Irish National Diabetic RetinaScreen Programme: report on five rounds of retinopathy screening and screen-positive referrals. (INDEAR study report no. 1)

Patients with Type 2 Diabetes, Higher Blood Pressure, and Infrequent Fundus Examinations Have a Higher Risk of Sight-Threatening Retinopathy

Background: Diabetic retinopathy (DR) is the most common cause of preventable blindness among working-age adults. This study aimed to evaluate the impact of the regularity of fundus examinations and risk factor control in patients with type 2 diabetes (T2DM) on the prevalence and severity of DR. Methods: One hundred and fifty-six T2DM patients were included in this cross-sectional study. Results: In this sample, the prevalence of DR was 46.2%. Patients with no DR mainly did not examine the fundus regularly, while most patients with mild/moderate nonproliferative DR (NPDR) underwent a fundus examination regularly. In 39.7% of patients, this was the first fundus examination due to diabetes, and 67% of them had sight-threatening DR (STDR). Diabetes duration (p = 0.007), poor glycemic control (HbA1c) (p = 0.006), higher systolic blood pressure (SBP) (p < 0.001), and diastolic blood pressure (DBP) (p = 0.002) were the main predictors of DR. However, the impact of SBP (AOR 1.07, p = 0.003) and DBP (AOR 1.13, p = 0.005) on DR development remained significant even after adjustment for diabetes duration and HbA1c. The DR prevalence was higher in patients with higher blood pressure (≥130/80 mmHg) than in those with target blood pressure (<130/80 mmHg) (p = 0.043). None of the patients with target blood pressure had STDR. The peaks in SBP and DBP were observed in T2DM with DR and the first fundus examination due to diabetes. Conclusions: In this T2DM sample, DR prevalence was very high and strongly related to blood pressure and a lack of regular fundus examinations. These results indicate the necessity of establishing systematic DR screening in routine diabetes care and targeting blood pressure levels according to T2DM guidelines.

Addressing Technical Failures in a Diabetic Retinopathy Screening Program

Purpose

Diabetic retinopathy (DR) is a preventable cause of blindness detectable through screening using retinal digital photography. The Irish National Diabetic Retina Screening (DRS) programme, Diabetic RetinaScreen, provides free screening services to patients with diabetes from aged 12 years and older. A technical failure (TF) occurs when digital retinal imaging is ungradable, resulting in delays in the diagnosis and treatment of sight-threatening disease. Despite their impact, the causes of TFs, and indeed the utility of interventions to prevent them, have not been extensively examined.

Aim

Primary analysis aimed to identify factors associated with TF. Secondary analysis examined a subset of cases, assessing patient data from five time points between 2019 and 2021 to identify photographer/patient factors associated with TF.

Methods

Patient data from the DRS database for one provider were extracted for analysis between 2018 and 2022. Information on patient demographics, screening results, and other factors previously associated with TF were analyzed. Primary analysis involved using mixed-effects logistic regression models with nested patient-eye random effects. Secondary analysis reviewed a subset of cases in detail, checking for causes of TF.

Results

The primary analysis included a total of 366,528 appointments from 104,407 patients over 5 years. Most patients had Type 2 diabetes (89.2%), and the overall TF rate was 4.9%. Diabetes type and duration, dilate pupil status, and the presence of lens artefacts on the camera were significantly associated with TF. The Secondary analysis identified the primary cause of TF was found to be optically dense cataracts, accounting for over half of the TFs.

Conclusion

This study provides insight into the causes of TF within the Irish DRS program, highlighting cataracts as the primary contributing factor. The identification of patient-level factors associated with TF facilitates appropriate interventions that can be put in place to improve patient outcomes and minimize delays in treatment and diagnosis.

Accuracy of Low-Cost, Smartphone-Based Retinal Photography for Diabetic Retinopathy Screening: A Systematic Review

Purpose

Diabetic retinopathy (DR) is a leading cause of blindness. Early DR screening is essential, but the infrastructure can be less affordable in low resource countries. This study aims to review the accuracy of low-cost smartphone-based fundus cameras for DR screening in adult patients with diabetes.

Methods

We performed a systematic literature search to find studies that reported the sensitivity and specificity of low-cost smartphone-based devices for fundus photography in adult patients with diabetes. We searched three databases (MEDLINE, Google Scholar, Scopus) and one register (Cochrane CENTRAL). We presented the accuracy values by grouping the diagnosis into three: any DR, referrable DR, and diabetic macular oedema (DMO). Risk of bias and applicability of the studies were assessed using QUADAS-2.

Results

Five out of 294 retrieved records were included with a total of six smartphone-based devices reviewed. All of the reference diagnostic methods used in the included studies were either indirect ophthalmoscopy or slit-lamp examinations and all smartphone-based devices' imaging protocols used mydriatic drops. The reported sensitivity and specificity for any DR were 52-92.2% and 73.3-99%; for referral DR were 21-91.4% and 64.9-100%; and for DMO were 29.4-81% and 95-100%, respectively.

Conclusion

Sensitivity available low-cost smartphone-based devices for DR screening were acceptable and their specificity particularly for detecting referrable DR and DMO were considerably good. These findings support their potential utilization for DR screening in a low resources setting.

The Effect on Patients' Visual Acuity and Grade, Secondary to Non-Attendance at Treatment Centers, Post Referral from Diabetic RetinaScreen Ireland

Background

Patient non-attendance following referral to hospital is a significant challenge, in particular, for persons with diabetes.

Aim

We sought to determine the impact on both visual acuity and the subsequent follow-up retinopathy grade of patients when they fail to attend Diabetic Retinopathy Treatment (DRT) Centers following referral from Diabetic RetinaScreen (DRS).

Methods

A retrospective analysis of patients discharged from DRT due to multiple consecutive missed appointments between January 2016 and June 2021. Patients discharged for non-attendance were compared with patients discharged from completed treatment.

Results

Of the 24,945 NEC patients referred to DRT, 5900 (24%) and 9345 (37%) were discharged back to DRS due to non-attendance and completed treatment, respectively. Those discharged for non-attendance were younger (60.7 v 63.4, p < 0.001) and had higher proportions of males (67% v 63%, p < 0.001) and people with type 1 diabetes (27% v 18%, p < 0.001). After attending rescreening after discharge, those discharged for non-attendance were significantly more likely to have a worsening of DR grade (26% v 8%, p < 0.001).

Conclusion

Despite being notified that further investigation (with possible treatment) was required post DRS, many diabetic patients failed to attend for further management of their eye care in DRT. These patients had worse visual outcomes compared to those that attended. Improved patient education and communication are required to mitigate against the consequences of non-attendance.

Diabetic retinopathy screening in the emerging era of artificial intelligence

Diabetic retinopathy is a frequent complication in diabetes and a leading cause of visual impairment. Regular eye screening is imperative to detect sight-threatening stages of diabetic retinopathy such as proliferative diabetic retinopathy and diabetic macular oedema in order to treat these before irreversible visual loss occurs. Screening is cost-effective and has been implemented in various countries in Europe and elsewhere. Along with optimised diabetes care, this has substantially reduced the risk of visual loss. Nevertheless, the growing number of patients with diabetes poses an increasing burden on healthcare systems and automated solutions are needed to alleviate the task of screening and improve diagnostic accuracy. Deep learning by convolutional neural networks is an optimised branch of artificial intelligence that is particularly well suited to automated image analysis. Pivotal studies have demonstrated high sensitivity and specificity for classifying advanced stages of diabetic retinopathy and identifying diabetic macular oedema in optical coherence tomography scans. Based on this, different algorithms have obtained regulatory approval for clinical use and have recently been implemented to some extent in a few countries. Handheld mobile devices are another promising option for self-monitoring, but so far they have not demonstrated comparable image quality to that of fundus photography using non-portable retinal cameras, which is the gold standard for diabetic retinopathy screening. Such technology has the potential to be integrated in telemedicine-based screening programmes, enabling self-captured retinal images to be transferred virtually to reading centres for analysis and planning of further steps. While emerging technologies have shown a lot of promise, clinical implementation has been sparse. Legal obstacles and difficulties in software integration may partly explain this, but it may also indicate that existing algorithms may not necessarily integrate well with national screening initiatives, which often differ substantially between countries.

Automated multidimensional deep learning platform for referable diabetic retinopathy detection: a multicentre, retrospective study

OBJECTIVE

To develop and validate a real-world screening, guideline-based deep learning (DL) system for referable diabetic retinopathy (DR) detection.

DESIGN

This is a multicentre platform development study based on retrospective, cross-sectional data sets. Images were labelled by two-level certificated graders as the ground truth. According to the UK DR screening guideline, a DL model based on colour retinal images with five-dimensional classifiers, namely image quality, retinopathy, maculopathy gradability, maculopathy and photocoagulation, was developed. Referable decisions were generated by integrating the output of all classifiers and reported at the image, eye and patient level. The performance of the DL was compared with DR experts.

SETTING

DR screening programmes from three hospitals and the Lifeline Express Diabetic Retinopathy Screening Program in China.

PARTICIPANTS

83 465 images of 39 836 eyes from 21 716 patients were annotated, of which 53 211 images were used as the development set and 30 254 images were used as the external validation set, split based on centre and period.

MAIN OUTCOMES

Accuracy, F1 score, sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), Cohen's unweighted κ and Gwet's AC1 were calculated to evaluate the performance of the DL algorithm.

RESULTS

In the external validation set, the five classifiers achieved an accuracy of 0.915-0.980, F1 score of 0.682-0.966, sensitivity of 0.917-0.978, specificity of 0.907-0.981, AUROC of 0.9639-0.9944 and AUPRC of 0.7504-0.9949. Referable DR at three levels was detected with an accuracy of 0.918-0.967, F1 score of 0.822-0.918, sensitivity of 0.970-0.971, specificity of 0.905-0.967, AUROC of 0.9848-0.9931 and AUPRC of 0.9527-0.9760. With reference to the ground truth, the DL system showed comparable performance (Cohen's κ: 0.86-0.93; Gwet's AC1: 0.89-0.94) with three DR experts (Cohen's κ: 0.89-0.96; Gwet's AC1: 0.91-0.97) in detecting referable lesions.

CONCLUSIONS

The automatic DL system for detection of referable DR based on the UK guideline could achieve high accuracy in multidimensional classifications. It is suitable for large-scale, real-world DR screening.

Feasibility of a multifaceted implementation intervention to improve attendance at diabetic retinopathy screening in primary care in Ireland: a cluster randomised pilot trial

OBJECTIVES

Diabetic retinopathy screening (DRS) uptake is suboptimal in many countries with limited evidence available on interventions to enhance DRS uptake in primary care. We investigated the feasibility and preliminary effects of an intervention to improve uptake of Ireland's national DRS programme, Diabetic RetinaScreen, among patients with type 1 or type 2 diabetes.

DESIGN/SETTING

We conducted a cluster randomised pilot trial, embedded process evaluation and cost analysis in general practice, July 2019 to January 2020.

PARTICIPANTS

Eight practices participated in the trial. For the process evaluation, surveys were conducted with 25 staff at intervention practices. Interviews were conducted with nine staff at intervention practices, and 10 patients who received the intervention.

INTERVENTIONS

The intervention comprised practice reimbursement, an audit of attendance, electronic prompts targeting professionals, General Practice-endorsed patient reminders and a patient information leaflet. Practices were randomly allocated to intervention (n=4) or wait-list control (n=4) (usual care).

OUTCOMES

Staff and patient interviews explored their perspectives on the intervention. Patient registration and attendance, including intention to attend, were measured at baseline and 6 months. Microcosting was used to estimate intervention delivery cost.

RESULTS

The process evaluation identified that enablers of feasibility included practice culture and capacity to protect time, systems to organise care, and staff skills, and workarounds to improve intervention 'fit'. At 6 months, 22/71 (31%) of baseline non-attenders in intervention practices subsequently attended screening compared with 15/87 (17%) in control practices. The total delivery cost across intervention practices (patients=363) was €2509, averaging €627 per practice and €6.91 per audited patient. Continuation criteria supported proceeding to a definitive trial.

CONCLUSIONS

The Improving Diabetes Eye screening Attendance intervention is feasible in primary care; however, consideration should be given to how best to facilitate local tailoring. A definitive trial of clinical and cost-effectiveness is required with preliminary results suggesting a positive effect on uptake.

TRIAL REGISTRATION NUMBER

NCT03901898.

A simulation study of the economic and health impact of a diabetes prevention programme in Ireland

AIMS

Type 2 diabetes is a major public health issue that has a large effect on society including its health and social services. The aims of this paper are to generate a projection of the number of cases and explore the potential impact of a preventive intervention targeted at people with pre-diabetes on disease prevalence, complications, mortality and cost.

METHODS

A Markov simulation model of diabetes and pre-diabetes in Ireland, for the period 1991 to 2036, was generated based on international epidemiological data. The simulation was calibrated with the available Irish data on the prevalence of pre-diabetes, diabetes and diabetic complications. The economic and health impact of a hypothetical nationwide preventive intervention programme, which reduces the incidence by a factor consistent with the international literature, was estimated under three scenarios of alternative effectiveness and uptake.

RESULTS

The estimated number of people over 40 years of age with type 2 diabetes in Ireland is projected to increase from 216,000 in 2020 to 414,000 in 2036. A prevention programme, based on the NHS Diabetes Prevention Programme, is estimated to result in a reduction of between 2000 (0.5%) and 19,000 (4.6%) in the number of prevalent cases of diabetes in 2036 resulting in substantial health and quality of life benefits.

CONCLUSIONS

A wide range of initiatives with uncertain outcomes will be required to reduce the impact of obesity and type 2 diabetes. A diabetes prevention programme seems likely to be worth pursuing as one element of this set of initiatives.

Factors associated with non-attendance in the Irish national diabetic retinopathy screening programme (INDEAR study report no. 2)

AIMS

We aimed to determine the patient and screening-level factors that are associated with non-attendance in the Irish National Diabetic Retinal screening programme (Diabetic RetinaScreen). To accomplish this, we modelled a selection of predictors derived from the historical screening records of patients with diabetes.

METHODS

In this cohort study, appointment data from the national diabetic retinopathy screening programme (RetinaScreen) were extracted and augmented using publicly available meteorological and geospatial data. A total of 653,969 appointments from 158,655 patients were included for analysis. Mixed-effects models (univariable and multivariable) were used to estimate the influence of several variables on non-attendance to screening appointments.

RESULTS

All variables considered for analysis were statistically significant. Variables of note, with meaningful effect, were age (OR: 1.23 per decade away from 70; 95% CI: [1.22-1.24]), type 2 diabetes (OR: 1.10; 95% CI: [1.06-1.14]) and socio-economic deprivation (OR: 1.12; 95% CI: [1.09-1.16]). A majority (52%) of missed appointments were from patients who had missed three or more appointments.

CONCLUSIONS

This study is the first to outline factors that are associated with non-attendance within the Irish national diabetic retinopathy screening service. In particular, when corrected for age and other factors, patients with type 2 diabetes had higher rates of non-attendance. Additionally, this is the first study of any diabetic screening programme to demonstrate that weather may influence attendance. This research provides unique insight to guide the implementation of an optimal and cost-effective intervention strategy to improve attendance.

A micro costing analysis of the development of a primary care intervention to improve the uptake of diabetic retinopathy screening

Background

The application of economic analysis within implementation science is still developing and the cost of intervention development, which differs markedly from the costs of initial implementation and maintenance, is often overlooked. Our aim was to retrospectively cost the development of a multifaceted intervention in primary care to improve attendance at diabetic retinopathy screening.

Methods

A retrospective micro costing of developing the intervention from the research funder perspective was conducted. It was based on a systematic intervention development process involving analysis of existing audit data and interviews with patients and healthcare professionals (HCPs), conducting consensus meetings with patients and HCPs, and using these data together with a rapid review of the effectiveness of interventions, to inform the final intervention. Both direct (non-personnel, e.g. travel, stationary, room hire) and indirect (personnel) costs were included. Data sources included researcher time logs, payroll data, salary scales, an online financial management system, invoices and purchase orders. Personnel involved in the intervention development were consulted to determine the activities they conducted and the duration of their involvement. Sensitivity and scenario analyses were conducted to estimate uncertainty around parameters and scope.

Results

The total cost of intervention development (July 2014–January 2019) was €40,485 of which 78% were indirect (personnel) costs (€31,451). In total, personnel contributed 1368 h to intervention development. Highest cost activities were the patient interviews, and consensus process, contributing 23% and 34% of the total cost. Varying estimated time spent on intervention development activities by + 10% increased total intervention development cost by 6% to €42,982.

Conclusions

Our results highlight that intervention development requires a significant amount of human capital input, combining research experience, patient and public experience, and expert knowledge in relevant fields. The time committed to intervention development is critical but has a significant opportunity cost. With limited resources for research on developing and implementing interventions, capturing intervention development costs and incorporating them as part of assessment of cost-effective interventions, could inform research priority and resource allocation decisions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13012-021-01085-4.