Literature DB >> 31668742

Comparison of 1-field, 2-fields, and 3-fields fundus photography for detection and grading of diabetic retinopathy.

Jessica C Lee1, Lilian Nguyen2, Linda S Hynan3, Preston H Blomquist4.   

Abstract

AIM: To evaluate the sensitivity and specificity of 1-, 2-, and 3-fields, nonmydriatic (NM), 45° color photography compared with mydriatic ophthalmoscopy for detection of diabetic retinopathy (DR).
METHODS: Masked, comparative case series was performed utilizing a group of 128 diabetic patients (256 eyes) with various stages of DR who underwent both 3-fields NM color photography and ophthalmologic examination. In a blinded manner, the same optometrist who read the original 3-fields images for a patient read the 1- and 2-fields photographs on separate dates later.
RESULTS: The sensitivity and specificity of digital retinal photography compared with dilated ophthalmoscopy were, respectively: 88% and 76% for 1-field; 94% and 69% for 2-fields; and 100% and 79% for 3-fields. The proportion of agreement between fundus photography reading and exam DR diagnosis were 58% for 1-field, 58% for 2-fields, and 77% for 3-fields. Kappa and Cramer's V statistics for 1-, 2-, and 3-fields were 0.55 and 0.60, 0.52 and 0.57, and 0.72 and 0.74, respectively. Three-fields measurement of DR was most similar to the dilated ophthalmological exam overall and across all DR severity levels.
CONCLUSIONS: Compared to 1- and 2-fields fundus photography, 3-fields is superior for detecting vision-threatening DR. One- and 2-fields have reasonable sensitivity for DR screening.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Diabetic retinopathy; Fundus photography; Screening

Mesh:

Year:  2019        PMID: 31668742     DOI: 10.1016/j.jdiacomp.2019.107441

Source DB:  PubMed          Journal:  J Diabetes Complications        ISSN: 1056-8727            Impact factor:   2.852


  4 in total

1.  A new handheld fundus camera combined with visual artificial intelligence facilitates diabetic retinopathy screening.

Authors:  Shang Ruan; Yang Liu; Wei-Ting Hu; Hui-Xun Jia; Shan-Shan Wang; Min-Lu Song; Meng-Xi Shen; Da-Wei Luo; Tao Ye; Feng-Hua Wang
Journal:  Int J Ophthalmol       Date:  2022-04-18       Impact factor: 1.779

2.  The Cost-Effectiveness of a Telemedicine Screening Program for Diabetic Retinopathy in New York City.

Authors:  Hasan Muqri; Anurag Shrivastava; Rakin Muhtadi; Roy S Chuck; Umar K Mian
Journal:  Clin Ophthalmol       Date:  2022-05-17

3.  Cross-Sectional Analysis of the Involvement of Interleukin-17A in Diabetic Retinopathy in Elderly Individuals with Type 2 Diabetes Mellitus.

Authors:  Fuqiang Liu; Feng Han; Xiaoli Liu; Lina Yang; Caixia Jiang; Chen Cui; Fang Yuan; Xin Zhang; Lei Gong; Xinguo Hou; Yuan Liu; Li Chen
Journal:  Diabetes Metab Syndr Obes       Date:  2021-10-09       Impact factor: 3.168

4.  Real-world outcomes of a clinical decision support system for diabetic retinopathy in Spain.

Authors:  Pedro Romero-Aroca; Raquel Verges; Najlaa Maarof; Aida Vallas-Mateu; Alex Latorre; Antonio Moreno-Ribas; Ramon Sagarra-Alamo; Josep Basora-Gallisa; Julian Cristiano; Marc Baget-Bernaldiz
Journal:  BMJ Open Ophthalmol       Date:  2022-03-28
  4 in total

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