#1750 Burden and excess risk of adverse outcomes in patients with type 1 diabetes utilizing KDIGO classification: a national cohort study

Abstract Background and Aims Our investigation was motivated by the underutilization of the “Kidney Disease Improving Global Outcomes” (KDIGO) classification in evaluating the burden and impact of renal and cardiovascular (CV) adverse outcomes in individuals with type 1 diabetes mellitus (T1DM). Focusing on T1DM patients from the Swedish National Diabetes Register, our study aimed to clarify three key aspects: 1) the distribution of various KDIGO categories across the cohort, 2) the incidence of adverse renal and cardiovascular events, including mortality, for each KDIGO category, and 3) the association of baseline KDIGO category and future excess risk for five major outcomes described below. Method The estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI 2009 equation at baseline and during follow-up. In accordance with KDIGO 2012 guidelines, participants were classified based on their baseline albuminuria and creatinine into G1 to G5 eGFR and A1 to A3 albuminuria categories. Renal outcomes of interest for incidence analysis included: acute kidney injury, 40% eGFR decline from baseline, kidney failure, renal death, and a composite outcome named “MAKE” comprising either of the above renal outcomes. The CV outcomes were coronary heart disease (incorporating acute myocardial infarction and unstable angina), stroke and CV death, the composite outcome “MACE” that included either of the above CV outcomes and heart failure. Additionally, incidence of all-cause mortality was analysed. The cumulative incidence of outcomes was assessed using Kaplan-Meier Survival curves, and incidence rate was calculated per 1000 person-years (py). Cox proportional hazards regression models of risk in the KDIGO strata were employed to examine the association between baseline KDIGO category and the risk of the following five major outcomes: 40% decline, KF, MAKE, MACE and all-cause mortality. Hazard ratios (HR) and 95% confidence intervals were determined. Cox-regression analyses were conducted twice: initially using as reference the conventional KDIGO low-risk categories “combined G1A1 + G2A1” and then using “only G1A1” to specifically evaluate if G2A1 is associated with excess risk. Results Among 39 067 included patients, mean follow-up was 9.1 years (350 000 person-years). The prevalence of chronic kidney disease, defined as eGFR <60 ml/min/1.73 m2 and/or albuminuria, was 18.5% of whom 8.1% were normoalbuminuric. As seen in the figure below, a progressive increase in incidence and adjusted HR for all outcomes was found with advancing eGFR and albuminuria categories, even in individuals with eGFR ≥60 ml/min/1.73 m2. Interestingly, repeat analysis using G1A1 alone as reference revealed significantly elevated risk for all major outcomes even in G2A1 (10% of the entire cohort), conventionally perceived as low risk. Conclusion A progressively increasing burden of adverse cardiorenal outcomes including mortality was observed with advancing KDIGO categories in T1DM population. Even in subjects with preserved eGFR and normoalbuminuria, we identified an elevated risk for all major outcomes, indicating that early screening and implementation of preventive strategies may be beneficial in improving prognosis of this population.