Literature DB >> 19540187

Compliance with the quality standards of National Diabetic Retinopathy Screening Committee.

Sreedhar Jyothi1, Babar Elahi, Anamika Srivastava, Marilyn Poole, Dinesh Nagi, Sobha Sivaprasad.   

Abstract

AIMS: The National Diabetic Retinopathy Screening Committee has recommended 19 standards for quality assurance of screening programmes in the United Kingdom. Five of the standards apply to the care provided by ophthalmology departments. This study assesses the quality assurance of the eye care provided by the Wakefield and North Kirklees Screening programme.
METHODS: A retrospective audit of case notes of patients for 12 consecutive months in 2007. The outcomes were compared with the five quality standards.
RESULTS: Out of a total number of 15,080 patients screened for diabetic retinopathy (DR), 479 (3.17%) required referral to ophthalmology department (screen-positive). Of these, 352 (2.33% of total screened) were referred for diabetic retinopathy. Forty-three patients (13%) were referred for proliferative retinopathy (R3), 279 (79%) for maculopathy (M1), 24 (7%) for non-proliferative retinopathy (R2), and 4 (1%) for a history of previous photo-coagulation (P1). Fifty-eight patients (16%) failed to attend. A timely consultation was achieved in 33% of R3 and 77% of M1 patients. Only 31% of R3 and 8% of M1 at screening were listed at their first visit to ophthalmology clinic and received laser treatment in stipulated time.
CONCLUSION: Significant progress is required for timely consultation and management of screen-positive patients. In order to achieve these targets efficiently, it may be appropriate to re-define M1 so that a significant proportion of patients with M1 may be referred to and better managed by primary care physicians or diabetologists.

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Year:  2009        PMID: 19540187     DOI: 10.1016/j.pcd.2009.05.005

Source DB:  PubMed          Journal:  Prim Care Diabetes        ISSN: 1878-0210            Impact factor:   2.459


  9 in total

1.  Predictors for diabetic retinopathy progression-findings from nominal group technique and Evidence review.

Authors:  Sajjad Haider; Salman Naveed Sadiq; Eniya Lufumpa; Harpreet Sihre; Mohammad Tallouzi; David J Moore; Krishnarajah Nirantharakumar; Malcolm James Price
Journal:  BMJ Open Ophthalmol       Date:  2020-10-09

2.  SDOCT imaging to identify macular pathology in patients diagnosed with diabetic maculopathy by a digital photographic retinal screening programme.

Authors:  Sarah Mackenzie; Christian Schmermer; Amanda Charnley; Dawn Sim; Martin Dumskyj; Stephen Nussey; Catherine Egan
Journal:  PLoS One       Date:  2011-05-06       Impact factor: 3.240

3.  Validation of diabetic retinopathy and maculopathy diagnoses recorded in a U.K. primary care database.

Authors:  Elisa Martín-Merino; Joan Fortuny; Elena Rivero; Luis Alberto García-Rodríguez
Journal:  Diabetes Care       Date:  2012-02-22       Impact factor: 19.112

4.  Cost-effectiveness of digital surveillance clinics with optical coherence tomography versus hospital eye service follow-up for patients with screen-positive maculopathy.

Authors:  Jose Leal; Ramon Luengo-Fernandez; Irene M Stratton; Angela Dale; Katerina Ivanova; Peter H Scanlon
Journal:  Eye (Lond)       Date:  2018-11-30       Impact factor: 3.775

5.  Application of artificial intelligence-based dual-modality analysis combining fundus photography and optical coherence tomography in diabetic retinopathy screening in a community hospital.

Authors:  Rui Liu; Qingchen Li; Feiping Xu; Shasha Wang; Jie He; Yiting Cao; Fei Shi; Xinjian Chen; Jili Chen
Journal:  Biomed Eng Online       Date:  2022-07-20       Impact factor: 3.903

6.  Disease burden of diabetes, diabetic retinopathy and their future projections in the UK: cross-sectional analyses of a primary care database.

Authors:  Sajjad Haider; Rasiah Thayakaran; Anuradha Subramanian; Konstantinos A Toulis; David Moore; Malcolm James Price; Krishnarajah Nirantharakumar
Journal:  BMJ Open       Date:  2021-07-12       Impact factor: 2.692

7.  A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis.

Authors:  Fangyao Tang; Xi Wang; An-Ran Ran; Carmen K M Chan; Mary Ho; Wilson Yip; Alvin L Young; Jerry Lok; Simon Szeto; Jason Chan; Fanny Yip; Raymond Wong; Ziqi Tang; Dawei Yang; Danny S Ng; Li Jia Chen; Marten Brelén; Victor Chu; Kenneth Li; Tracy H T Lai; Gavin S Tan; Daniel S W Ting; Haifan Huang; Haoyu Chen; Jacey Hongjie Ma; Shibo Tang; Theodore Leng; Schahrouz Kakavand; Suria S Mannil; Robert T Chang; Gerald Liew; Bamini Gopinath; Timothy Y Y Lai; Chi Pui Pang; Peter H Scanlon; Tien Yin Wong; Clement C Tham; Hao Chen; Pheng-Ann Heng; Carol Y Cheung
Journal:  Diabetes Care       Date:  2021-07-27       Impact factor: 17.152

8.  Altered myocardial response in patients with diabetic retinopathy: an exercise echocardiography study.

Authors:  Zhe Zhen; Yan Chen; Kendrick Shih; Ju-Hua Liu; Michele Yuen; David Sai-Hung Wong; Karen Siu-Ling Lam; Hung-Fat Tse; Kai-Hang Yiu
Journal:  Cardiovasc Diabetol       Date:  2015-09-18       Impact factor: 9.951

9.  Real-world artificial intelligence-based opportunistic screening for diabetic retinopathy in endocrinology and indigenous healthcare settings in Australia.

Authors:  Jane Scheetz; Dilara Koca; Myra McGuinness; Edith Holloway; Zachary Tan; Zhuoting Zhu; Rod O'Day; Sukhpal Sandhu; Richard J MacIsaac; Chris Gilfillan; Angus Turner; Stuart Keel; Mingguang He
Journal:  Sci Rep       Date:  2021-08-04       Impact factor: 4.379

  9 in total

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