BURDEN AND EXCESS RISK OF ADVERSE OUTCOMES IN PATIENTS WITH TYPE 1 DIABETES UTILIZING KDIGO CLASSIFICATION: A NATIONAL COHORT STUDY

Introduction:

The most widely adopted Kidney Disease Improving Global Outcomes (KDIGO) classification has been underutilized so far for evaluating the burden and risk of renal and cardiovascular (CV) outcomes in individuals with type 1 diabetes mellitus (T1DM). This study, using data from the Swedish National Diabetes Register, sought to address three key objectives: 1) to delineate the distribution of KDIGO categories within the T1DM cohort, 2) to quantify the incidence of renal and CV events, including mortality, associated with each KDIGO category, and 3) to assess the relationship between baseline KDIGO categories and future risk of five major outcomes. 

Methods:

We calculated the estimated glomerular filtration rate (eGFR) using the CKD-EPI 2009 equation at both baseline and during follow-up. According to KDIGO 2024 guidelines, participants were classified into eGFR categories (G1 to G5, with subcategorization of G1 into G1a and G1b) and albuminuria categories (A1 to A3). The renal outcomes examined included acute kidney injury, a 40% decline in eGFR, kidney failure, renal death, and a composite outcome termed "MAKE" (which consists of any of the above-mentioned renal outcomes). CV outcomes assessed were coronary heart disease (including acute myocardial infarction and unstable angina), stroke, cardiovascular death, and a composite outcome "MACE" (which includes any of these cardiovascular events plus heart failure). We also evaluated all-cause mortality. Cumulative incidence rates were calculated using Kaplan-Meier survival curves, and incidence rates were reported per 1000 person-years. Cox proportional hazards models were used to determine the association between baseline KDIGO categories and the risk of the five major outcomes: 40% eGFR decline, kidney failure, MAKE, MACE, and all-cause mortality. Hazard ratios (HR) and 95% confidence intervals were computed. Cox regression analyses were conducted using three different reference categories: (1) the conventional low-risk categories "combined G1A1+G2A1";  and (2) "G1A1" alone to assess if G2A1 had excess risk; and (3) “G1bA1” alone to evaluate if eGFR ≥105 ml/min had increased risk due to hyperfiltration

Results:

Among 39,067 patients, with a mean follow-up duration of 9.1 years (totaling 350,000 person-years), and median number of eGFR measurements of 9.0 (IQR 5.0, 13.0), 18.5% had chronic kidney disease (defined as eGFR <60 ml/min/1.73m² and/or albuminuria), with 8.1% being normoalbuminuric. The study found a progressive increase in incidence rates (Figure 1) and adjusted hazard ratios for all outcomes with advancing KDIGO categories, even among individuals with eGFR ≥60 ml/min/1.73m². Notably, when using G1A1 as the reference, the G2A1 group—traditionally considered low risk—exhibited a significantly higher risk for all major outcomes (Table 2), whereas eGFR ≥105 ml/min without albuminuria was not associated with increased risk (Table 3). 

Figure 1: Kaplan-Meier survival curves showing cumulative incidences of major outcomes

Table 1: Adjusted hazard ratios for major outcomes with conventional G1A1+G2A1 categories as reference

Table 2: Adjusted hazard ratios for major outcomes with G1A1 as sole reference category

Table 3: Adjusted hazard ratios for major outcomes with G1bA1 as sole reference category

Conclusions:

Our findings indicate a progressive increase in the burden of adverse cardiorenal outcomes, including mortality, with higher KDIGO categories in the T1DM population. Elevated risks were observed even among individuals with preserved eGFR and normoalbuminuria, underscoring the importance of early screening and preventive measures to improve outcomes for this high-risk group. 

I have no potential conflict of interest to disclose.

I did not use generative AI and AI-assisted technologies in the writing process.