Literature DB >> 25427567

Screening for Diabetic Retinopathy in the Central Region of Portugal. Added Value of Automated 'Disease/No Disease' Grading.

Luisa Ribeiro1, Carlos Manta Oliveira, Catarina Neves, João Diogo Ramos, Hélder Ferreira, José Cunha-Vaz.   

Abstract

Purpose: To describe the procedures of a nonmydriatic diabetic retinopathy (DR) screening program in the Central Region of Portugal and the added value of the introduction of an automated disease/no disease analysis.
Methods: The images from the DR screening program are analyzed in a central reading center using first an automated disease/no disease analysis followed by human grading of the disease cases. The grading scale used is as follows: R0 - no retinopathy, RL - nonproliferative DR, M - maculopathy, RP - proliferative DR and NC - not classifiable.
Results: Since the introduction of automated analysis in July 2011, a total of 89,626 eyes (45,148 patients) were screened with the following distribution: R0 - 71.5%, RL - 22.7%, M - 2.2%, RP - 0.1% and NC - 3.5%. The implemented automated system showed the potential for human grading burden reduction of 48.42%. Conclusions: Screening for DR using automated analysis allied to a simplified grading scale identifies DR vision-threatening complications well while decreasing human burden.
© 2014 S. Karger AG, Basel.

Entities:  

Year:  2014        PMID: 25427567     DOI: 10.1159/000368426

Source DB:  PubMed          Journal:  Ophthalmologica        ISSN: 0030-3755            Impact factor:   3.250


  7 in total

1.  Construction of Predictive Model for Type 2 Diabetic Retinopathy Based on Extreme Learning Machine.

Authors:  Lei Liu; Mengmeng Wang; Guocheng Li; Qi Wang
Journal:  Diabetes Metab Syndr Obes       Date:  2022-08-24       Impact factor: 3.249

2.  Assessment of Training Outcomes of Nurse Readers for Diabetic Retinopathy Telescreening: Validation Study.

Authors:  Marie Carole Boucher; Michael Trong Duc Nguyen; Jenny Qian
Journal:  JMIR Diabetes       Date:  2020-04-07

Review 3.  Digital innovations for retinal care in diabetic retinopathy.

Authors:  Stela Vujosevic; Celeste Limoli; Livio Luzi; Paolo Nucci
Journal:  Acta Diabetol       Date:  2022-08-12       Impact factor: 4.087

Review 4.  The Role of Telemedicine, In-Home Testing and Artificial Intelligence to Alleviate an Increasingly Burdened Healthcare System: Diabetic Retinopathy.

Authors:  Janusz Pieczynski; Patrycja Kuklo; Andrzej Grzybowski
Journal:  Ophthalmol Ther       Date:  2021-06-22

Review 5.  Automated detection of diabetic retinopathy in retinal images.

Authors:  Carmen Valverde; Maria Garcia; Roberto Hornero; Maria I Lopez-Galvez
Journal:  Indian J Ophthalmol       Date:  2016-01       Impact factor: 1.848

6.  Andalusian program for early detection of diabetic retinopathy: implementation and 15-year follow-up of a population-based screening program in Andalusia, Southern Spain.

Authors:  Rafael Rodriguez-Acuña; Eduardo Mayoral; Manuel Aguilar-Diosdado; Reyes Rave; Beatriz Oyarzabal; Carmen Lama; Ana Carriazo; Maria Asuncion Martinez-Brocca
Journal:  BMJ Open Diabetes Res Care       Date:  2020-10

7.  Five regions, five retinopathy screening programmes: a systematic review of how Portugal addresses the challenge.

Authors:  Andreia Marisa Penso Pereira; Raul Manuel da Silva Laureano; Fernando Buarque de Lima Neto
Journal:  BMC Health Serv Res       Date:  2021-07-30       Impact factor: 2.655

  7 in total

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