Aims/hypothesis: A protective role of sodium–glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide 1 receptor agonists (GLP1-ra) in the development of diabetic retinopathy and diabetic macular oedema has been described in some recent studies, which may extend beyond glycaemic control. We aimed to review the clinical impact of SGLT2i and GLP1-ra therapy on the risk of diabetic retinopathy and diabetic macular oedema in individuals with type 2 diabetes taking insulin. Methods: This is a retrospective cohort analysis of approximately two million people with type 2 diabetes receiving insulin across 97 healthcare organisations using a global federated health research network (TriNetX, Cambridge, USA). Two intervention cohorts (SGLT2i + insulin, n=176,409; GLP1-ra + insulin, n=207,034) were compared against a control cohort (insulin with no SGLT2i/GLP1-ra, n=1,922,312). Kaplan–Meier survival analysis was performed and estimated HRs were reported for each outcome. Propensity score was used to 1:1 match for age, sex, ischaemic heart disease, hypertension, microvascular complications, chronic kidney disease, HbA_1c, BMI and use of pioglitazone, lipid modifying agents, antilipemic agents, ACE inhibitors, angiotensin II inhibitors and metformin. A sub-analysis comparing the two intervention cohorts was also performed. Results: SGLT2i with insulin was associated with a reduced HR (95% CI) for diabetic macular oedema compared with the control cohort (0.835; 0.780, 0.893), while GLP1-ra with insulin demonstrated a lack of signal with no statistical significance to the HR (1.013; 0.960, 1.069). SGLT2i with insulin was not associated with a clinically significant increase in the risk of developing diabetic retinopathy (1.076; 1.027, 1.127), while GLP1-ra with insulin increased diabetic retinopathy risk (1.308; 1.261, 1.357). Compared with SGLT2i with insulin, GLP1-ra with insulin was associated with higher risk of diabetic retinopathy (1.205; 1.153, 1.259) and diabetic macular oedema (1.130; 1.056, 1.208). Conclusions/interpretation: Our study suggests that the combination of SGLT2i and insulin is associated with lower risk of developing diabetic macular oedema. However, the use of GLP1-ra was associated with an increased risk of diabetic retinopathy in individuals with type 2 diabetes also taking insulin. A comparative analysis showed favourable outcomes with SGLT2i and insulin in the development of diabetic macular oedema and diabetic retinopathy. RCTs using dedicated retinal imaging are required to determine the causal relationship with these therapies. Graphical

Aim: To assess the relationship of sodium‐glucose cotransporter‐2 inhibitors (SGLT2i), glucagon‐like peptide‐1 receptor analogues (GLP‐1RA) and their combination (SGLT2i + GLP‐1RA) with 5‐year risk of all‐cause mortality, hospitalization and cardiovascular/macrovascular disease in people with type 2 diabetes. Materials and Methods: Retrospective cohort analysis of 2.2 million people with type 2 diabetes receiving insulin across 85 health care organizations using a global federated health research network. Three intervention cohorts (SGLT2i, GLP‐1RA and SGLT2i + GLP‐1RA) were compared against a control cohort (no SGLT2i/GLP‐1RA). Propensity score matching for age, ischaemic heart disease, sex, hypertension, chronic kidney disease, heart failure and glycated haemoglobin was used to balance cohorts 1:1 (SGLT2i, n = 143 600; GLP‐1RA, n = 186 841; SGLT‐2i + GLP‐1RA, n = 108 504). A sub‐analysis comparing combination and monotherapy cohorts was also performed. Results: The intervention cohorts showed a reduced hazard ratio (HR, 95% confidence interval) over 5 years compared with the control cohort for all‐cause mortality (SGLT2i 0.49, 0.48‐0.50; GLP‐1RA 0.47, 0.46‐0.48; combination 0.25, 0.24‐0.26), hospitalization (0.73, 0.72‐0.74; 0.69, 0.68‐0.69; 0.60, 0.59‐0.61) and acute myocardial infarct (0.75, 0.72‐0.78; 0.70, 0.68‐0.73; 0.63, 0.60‐0.66), respectively. All other outcomes showed a significant risk reduction in favour of the intervention cohorts. The sub‐analysis showed a significant risk reduction in all‐cause mortality for combination therapy versus SGLT2i (0.53, 0.50‐0.55) and GLP‐1RA (0.56, 0.54‐0.59). Conclusions: SGLT2i, GLP‐1RAs or combination therapy confers mortality and cardiovascular protection in people with type 2 diabetes over 5 years. Combination therapy was associated with the greatest risk reduction in all‐cause mortality versus a propensity matched control cohort. In addition, combination therapy offers a reduction in 5‐year all‐cause mortality when compared directly against either monotherapy.

Aims: There is conflicting evidence on whether the type of atrial fibrillation (AF) is associated with risk of cardiovascular events, including acute myocardial infarction (MI) and ischemic stroke. The aim of the present study was to investigate whether the risk of MI and ischemic stroke differs between individuals with first-diagnosed paroxysmal vs. non-paroxysmal AF treated with anticoagulants. Methods and results: De-identified electronic medical records from the TriNetX federated research network were used. Individuals with a new diagnosis of paroxysmal AF who had no evidence of other types of AF in their records were 1:1 propensity score-matched with individuals with non-paroxysmal AF, defined as persistent or chronic AF, who had no evidence of other types of AF in their records. All patients were followed for three years for the outcomes of MI and ischemic stroke. Cox proportional hazard models were used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs). In the propensity-matched cohort, among 24 848 well-matched AF individuals [mean age 74.4 ± 10.4; 10 101 (40.6%) female], 410 (1.7%) were diagnosed with acute MI and 875 (3.5%) with ischemic stroke during the three-year follow-up. Individuals with paroxysmal AF had significantly higher risk of acute MI (HR: 1.65, 95%CI: 1.35–2.01) compared to those with non-paroxysmal AF. First diagnosed paroxysmal AF was associated with higher risk of non-ST elevation MI (nSTEMI) (HR: 1.89, 95%CI: 1.44–2.46). No significant association was observed between the type of AF and risk of ischemic stroke (HR: 1.09, 95%CI: 0.95–1.25). Conclusion: Patients with first-diagnosed paroxysmal AF had higher risk of acute MI compared to individuals with non-paroxysmal AF, attributed to the higher risk of nSTEMI among patients with first-diagnosed paroxysmal AF. There was no significant association between type of AF and risk of ischemic stroke.

Background: Despite its many advantages, haemodialysis (HD) has been shown to be associated with significant cardiovascular events, especially in patients commencing HD. Currently, there is no specific method to risk-stratify incident HD patients. Blood-based biomarkers provide insight into myocardial injury and stress. We aimed to evaluate the association of increased circulating biomarker concentration in incident HD with incident major adverse cardiac events (MACE). Methods: This was a retrospective cohort study of incident haemodialysis cases within 3 months of treatment initiation (≥18 years) from the TriNetX database. Cohorts were grouped by biomarker thresholds: Troponin I: ≥50 ng/L, BNP ≥ 100 pg/mL and 1:1 propensity-score matched for demographic characteristics, baseline cardiovascular risk, laboratory values, and cardiovascular medication. Primary outcome: Incidence of major adverse cardiac events (MACE) censored prior to index event of HD. Secondary outcome: Risk of each individual component of the composite outcome. Cox regression reported hazard ratios (95% CI) for the outcomes. Results: In total, 62,206 and 10,476 patients were included in the troponin I and BNP cohorts, respectively. In the troponin I cohort, 5878 developed MACE (HR 1.33 (95% CI 1.26–1.41, p < 0.0001)). In the BNP cohort, 1050 developed MACE (HR 1.28 (95% CI 1.13–1.44, p < 0.0001)). Conclusions: In incident HD, routine clinical laboratory biomarkers can predict incident MACE. The results suggest the clinical need for CV mortality and morbidity risk profiling in incident HD using a combination of clinical and laboratory variables.