Severity of coronary artery disease and retinal microvascular signs in patients with diagnosed versus undiagnosed diabetes: cross-sectional study

The Profile of Glucose Lowering Therapy in Persons with Type 2 Diabetes Mellitus in an Aging Russian Population

We aimed to analyze the profile of glucose lowering therapy (GLT) in persons with diabetes mellitus type 2 (DM2) in an aging Russian population. A random population sample (n = 3898, men/women, 55−84) was examined in Novosibirsk, during 2015−2018 (HAPIEE Project). The design of the present work is a cross-sectional study. DM2 was defined in those with a history of DM2 receiving GLT, or at a level of fasting plasma glucose (FPG) ≥7.0 mmol/L. The entire DM2 group was included in the analysis (n = 803); of these, 476 persons were taking GLT and were included in the analysis at stage 2. Regular GLT medication intake for 12 months was coded with ATC. In studied sample, the prevalence of DM2 was 20.8%. Among subjects with DM2, 59% of individuals received GLT, 32% did not. Glycemic control (FPG < 7.0 mmol/L) was achieved in every fifth participant with DM2 (35% in those receiving GLT). In frequency of GLT use, biguanides ranked in first place (75%), sulfonylurea derivatives in second (35%), insulins in third (12%), and iDPP-4 in fourth (5%). Among those receiving GLT, 24% used combined oral therapy, and 6% used insulin-combined therapy. In conclusion, in a population sample aged 55−84 examined in 2015−2018, glycemic control was achieved in every fifth participant with DM2, and in every third participant receiving GLT. The proportion of participants using new GLT drugs was small, and there was a lack of HbA1c monitoring for intensive glycemic control.

Retinal arteriolar tortuosity and fractal dimension are associated with long-term cardiovascular outcomes in people with type 2 diabetes

AIMS/HYPOTHESIS

Our aim was to determine whether quantitative retinal traits in people with type 2 diabetes are independently associated with incident major cardiovascular events including CHD and stroke.

METHODS

A total of 1066 men and women with type 2 diabetes, aged 65-74 years, were followed up over 8 years in the population-based Edinburgh Type 2 Diabetes Study. Using retinal photographs taken at baseline and specialist software, a number of quantitative retinal traits were measured, including arteriolar and venular widths and tortuosity as well as fractal dimension (a measure of the branching pattern complexity of the retinal vasculature network). Incident CHD events occurring during follow-up included fatal and non-fatal myocardial infarction, first episodes of angina and coronary interventions for CHD. Incident cerebrovascular events included fatal and non-fatal stroke or transient ischaemic attack. Cox proportional hazard regression analyses were performed to identify the association of the retinal traits with cardiovascular events in the population with retinal data available (n = 1028).

RESULTS

A total of 200 participants had an incident cardiovascular event (139 CHD and 61 cerebrovascular events). Following adjustment for age and sex, arteriolar tortuosity and fractal dimension were associated with cerebrovascular events (HR 1.27 [95% CI 1.02, 1.58] and HR 0.74 [95% CI 0.57, 0.95], respectively), including with stroke alone (HR 1.30 [95% CI 1.01, 1.66] and HR 0.73 [95% CI 0.56, 0.97], respectively). These associations persisted after further adjustment for established cardiovascular risk factors (HR 1.26 [95% CI 1.01, 1.58] and HR 0.73 [95% CI 0.56, 0.94], respectively). Associations generally reduced in strength after a final adjustment for the presence of diabetic retinopathy, but the association of fractal dimension with incident cerebrovascular events and stroke retained statistical significance (HR 0.73 [95% CI 0.57, 0.95] and HR 0.72 [95% CI 0.54, 0.97], respectively). Associations of retinal traits with CHD were generally weak and showed no evidence of statistical significance.

CONCLUSIONS/INTERPRETATION

Arteriolar tortuosity and fractal dimension were associated with incident cerebrovascular events, independent of a wide range of traditional cardiovascular risk factors including diabetic retinopathy. These findings suggest potential for measurements of early retinal vasculature change to aid in the identification of people with type 2 diabetes who are at increased risk from stroke.

Deep Learning-Based Detection of Early Renal Function Impairment Using Retinal Fundus Images: Model Development and Validation

BACKGROUND

Retinal imaging has been applied for detecting eye diseases and cardiovascular risks using deep learning-based methods. Furthermore, retinal microvascular and structural changes were found in renal function impairments. However, a deep learning-based method using retinal images for detecting early renal function impairment has not yet been well studied.

OBJECTIVE

This study aimed to develop and evaluate a deep learning model for detecting early renal function impairment using retinal fundus images.

METHODS

This retrospective study enrolled patients who underwent renal function tests with color fundus images captured at any time between January 1, 2001, and August 31, 2019. A deep learning model was constructed to detect impaired renal function from the images. Early renal function impairment was defined as estimated glomerular filtration rate <90 mL/min/1.73 m2. Model performance was evaluated with respect to the receiver operating characteristic curve and area under the curve (AUC).

RESULTS

In total, 25,706 retinal fundus images were obtained from 6212 patients for the study period. The images were divided at an 8:1:1 ratio. The training, validation, and testing data sets respectively contained 20,787, 2189, and 2730 images from 4970, 621, and 621 patients. There were 10,686 and 15,020 images determined to indicate normal and impaired renal function, respectively. The AUC of the model was 0.81 in the overall population. In subgroups stratified by serum hemoglobin A1c (HbA1c) level, the AUCs were 0.81, 0.84, 0.85, and 0.87 for the HbA1c levels of ≤6.5%, >6.5%, >7.5%, and >10%, respectively.

CONCLUSIONS

The deep learning model in this study enables the detection of early renal function impairment using retinal fundus images. The model was more accurate for patients with elevated serum HbA1c levels.

Burden of Undiagnosed Type 2 Diabetes in Diabetic Kidney Disease: A Japanese Retrospective Cohort Study

The risk of developing diabetic kidney disease (DKD) in patients with undiagnosed diabetes mellitus (UD) has never been evaluated. We studied the burden of UD on the risk of developing DKD in the Japanese population in a single-center retrospective cohort study. The patients with type 2 diabetes mellitus, but without DKD (estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² or proteinuria), were recruited from January 2018 to January 2019; medical records were scrutinized retrospectively from January 2003 until May 2019. The individuals, with diabetes that could not be denied based on past and current records, comprised the undiagnosed diabetes (UD) group whereas those with confirmed diagnosis comprised the diagnosed diabetes (DD) group. The group differences were tested using a Kaplan–Meier curve and Cox proportional hazards model. Among the 408 participants, 164 (40.2%) and 244 (59.8%) comprised the DD and UD groups, respectively. The baseline parameters, including age, male gender, and BMI were comparable between the groups, but the plasma glucose, HbA1c levels, and diabetic retinopathy prevalence were higher in the UD group. The risk of developing DKD (log rank test, p < 0.001), an eGFR of < 60 mL/min/1.73 m² (p = 0.001) and proteinuria (p = 0.007) were also higher in the UD group. The unadjusted and adjusted hazard ratios for DKD were 1.760 ((95% CI: 1.323–2.341), p < 0.001) and 1.566 ((95% CI: 1.159–2.115), p = 0.003), respectively, for the UD group. In conclusion, this is the first report showing that UD is a strong risk factor for DKD. The notion that a longer duration of untreated diabetes mellitus is involved strongly in the risk of developing DKD warrants the need for the identification and monitoring of UD patients.

Glucose-lowering therapy and cardiovascular outcomes in patients with type 2 diabetes mellitus and acute coronary syndrome

Diabetes is a common comorbidity in patients hospitalized for an acute coronary syndrome event, and prevalence is increasing. Among patients hospitalized with acute myocardial infarction, diabetes can be an independent predictor of mortality and new cardiovascular events; both short- and long-term outcomes are worse for patients with diabetes relative to those without, and undiagnosed diabetes is associated with greater mortality. The impact of glycemic control on cardiovascular outcomes and the best approach to treat hyperglycemia upon hospital admission for acute coronary syndrome in patients with or without known diabetes remain open questions. This review assesses available evidence for hyperglycemia management at the time of admission for acute coronary syndrome and, thereafter, finds that (1) admission plasma glucose plays a role in predicting adverse events, especially in patients with unknown diabetes; (2) glycated haemoglobin is a likely predictor of events in patients with unknown diabetes; and (3) hypoglycemia at the time of acute myocardial infarction hospital admission is an important predictor for mortality in patients with and without diabetes. Whether glucose-targeted insulin and glucose infusion have advantages over glucose-insulin-potassium infusion remains controversial. Evidence for the effect of novel glucose-lowering agents used at the time of an acute cardiovascular event is limited and requires more dedicated studies.

The role of newly diagnosed diabetes mellitus for poor in-hospital prognosis of coronary artery bypass grafting

Background: The management of coronary artery disease in patients with type 2 diabetes (T2DM) who need myocardial revascularization is a great challenge. Aims: To study the role of newly diagnosed T2DM in the development of in-hospital adverse outcomes after coronary artery surgery (CABG). Methods: 708 consecutive patients underwent CABG were included. All patients without history of T2DM and with border fasting hyperglycemia underwent an oral glucose tolerance test. Results: The screening allowed to diagnose T2DM in 8.9% and prediabetes in 10.4% of the study population. The the number of patients with T2DM increased from 15.2% to 24.1%, and with prediabetes from 3.0% to 13.4%. The total number of patients with carbohydrate metabolism disorders increased from 18.2% to 37.5%. The trend towards higher rate of in-hospital complications after CABG was defined among patients with newly diagnosed and previously diagnosed T2DM. The regression analysis demonstrated the presence of the relationships between the previously diagnosed T2DM and the total number of significant complications (odds ratio (OR) 1.350, 95% confidence interval (CI): 1.0571.723, p=0.020) and prolonged in-hospital stay (OR 1.609, 95%CI 1.2022.155, p=0.001). The significance of these relationships increased with the addition of newly diagnosed T2DM to the regression model (for in-hospital complications: OR 1.731, 95% CI 1.1312.626, p=0.012; for prolonged in-hospital stay: OR 2.229, 95%CI 1.4123.519, p0.001). Moreover, additional associations between T2DM and the risk of developing multiple organ dysfunction (OR 2.911, 95% CI 1.0727.901, p=0.039), urgent lower extremity surgery (OR 1.638, 95%CI 1.00915.213, p=0.020) and the need for extracorporeal correction of hemostasis (OR 3.472, 95%CI 1.04211.556, p=0.044) have been defined. Importantly, the presence of these associations would not have been identified without including newly diagnosed DM in the regression model. Conclusion: The newly diagnosed T2DM affects the prognosis of CABG as well as the previously diagnosed T2DM. The obtained results suggest the importance of active preoperative T2DM screening.