| Title |
Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine
|
|---|---|
| Published in |
Diabetologia, August 2017
|
| DOI | 10.1007/s00125-017-4386-0 |
| Pubmed ID | |
| Authors |
Antonio Eleuteri, Anthony C. Fisher, Deborah M. Broadbent, Marta García-Fiñana, Christopher P. Cheyne, Amu Wang, Irene M. Stratton, Mark Gabbay, Daniel Seddon, Simon P. Harding, for the Individualised Screening for Diabetic Retinopathy (ISDR) Study Group |
| Abstract |
Individualised variable-interval risk-based screening offers better targeting and improved cost-effectiveness in screening for diabetic retinopathy. We developed a generalisable risk calculation engine (RCE) to assign personalised intervals linked to local population characteristics, and explored differences in assignment compared with current practice. Data from 5 years of photographic screening and primary care for people with diabetes, screen negative at the first of > 1 episode, were combined in a purpose-built near-real-time warehouse. Covariates were selected from a dataset created using mixed qualitative/quantitative methods. Markov modelling predicted progression to screen-positive (referable diabetic retinopathy) against the local cohort history. Retinopathy grade informed baseline risk and multiple imputation dealt with missing data. Acceptable intervals (6, 12, 24 months) and risk threshold (2.5%) were established with patients and professional end users. Data were from 11,806 people with diabetes (46,525 episodes, 388 screen-positive). Covariates with sufficient predictive value were: duration of known disease, HbA1c, age, systolic BP and total cholesterol. Corrected AUC (95% CIs) were: 6 months 0.88 (0.83, 0.93), 12 months 0.90 (0.87, 0.93) and 24 months 0.91 (0.87, 0.94). Sensitivities/specificities for a 2.5% risk were: 6 months 0.61, 0.93, 12 months 0.67, 0.90 and 24 months 0.82, 0.81. Implementing individualised RCE-based intervals would reduce the proportion of people becoming screen-positive before the allocated screening date by > 50% and the number of episodes by 30%. The Liverpool RCE shows sufficient performance for a local introduction into practice before wider implementation, subject to external validation. This approach offers potential enhancements of screening in improved local applicability, targeting and cost-effectiveness. |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 7 | 54% |
| Korea, Democratic People's Republic of | 1 | 8% |
| Germany | 1 | 8% |
| United States | 1 | 8% |
| Unknown | 3 | 23% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 54% |
| Practitioners (doctors, other healthcare professionals) | 3 | 23% |
| Scientists | 2 | 15% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 8 | 19% |
| Student > Ph. D. Student | 7 | 17% |
| Researcher | 5 | 12% |
| Student > Master | 4 | 10% |
| Student > Bachelor | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 12 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 40% |
| Business, Management and Accounting | 2 | 5% |
| Computer Science | 2 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 6 | 14% |
| Unknown | 13 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 November 2022.
All research outputs
#1,995,760
of 23,114,117 outputs
Outputs from Diabetologia
#1,061
of 5,096 outputs
Outputs of similar age
#40,788
of 317,439 outputs
Outputs of similar age from Diabetologia
#51
of 107 outputs
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