Evidence map›Paper›PMID 33735069›Full record

ReviewThe Lancet. Digital health2021

A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability.

Saad M Khan, Xiaoxuan Liu, Siddharth Nath, Edward Korot, Livia Faes, Siegfried K Wagner, Pearse A Keane, Neil J Sebire, Matthew J Burton, Alastair K Denniston

Erratum issuedAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in The Lancet. Digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 161 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
161citing papers in PubMed, 5 pooled it
–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

161 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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101 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Saad M KhanAcademic Unit of Ophthalmology, Institute of Inflammation & Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK.
Xiaoxuan LiuAcademic Unit of Ophthalmology, Institute of Inflammation & Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; Ophthalmology Department, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Health Data Research UK, London, UK; Centre for Regulatory Science and Innovation, Birmingham Health Partners, Birmingham, UK.
Siddharth NathDepartment of Ophthalmology and Visual Sciences, McGill University, Montreal, QC, Canada.
Edward KorotMoorfields Eye Hospital NHS Foundation Trust, London, UK; Stanford University Byers Eye Institute, Palo Alto, CA, USA.
Livia FaesMoorfields Eye Hospital NHS Foundation Trust, London, UK; Eye Clinic, Cantonal Hospital of Lucerne, Lucerne, Switzerland.
Siegfried K WagnerNational Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
Pearse A KeaneNational Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
Neil J SebireHealth Data Research UK, London, UK.
Matthew J BurtonInternational Centre for Eye Health, Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK.
Alastair K DennistonAcademic Unit of Ophthalmology, Institute of Inflammation & Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; Ophthalmology Department, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Health Data Research UK, London, UK; Centre for Regulatory Science and Innovation, Birmingham Health Partners, Birmingham, UK; National Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK. Electronic address: a.denniston@bham.ac.uk.

Funding

Department of HealthMedical Research Council MC_PC_19005Medical Research Council MR/T019050/1Wellcome Trust 200141Wellcome Trust 200141/Z/15/ZWellcome Trust 207472Wellcome Trust 207472/Z/17/Z
6 · The paper itself

Abstract

Health data that are publicly available are valuable resources for digital health research. Several public datasets containing ophthalmological imaging have been frequently used in machine learning research; however, the total number of datasets containing ophthalmological health information and their respective content is unclear. This Review aimed to identify all publicly available ophthalmological imaging datasets, detail their accessibility, describe which diseases and populations are represented, and report on the completeness of the associated metadata. With the use of MEDLINE, Google's search engine, and Google Dataset Search, we identified 94 open access datasets containing 507 724 images and 125 videos from 122 364 patients. Most datasets originated from Asia, North America, and Europe. Disease populations were unevenly represented, with glaucoma, diabetic retinopathy, and age-related macular degeneration disproportionately overrepresented in comparison with other eye diseases. The reporting of basic demographic characteristics such as age, sex, and ethnicity was poor, even at the aggregate level. This Review provides greater visibility for ophthalmological datasets that are publicly available as powerful resources for research. Our paper also exposes an increasing divide in the representation of different population and disease groups in health data repositories. The improved reporting of metadata would enable researchers to access the most appropriate datasets for their needs and maximise the potential of such resources.

Indexed as

Databases, FactualDatasets as TopicOphthalmologyDiagnostic ImagingEye DiseasesHumansMetadata

Identifiers

PMID33735069
PMCPMC7618278

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.