Is aspirin associated with diabetic retinopathy? The Singapore Epidemiology of Eye Disease (SEED) study

Cost-effectiveness of diabetic retinopathy screening for newly diagnosed type 2 diabetic patients: A nationwide population-based propensity score-matched cohort study

AIMS

This study investigated the association between the frequency of screening for diabetic retinopathy (DR) versus the development of DR and corresponding medical expenses among patients newly diagnosed with type 2 diabetes mellitus (T2DM).

METHODS

This longitudinal, population-based study used the Taiwan National Health Insurance Research Database (2004 to 2020) as a data source. Propensity score matching (PSM) (sex, age, comorbidities and concurrent medication use) was employed in the grouping of T2DM patients according to different frequency of DR screening. Outcome measures included the proportion of patients who developed DR, who received DR treatment, and the associated medical expenses and hospitalizations.

RESULTS

The 17-year cohort included 337,046 patients. After PSM, three groups each containing 35,739 patients were assembled and analyzed. Compared to low-frequency screening, high-frequency screening was more effective in detecting patients requiring treatment; however, the net cost for treatment was significantly lower. Standard-frequency screening appears to provide the best balance in terms of DR detection, diagnosis interval, the risk of DR-related hospitalization, and DR treatment costs.

CONCLUSIONS

In this real-world cohort study covering all levels of the healthcare system, infrequent screening was associated with delayed diagnosis and elevated treatment costs, while a fundus screening interval of 1-2 years proved optimal in terms of detection and medical expenditures.

Aspirin intake is not associated with diabetic retinopathy and diabetic macular edema: A report from the Fushun diabetic retinopathy cohort study

PURPOSE

We aimed to study the effects of aspirin intake for diabetic retinopathy (DR) and diabetic macular edema (DME) in a cohort from northeastern China.

METHODS

Participants in the Fushun Diabetic Retinopathy Cohort Study were enrolled between July 2012 and May 2013. Fundus photographs of six fields were graded according to the modified Airlie House Classification system. The prevalence, incidence, progression, and regression of DR, as well as the prevalence/incidence of DME, were evaluated at baseline and during follow-up examinations after at least 1 year.

RESULTS

In total, 1370 patients were enrolled in the study, and 270 (19.7%) were taking aspirin. The prevalence of any DR in participants with and without aspirin intake was 47.4% and 44.9%, respectively (P = 0.46). The incidence of any DR in patients with and without aspirin intake was 9.2% and 8.3%, respectively (P = 0.74). In univariate regression, there was no association between aspirin intake and the prevalence of any DR and DME (odds ratios (OR), 95% confidence intervals (CI): 0.93, 0.68-1.27 and 1.22, 0.79-1.88, respectively). Aspirin intake was not significantly associated with the prevalence and incidence of DME (OR, 95% CI: 1.22, 0.79-1.88 and 1.79, 0.62-5.17, respectively). Furthermore, aspirin intake was not significantly associated with DR progression or regression (OR, 95% CI: 1.04, 0.66-1.66 and 0.75, 0.52-1.09, respectively).

CONCLUSION

Aspirin intake was not associated with the prevalence and incidence of any DR or DME in a northeastern Chinese population. Neither progression nor regression of DR revealed a significant association with aspirin intake.

Effect of anticoagulant/antiplatelet therapy on the development and progression of diabetic retinopathy

Background

We investigated whether antiplatelet/anticoagulant (APAC) therapy can protect patients with type 2 diabetes mellitus (T2DM) from the development or progression of diabetic retinopathy (DR).

Methods

This is a retrospective cohort study using Longitudinal Health Insurance Database in Taiwan. A total of 73,964 type 2 diabetic patients older than 20 years old were included. Hazard ration (HR) of non-proliferative DR (NPDR), proliferative DR (PDR), and diabetic macular edema (DME) were analyzed with APAC usage as a time-dependent covariate. Age, sex, comorbidities, and medicines were further adjusted in a multi-variable model. Contributions of respective APAC was investigated with sensitivity analysis.

Results

Compared with nonusers, APAC users had a lower cumulative incidence of NPDR (P < 0.001), overall incidence of NPDR (10.7 per 1000 person-years), and risk of developing NPDR (adjusted HR = 0.78, 95% CI = 0.73–0.83). However, no significant differences were observed between APAC users and nonusers in the risks of PDR or DME. Hypertension, diabetic nephropathy and diabetic neuropathy were risk factors for NDPR development, while heart disease, cardiovascular disease, peripheral arterial occlusive disease, and statin usage were covariates decreasing NPDR development. Aspirin and Dipyridamole showed significant protection against NPDR development. Clopidogrel, Ticlopidine, and warfarin showed enhanced protection in combination with aspirin usage.

Conclusions

APAC medications have a protective effect against NPDR development. Diabetic patients benefit from single use of aspirin or dipyridamole on prevention of NPDR.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12886-022-02323-z.

Relation Between Platelet Reactivity Levels and Diabetic Retinopathy Stage in Patient with Type 2 Diabetes Mellitus by Using Multiplate Whole Blood Aggregometry

Purpose: To test the hypothesis of a possible association between platelet reactivity and the severity of diabetic retinopathy using Multiplate whole blood aggregometry in type 2 diabetes mellitus patients. Methods: Of 157 patients were divided to three groups based on the severity of diabetic retinopathy (normal, non-proliferative and proliferative [ordinal among group 1-2-3]). Platelet reactivity was measured using arachidonic acid response to the ASPI and ADP platelet test. The association between DR stage and the degree of platelet reactivity (predictor variable) ASPI, ADP, systolic blood pressure, age, hypertension, body mass index (BMI), HbA1c, creatinine, Microalbumin, platelet, triglyceride/HDL and Hscrp variables were evaluated using ordinal logistic regression models (Model 1). The association between DR presence (outcome variable (group 1 vs group 2 and 3)) and the presence of variables was evaluated using binary logistic regression models (Model 2). Results: A comparison of the laboratory parameters of the three groups revealed that the ASPI, ADP, glucose and HbA1c values were significantly higher in Group-3 than Group-1. ASPI (odds-ratio OR: 1.044[1.021-1.09], p < .001], ADP (OR: 1.033[1.010-1.10], p: 0.002] and HbA1c (OR: 2.42(1.22, 4.94), p < .001) were demonstrated to be associated with stage of DR while the other variables were not. In binary logistic regression (model-2) analysis; ASPI (OR: 1.061[1.031-1.1], p < .001], ADP (OR: 1.03(1.01, 1.06), p: 0.045] and HbA1c (OR: 4.37 (1.67, 11.36)], p: 0.002) were associated with DR while the other variables were not. Conclusion: Herewith, we demonstrated that higher platelet reactivity measured by multiplate ASPI and ADP was significantly associated with stages of DR. Therefore, these measurements may be useful to predict the severity of DR in the clinical practice of physicians.

Aspirin in a diabetic retinopathy setting: Insights from NO BLIND study

BACKGROUND AND AIMS

Diabetic retinopathy (DR) is the most common microvascular complication of diabetes. Diabetic macroangiopathies, particularly cardiovascular (CV) diseases, seem closely related to diabetes microvascular complications. Aspirin represents the most prescribed compound in CV prevention. Aspirin impact on DR is still object of debate. As it is already recommended among diabetics at high CV risk, aim of this study was to assess a potential relationship between DR and aspirin therapy, in a type 2 diabetes cohort of patients screened through telemedicine.

METHODS AND RESULTS

NO Blind is a cross-sectional, multicenter, observational study, which involved nine Italian outpatient clinics. Primary endpoint was the assessment of the relationship between aspirin treatment and DR. 2068 patients were enrolled in the study, subsequently split in two subpopulations according to either the presence or absence of DR. Overall, 995 subjects were under aspirin therapy. After adjusting for most common potential confounders, age and gender, aspirin reveals significantly associated with DR (OR: 1.72, 95%CI: 1.58-2.89, p = 0.002) and proliferative DR (PDR) (OR: 1.89, 95%CI: 1.24-2.84, p = 0.003). Association comes lost further adjusting for MACEs (OR: 1.28, 95%CI: 0.85-1.42, p = 0.157) (Model 4) and eGFR (OR: 0.93; 95%CI: 0.71-1.22; p = 0.591) (Model 5).

CONCLUSION

In this multicenter cross-sectional study including a large sample of outpatients with T2DM, we showed that aspirin was not associated with DR after adjustment for several cardio-metabolic confounders. However, as partially confirmed by our findings, and related to the well-known pro-hemorrhagic effect of aspirin, its use should be individually tailored, even by telemedicine tools.

POSTERIOR FUNDUS HEMORRHAGES: Frequency and Associated Factors: The Beijing Eye Study

PURPOSE

To examine frequency and associations of retinal hemorrhages.

METHODS

The population-based Beijing Eye Study included 3,468 individuals. Monoscopic fundus photographs were examined for hemorrhages.

RESULTS

Retinal hemorrhages were detected in 515 eyes (429 individuals) (prevalence: 7.6%; 95% confidence interval [CI]: 7.0-8.0 per eye; 12.7%; 95% CI: 11.7-13.7 per person). Higher prevalence of retinal hemorrhages was correlated (multivariate analysis) with higher systolic blood pressure (P < 0.001; odds ratio: 1.02; 95% CI: 1.01-1.03), higher prevalence of diabetic retinopathy (P < 0.001; odds ratio: 121; 95% CI: 61-240), and higher prevalence of retinal vein occlusions (P < 0.001; odds ratio: 27; 95% CI: 17-42). Retinal hemorrhages were due to diabetic retinopathy (189 [36.7%] eyes), retinal vein occlusions (n = 65 [12.6%]), posterior vitreous detachment (n = 23 [4.5%]), glaucoma (n = 14 [2.7%]), exudative age-related macular degeneration (n = 8 [1.6%]), hypertensive retinopathy (n = 10 [1.9%]), and exudative myopic maculopathy (n = 1 [0.2%]). Retinal hemorrhages without evident ocular cause ("NOH") were detected in 204 (3.0%) eyes (or 39.6% of all retinal hemorrhages). Higher prevalence of NOHs was correlated with higher systolic blood pressure (P < 0.001; odds ratio: 1.02; 95% CI: 1.01-1.03) after adjusting for blood glucose concentration and prevalence of cortical cataract.

CONCLUSION

In a population-based recruited cohort of individuals aged 50+ years, prevalence of any fundus hemorrhage was about 8% per eye and 13% per individual. Approximately 60% of the hemorrhages were due to ocular reasons, mainly diabetic retinopathy, retinal vein occlusions, and posterior vitreous detachment, whereas 40% of the bleedings were not evidently associated with ophthalmologic causes but strongly with elevated systolic blood pressure.

Technical and imaging factors influencing performance of deep learning systems for diabetic retinopathy

Deep learning (DL) has been shown to be effective in developing diabetic retinopathy (DR) algorithms, possibly tackling financial and manpower challenges hindering implementation of DR screening. However, our systematic review of the literature reveals few studies studied the impact of different factors on these DL algorithms, that are important for clinical deployment in real-world settings. Using 455,491 retinal images, we evaluated two technical and three image-related factors in detection of referable DR. For technical factors, the performances of four DL models (VGGNet, ResNet, DenseNet, Ensemble) and two computational frameworks (Caffe, TensorFlow) were evaluated while for image-related factors, we evaluated image compression levels (reducing image size, 350, 300, 250, 200, 150 KB), number of fields (7-field, 2-field, 1-field) and media clarity (pseudophakic vs phakic). In detection of referable DR, four DL models showed comparable diagnostic performance (AUC 0.936-0.944). To develop the VGGNet model, two computational frameworks had similar AUC (0.936). The DL performance dropped when image size decreased below 250 KB (AUC 0.936, 0.900, p < 0.001). The DL performance performed better when there were increased number of fields (dataset 1: 2-field vs 1-field-AUC 0.936 vs 0.908, p < 0.001; dataset 2: 7-field vs 2-field vs 1-field, AUC 0.949 vs 0.911 vs 0.895). DL performed better in the pseudophakic than phakic eyes (AUC 0.918 vs 0.833, p < 0.001). Various image-related factors play more significant roles than technical factors in determining the diagnostic performance, suggesting the importance of having robust training and testing datasets for DL training and deployment in the real-world settings.

Hypertension, blood pressure control and diabetic retinopathy in a large population-based study

Background

Clinical trials have shown beneficial effects of blood pressure (BP) control in reducing the risk of diabetic retinopathy (DR). However, association between BP control and DR in population-based studies is not clear. We aimed to examine the association of hypertension and BP control with DR.

Methods

We analysed data from a population-based cross-sectional study of Chinese, Malay and Indians adults with diabetes and hypertension (2004–2011, n = 2189, aged 40–80 years) in Singapore. DR severity was assessed from retinal photographs and graded for any- and vision-threatening DR (VTDR) using the modified Airlie House classification. Hypertension status was classified into (1) good control: on treatment (SBP < 130 and DBP < 80 mm Hg), (2) moderate control: on treatment, with BP levels other than group 1 and 3, (3) poor control: on treatment (SBP ≥140 and DBP ≥ 90 mm Hg), (4) untreated hypertension, any BP level. SBP, DBP and pulse pressure (PP) were analyzed as categories and as continuous variables. The association between BP and DR was assessed using multivariable logistic regression models.

Results

The prevalence of any-DR and VTDR in the study population was 33.8% and 9.0% respectively. Both poorly controlled and untreated hypertension were significantly associated with any-DR with odds ratio (OR) (95% confidence interval [CI]) of 1.97 (1.39–2.83), and 2.01 [1.34–3.05]. Among BP components, SBP and PP were associated with both any-DR and VTDR with OR (95% CI) of 1.45 (1.28–1.65) and 1.61 (1.41–1.84) for any-DR, and 1.44 (1.19–1.76) and 1.67 (1.37–2.06) for VTDR.

Conclusion

In a population-based sample of Asian adults with diabetes and hypertension, treated but poorly controlled as well as untreated hypertension were significantly associated with any-DR. Among the BP components, higher SBP and PP levels were associated with both any-DR and VTDR. Further longitudinal studies are necessary to confirm our findings.

Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes

IMPORTANCE

A deep learning system (DLS) is a machine learning technology with potential for screening diabetic retinopathy and related eye diseases.

OBJECTIVE

To evaluate the performance of a DLS in detecting referable diabetic retinopathy, vision-threatening diabetic retinopathy, possible glaucoma, and age-related macular degeneration (AMD) in community and clinic-based multiethnic populations with diabetes.

DESIGN, SETTING, AND PARTICIPANTS

Diagnostic performance of a DLS for diabetic retinopathy and related eye diseases was evaluated using 494 661 retinal images. A DLS was trained for detecting diabetic retinopathy (using 76 370 images), possible glaucoma (125 189 images), and AMD (72 610 images), and performance of DLS was evaluated for detecting diabetic retinopathy (using 112 648 images), possible glaucoma (71 896 images), and AMD (35 948 images). Training of the DLS was completed in May 2016, and validation of the DLS was completed in May 2017 for detection of referable diabetic retinopathy (moderate nonproliferative diabetic retinopathy or worse) and vision-threatening diabetic retinopathy (severe nonproliferative diabetic retinopathy or worse) using a primary validation data set in the Singapore National Diabetic Retinopathy Screening Program and 10 multiethnic cohorts with diabetes.

EXPOSURES

Use of a deep learning system.

MAIN OUTCOMES AND MEASURES

Area under the receiver operating characteristic curve (AUC) and sensitivity and specificity of the DLS with professional graders (retinal specialists, general ophthalmologists, trained graders, or optometrists) as the reference standard.

RESULTS

In the primary validation dataset (n = 14 880 patients; 71 896 images; mean [SD] age, 60.2 [2.2] years; 54.6% men), the prevalence of referable diabetic retinopathy was 3.0%; vision-threatening diabetic retinopathy, 0.6%; possible glaucoma, 0.1%; and AMD, 2.5%. The AUC of the DLS for referable diabetic retinopathy was 0.936 (95% CI, 0.925-0.943), sensitivity was 90.5% (95% CI, 87.3%-93.0%), and specificity was 91.6% (95% CI, 91.0%-92.2%). For vision-threatening diabetic retinopathy, AUC was 0.958 (95% CI, 0.956-0.961), sensitivity was 100% (95% CI, 94.1%-100.0%), and specificity was 91.1% (95% CI, 90.7%-91.4%). For possible glaucoma, AUC was 0.942 (95% CI, 0.929-0.954), sensitivity was 96.4% (95% CI, 81.7%-99.9%), and specificity was 87.2% (95% CI, 86.8%-87.5%). For AMD, AUC was 0.931 (95% CI, 0.928-0.935), sensitivity was 93.2% (95% CI, 91.1%-99.8%), and specificity was 88.7% (95% CI, 88.3%-89.0%). For referable diabetic retinopathy in the 10 additional datasets, AUC range was 0.889 to 0.983 (n = 40 752 images).

CONCLUSIONS AND RELEVANCE

In this evaluation of retinal images from multiethnic cohorts of patients with diabetes, the DLS had high sensitivity and specificity for identifying diabetic retinopathy and related eye diseases. Further research is necessary to evaluate the applicability of the DLS in health care settings and the utility of the DLS to improve vision outcomes.