Evidence map›Paper›PMID 35177916›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2022

Optical Coherence Tomography Angiography Biomarkers Predict Anatomical Response to Bevacizumab in Diabetic Macular Edema.

Ayman G Elnahry, Alia M Noureldine, Ahmed A Abdel-Kader, Osama A Sorour, David J Ramsey

Abstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2022. 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
–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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. 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

5 authors.

Ayman G ElnahryDepartment of Ophthalmology, Faculty of Medicine, Cairo University, Cairo, Egypt.ORCID 0000-0001-5148-316X
Alia M NoureldineDepartment of Ophthalmology, Faculty of Medicine, Cairo University, Cairo, Egypt.
Ahmed A Abdel-KaderDepartment of Ophthalmology, Faculty of Medicine, Cairo University, Cairo, Egypt.
Osama A SorourDepartment of Ophthalmology, Faculty of Medicine, Tanta University, Tanta, Egypt.
David J RamseyDivision of Ophthalmology, Lahey Hospital & Medical Center, Tufts University School of Medicine, Boston, MA, USA.ORCID 0000-0002-5504-812X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo identify biomarkers that may predict an early anatomical response to the treatment of diabetic macular edema (DME) with intravitreal bevacizumab (IVB) by means of optical coherence tomography angiography (OCTA).

methodsThis study is a retrospective study of treatment-naïve patients with DME who underwent 6 × 6 mm OCTA imaging of the macula at baseline and after three monthly IVB injections. Thirty-six eyes of 23 patients were included. Eyes that demonstrated evidence of an early anatomical response, consisting of a >10% decrease in central macular thickness (CMT) (n = 18), were compared with those eyes that failed to show such an improvement (n = 18).

resultsAt baseline, early-response eyes had worse starting best-corrected visual acuity (BCVA, LogMAR 0.84 ± 0.41 versus LogMAR 0.51 ± 0.15,

conclusionProjection-resolved OCTA may be useful in predicting an early anatomical response of DME to treatment with IVB.

Indexed as

anti-VEGF agentsbevacizumabbiomarkersdiabetic macular edemamacular ischemiamacular perfusionoptical coherence tomography angiography

Identifiers

PMID35177916
PMCPMC8843414

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.