Evidence map›Paper›PMID 34067442›Full record

ReviewJournal of personalized medicine2021

Indicators of Visual Prognosis in Diabetic Macular Oedema.

Sagnik Sen, Kim Ramasamy, Sobha Sivaprasad

Open access · goldAbstract readReview
In one paragraph

Review in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
  2. Article
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  5. Review
  6. Article
  7. Article
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  11. Review
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  13. Article
  14. Age-Related Macular Degeneration and Diabetic Retinopathy.Journal of personalized medicine · 2022
    Article
  15. 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

3 authors at 2 institutions in 2 countries.

Sagnik SenDepartment of Retina and Vitreous Services, Aravind Eye Hospital, Madurai 625020, India.ORCID 0000-0001-5835-5371
Kim RamasamyDepartment of Retina and Vitreous Services, Aravind Eye Hospital, Madurai 625020, India.
Sobha SivaprasadNIHR Moorfields Biomedical Research Centre, Moorfields Eye Hospital, 162, City Road, London EC1V 2PD, UK.ORCID 0000-0001-8952-0659
Aravind Eye Hospital · INNIHR Moorfields Biomedical Research Centre · GB

Funding

Global Challenges Research Fund MR/P207881/1Medical Research Council MR/P027881/1
6 · The paper itself

Abstract

Diabetic macular oedema (DMO) is an important cause of moderate vision loss in people with diabetes. Advances in imaging technology have shown that a significant proportion of patients with DMO respond sub-optimally to existing treatment options. Identifying associations and predictors of response before treatment is initiated may help in explaining visual prognosis to patients and aid the development of personalized treatment strategies. Imaging features, such as central subfoveal thickness, photoreceptor integrity, disorganization of retinal inner layers, choroidal changes, and macular perfusion, have been reported to be prognostic factors of visual acuity (VA) in DMO. In this review we evaluated each risk factor to understand their relative importance in visual prognostication of DMO eyes post-treatment. Although individually, some of these factors may not be significant predictors, in combination they may form phenotypes that can inform visual prognosis. Stratification based on these phenotypes needs to be developed to progress to personalized medicine for DMO.

Indexed as

diabetic macular oedemadiabetic retinopathyindicatorspersonalized medicinevisual prognosis

Identifiers

PMID34067442
PMCPMC8224579
OpenAlexW3165285377

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.