Evidence map›Paper›PMID 39760640›Full record

ReviewExpert review of medical devices2025

Amblyopia screening: the current state and opportunities for optimization.

Jonathan Morse, Julius T Oatts

Abstract readReview
In one paragraph

Review in Expert review of medical devices, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

2 authors.

Jonathan MorseUniversity of Michigan School of Medicine, Ann Arbor, MI, USA.
Julius T OattsDivision of Ophthalmology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Funding

Community-based amblyopia screening using a novel deviceK23EY034893 · NEI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Julius Oatts · 2023 to 2026
$1.0M
NEI NIH HHS K23 EY034893
6 · The paper itself

Abstract

introductionAmblyopia, the leading cause of monocular childhood vision loss, affects millions and is projected to increase. Early detection and treatment are crucial for preventing vision impairment. AREAS COVERED: This commentary reviews the current state and opportunities for improvement in amblyopia screening strategy and technology focused primarily within the United States. A review of current guidelines from organizations and a literature review of innovations between 1999 and 2024 informed this commentary. Organizations recommend routine vision screening for children, starting in infancy and continuing through adolescence. However, the variations in screening devices, components, timelines, and requirements leave room for improving outcomes. An exploration of instrument-based screening which has emerged as an alternative to traditional optotype testing will be investigated, and the risks of these instruments with high sensitivity and varying specificity will be acknowledged. Finally, new approaches to directly identify amblyopia and search for innovative biomarkers that indicate amblyopia risk or amblyopia itself will be discussed. EXPERT OPINION: Improving the treatment of amblyopia necessitates the reimagination of current practices in connecting patients to care. Technologies that incorporate novel diagnostic approaches, like the consideration of specific biomarkers or the use of artificial intelligence, hold promise to identify cases of amblyopia rather than its risk factors.

Indexed as

AmblyopiaVision ScreeningChildHumansAmblyopiaartificial intelligencepediatric ophthalmologyvirtual realityvision screening

Identifiers

PMID39760640
PMCPMC11750595

What OpenQuestion holds

Textmetadata
LicenceTDM
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.