To identify subgroups of adults with type 1 diabetes and analyse their treatment pathways and risk of diabetes-related complications over a 5-year follow-up. We performed a k-means cluster analysis using the T1DExchange Registry (n = 6,302) to identify subgroups based on demographic and clinical characteristics. Annual reassessments linked treatment trajectories with these clusters, considering drug and technology use. Complication risks were analysed using Cox regression. Five clusters were identified: 1) A favourable combination of all variables (31.67 %); 2) Longer diabetes duration (22.63 %); 3) Higher HbA1c levels (13.28 %); 4) Higher BMI (15.25 %); 5) Older age at diagnosis (17.17 %). Two-thirds of patients remained in their initial cluster annually. Technology adoption showed improved glycaemic control over time. Cox proportional hazards showed different risk patterns: Cluster 1 had low complication risk; Cluster 2 had the highest risk for retinopathy, coronary artery disease and autonomic neuropathy; Cluster 3 had the highest risk for albuminuria, depression and diabetic ketoacidosis; Cluster 4 had increased risk for multiple complications; Cluster 5 had the highest risk for hypertension and severe hypoglycaemia, with elevated coronary artery disease risk. Clinical characteristics can identify subgroups of patients with T1DM showing differences in treatment and complications during follow-up.