology, NYU Langone Health, New York University, New York, NY, USA.
Vikram ModiDepartment of Ophthalmology, NYU Langone Health, New York University, New York, NY, USA.
Rachel VardiDepartment of Ophthalmology, NYU Langone Health, New York University, New York, NY, USA.
Kevin LiuDepartment of Ophthalmology, NYU Langone Health, New York University, New York, NY, USA.
Rishi P SinghCenter for Ophthalmic Bioinformatics, Cole Eye Institute, The Cleveland Clinic, Cleveland, OH, USA.
David SarrafDepartment of Ophthalmology, University of California - Los Angeles, Los Angeles, CA, USA.
Neal L OdenThe Emmes Company, LLC, Rockville, MD, USA.
Paul C VanVeldhuisenThe Emmes Company, LLC, Rockville, MD, USA.
Ingrid U ScottDepartments of Ophthalmology and Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
Michael S IpDoheny Eye Institute, University of California, Los Angeles, CA, USA.
Barbara A BlodiUniversity of Wisconsin Fundus Photograph Reading Center, Madison, WI, USA.
Yasha ModiDepartment of Ophthalmology, NYU Langone Health, New York University, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To assess the association of a novel spectral domain optical coherence tomography biomarker with 6-month visual acuity in in the Study of COmparative Treatments for REtinal Vein Occlusion 2. Methods: Spectral domain optical coherence tomography volume scans were evaluated for inner retinal hyperreflectivity, quantified by optical intensity ratio (OIR) and OIR variation. Baseline visual acuity letter score (VALS), baseline OCT biomarkers, and month 1 OIR were correlated with VALS at month 6. Regression trees, a machine learning technique yielding readily interpretable models, were used to assess for variable interaction. Results: Only baseline VALS correlated positively with month 6 VALS in multivariate regression. Regression trees detected a novel functional and anatomical interaction in a subgroup. Among patients with a baseline VALS worse than 43, those with an OIR variation at month 1 of more than 0.09 had a mean of 13 fewer letters of vision at 6 months compared with patients with an OIR variation of 0.09 or less. Conclusions: Baseline VALS was the strongest predictor of month 6 VALS. Regression tree analysis detected an interaction effect, in which higher OIR variation at month 1 predicted worse 6-month VALS in patients with low VALS at baseline. OIR variation may serve as a predictor for poor visual outcome despite treatment of macular edema secondary to retinal vein occlusion in patients with poor vision at baseline. Translational Relevance: Pixel heterogeneity in three-dimensional OCT data may serve as measure of disruption of the retinal laminations, and this factor may carry visually prognostic value.

Indexed as

Retinal Vein OcclusionAngiogenesis InhibitorsHumansIntravitreal InjectionsRetinaValsartanAngiogenesis InhibitorsValsartan

Identifiers

PMID37367722
PMCPMC10309158

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.