Evidence map›Paper›PMID 36583912›Full record

ArticleTranslational vision science & technology2022

Development and Validation of a Digital (Peek) Near Visual Acuity Test for Clinical Practice, Community-Based Survey, and Research.

Marzieh Katibeh, Sandip Das Sanyam, Elanor Watts, Nigel M Bolster, Reena Yadav, Abhishek Roshan, Sailesh K Mishra, Matthew J Burton, Andrew Bastawrous

Open access · goldAbstract read
In one paragraph

Article in Translational vision science & technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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

9 authors at 2 institutions in 2 countries.

Marzieh KatibehPeek Vision, Berkhamsted, UK.
Sandip Das SanyamSagarmatha Choudhary Eye Hospital, Lahan, Nepal.
Elanor WattsPeek Vision, Berkhamsted, UK.
Nigel M BolsterPeek Vision, Berkhamsted, UK.
Reena YadavSagarmatha Choudhary Eye Hospital, Lahan, Nepal.
Abhishek RoshanSagarmatha Choudhary Eye Hospital, Lahan, Nepal.
Sailesh K MishraNepal Netra Jyoti Sangh, Kathmandu, Nepal.
Matthew J BurtonInternational Centre for Eye Health, Clinical Research Department, London School of Hygiene and Tropical Medicine, London, UK.
Andrew BastawrousPeek Vision, Berkhamsted, UK.
London School of Hygiene & Tropical Medicine · GBAarhus University Hospital · DK

Funding

Department of HealthWellcome Trust 207472/Z/17/ZWellcome Trust 215633/Z/19/Z
6 · The paper itself

Abstract

Purpose: Unaddressed near vision impairment (NVI) affects more than 500 million people. Testing near vision is necessary to identify those in need of services. To make such testing readily accessible, we have developed and validated a new smartphone-based near visual acuity (NVA) test: Peek Near Vision (PeekNV). Methods: Two forms of the PeekNV test were developed: (1) quantitative measurement of NVA, and (2) binary screening test for presence or absence of NVI. The validity study was carried out with 483 participants in Sagarmatha Choudhary Eye Hospital, Lahan, Nepal, using a conventional Tumbling "E" Near Point Vision Chart as the reference standard. Bland-Altman limits of agreement (LoA) were used to evaluate test agreement and test-retest repeatability. NVI screening was assessed using Cohen's kappa coefficient, sensitivity, and specificity. Results: The mean difference between PeekNV and chart NVA results was 0.008 logMAR units (95% confidence interval [CI], -0.005 to 0.021) in right eye data, and the 95% LoA between PeekNV and chart testing were within 0.235 and -0.218 logMAR. As a NVI screening tool, the overall agreement between tests was 92.9% (κ = 0.85). The positive predictive value of PeekNV was 93.2% (95% CI, 89.6% to 96.9%), and the negative predictive value 92.7% (95% CI, 88.9% to 96.4%). PeekNV had a faster NVI screening time (11.6 seconds; 95% CI, 10.5 to 12.6) than the chart (14.9 seconds; 95% CI, 13.5 to 16.2; P < 0.001). Conclusions: The PeekNV smartphone-based test produces rapid NVA test results, comparable to those of an accepted NV test. Translational Relevance: PeekNV is a validated, reliable option for NV testing for use with smartphones or digital devices.

Indexed as

Vision TestsHumansVisual Acuity

Identifiers

PMID36583912
PMCPMC9807182
OpenAlexW4313410143

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.