Evidence map›Paper›PMID 34234636›Full record

ArticleFrontiers in neuroscience2021

Evaluating the Performance of qVFM in Mapping the Visual Field of Simulated Observers With Eye Diseases.

Pengjing Xu, Luis Andres Lesmes, Deyue Yu, Zhong-Lin Lu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 93% of its field
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

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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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 3 institutions in 2 countries.

Pengjing XuCollege of Optometry, The Ohio State University, Columbus, OH, United States.
Luis Andres LesmesAdaptive Sensory Technology, Inc., San Diego, CA, United States.
Deyue YuCollege of Optometry, The Ohio State University, Columbus, OH, United States.
Zhong-Lin LuDivision of Arts and Sciences, NYU Shanghai, Shanghai, China.
The Ohio State University · USNew York University Shanghai · CNSensory (United States) · US

Funding

Efficient Assessment of Visual Deficits and Rehabilitation Methods in AmblyopiaR01EY021553 · NEI · OHIO STATE UNIVERSITY · PI LU, ZHONG-LIN · 2012 to 2016
$2.1M
Efficient Assessment of Visual Deficits in Low VisionR01EY025658 · NEI · OHIO STATE UNIVERSITY · PI YU, DEYUE · 2016 to 2020
$1.9M
NEI NIH HHS R01 EY021553NEI NIH HHS R01 EY025658
6 · The paper itself

Abstract

purposeRecently, we developed a novel active learning framework, qVFM, to map visual functions in the visual field. The method has been implemented and validated in measuring light sensitivity and contrast sensitivity visual field maps (VFMs) of normal observers. In this study, we evaluated the performance of the qVFM method in mapping the light sensitivity VFM of simulated patients with peripheral scotoma, glaucoma, age-related macular degeneration (AMD), and cataract.

methodsFor each simulated patient, we sampled 100 locations (60 × 60 degrees) of the visual field and compared the performance of the qVFM method with a procedure that tests each location independently (the qYN method) in a cued Yes/No task. Two different switch modules, the distribution sampling method (DSM) and parameter delivering method (PDM), were implemented in the qVFM method. Simulated runs of 1,200 trials were used to compare the accuracy and precision of the qVFM-DSM, qVFM-PDM and qYN methods.

resultsThe qVFM method with both switch modules can provide accurate, precise, and efficient assessments of the light sensitivity VFM for the simulated patients, with the qVFM-PDM method better at detecting VFM deficits in the simulated glaucoma.

conclusionsThe qVFM method can be used to characterize residual vision of simulated ophthalmic patients. The study sets the stage for further investigation with real patients and potential translation of the method into clinical practice.

Indexed as

active learningage-related macular degenerationBayesian adaptive testingcataractglaucomaperimetryscotomavisual-field map

Identifiers

PMID34234636
PMCPMC8255634
OpenAlexW3176098985

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.