Evidence map›Paper›PMID 27402242›Full record

Trial reportJournal of diabetes science and technology2017

Screening for Diabetic Retinopathy Using a Portable, Noncontact, Nonmydriatic Handheld Retinal Camera.

Wenlan Zhang, Peter Nicholas, Stefanie Gail Schuman, Michael John Allingham, Ambar Faridi, Tushar Suthar, Scott William Cousins, Sasapin Grace Prakalapakorn

Open access · bronzeAbstract readClinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of diabetes science and technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
3.7field-weighted citation impact, top 8% 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

29 citing papers in PubMed, 47 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. A Systematic Review of Digital Ophthalmoscopes in Medicine.Clinical ophthalmology (Auckland, N.Z.) · 2023
    Review
  11. Article
  12. Evaluation of a New Neural Network Classifier for Diabetic Retinopathy.Journal of diabetes science and technology · 2022
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Article
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

8 authors at 1 institution in 1 country.

Wenlan Zhang1 Duke University, Department of Ophthalmology, Durham, NC, USA.
Peter Nicholas1 Duke University, Department of Ophthalmology, Durham, NC, USA.
Stefanie Gail Schuman1 Duke University, Department of Ophthalmology, Durham, NC, USA.
Michael John Allingham1 Duke University, Department of Ophthalmology, Durham, NC, USA.
Ambar Faridi1 Duke University, Department of Ophthalmology, Durham, NC, USA.
Tushar Suthar1 Duke University, Department of Ophthalmology, Durham, NC, USA.
Scott William Cousins1 Duke University, Department of Ophthalmology, Durham, NC, USA.
Sasapin Grace Prakalapakorn1 Duke University, Department of Ophthalmology, Durham, NC, USA.
Duke University · US

Funding

Evaluating a non-contact fundus camera for retinopathy of prematurity screeningK23EY024268 · NEI · DUKE UNIVERSITY · PI PRAKALAPAKORN, SASAPIN GRACE · 2014 to 2016
$638k
NEI NIH HHS K23 EY024268
6 · The paper itself

Abstract

backgroundDiabetic retinopathy (DR) is a leading cause of low vision and blindness. We evaluated the feasibility of using a handheld, noncontact digital retinal camera, Pictor, to obtain retinal images in dilated and undilated eyes for DR screening. We also evaluated the accuracy of ophthalmologists with different levels of training/experience in grading these images to identify eyes with vision-threatening DR.

methodsA prospective study of diabetic adults scheduled to have dilated eye exams at Duke Eye Center from January to May 2014 was conducted. An imager acquired retinal images pre- and postdilation with Pictor and selected 1 pre- and 1 postdilation image per eye. Five masked ophthalmologists graded images for gradability (based on image focus and centration) and the presence of no, mild, moderate, or severe nonproliferative DR (NPDR) or proliferative DR (PDR). Referable disease was defined as moderate or severe NPDR or PDR on image grading. We evaluated feasibility based on the graders' evaluation of image gradability. We evaluated accuracy of identifying vision-threatening disease (severe NPDR or PDR documented on dilated clinical examination) based on the graders' sensitivity and specificity of grading referable disease.

resultsImages were gradable in 86-94% of predilation and 94-97% of postdilation photos. Compared to the dilated clinical exam, overall sensitivity for identifying vision-threatening DR was 64-88% and specificity was 71-90%.

conclusionsPictor can capture retinal images of sufficient quality to screen for DR with and without dilation. Single retinal images obtained using Pictor can identify eyes with vision-threatening DR with high sensitivity and acceptable specificity compared to clinical exam.

Indexed as

AdultDiabetic RetinopathyDiagnostic ImagingFemaleHumansImage Interpretation, Computer-AssistedMaleMass ScreeningMiddle AgedOphthalmologyPhotographyRetinadiabetic retinopathyhandheld cameraportable imagingretinascreeningtelemedicine

Identifiers

PMID27402242
PMCPMC5375071
OpenAlexW2473828516

What OpenQuestion holds

Textmetadata
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.