M JUN1, M JARDINE1, H LAMBERS HEERSPINK1,2, V PERKOVIC1, S BADVE1, S KOTWAL1, M GALLAGHER1, K HARRIS1, J CHALMERS1, M WOODWARD1
1George Institute For Global Health, UNSW Sydney, Australia, Newtown, Australia, 2University Medical Center Groningen, Groningen, The Netherlands
Aim: To assess the association between variability in estimated glomerular filtration rate (eGFR) and the risk of major clinical outcomes in type 2 diabetes (T2DM) in the ADVANCE trial.
Background: It is not clear whether eGFR variability modifies the risk of future major clinical outcomes in T2DM or is non-consequential physiological variation.
Methods: Variability in eGFR (coefficient of variation[CV] defined as standard deviation divided by mean) was calculated in 8241 patients from 3 serum creatinine measurements over 20 months, classified into 3 groups by increasing thirds of eGFR variability: low (≤6.4; reference), moderate (>6.4 to ≤12.1) and high (>12.1). We repeated analyses using 2 alternative eGFR variability measures (standard deviation and range). The primary outcome was the composite of major macrovascular events, new or worsening nephropathy and all-cause mortality; secondary outcomes were these components. Cox regression models were used to estimate hazard ratios (HRs).
Results: Over a median follow-up of 2.9 years, 932 primary outcomes were recorded (466 major macrovascular events, 296 new or worsening nephropathy events and 418 deaths). Greater eGFR variability over 20 months was independently associated with higher risk of the primary outcome (HR for moderate and high variability compared with low variability: 1.07, 95% CI:0.91-1.27 and 1.22, 95% CI:1.03-1.45, respectively) with evidence of a positive log-linear trend(p=0.015). When outcomes were assessed individually, results were consistent for new or worsening nephropathy, but no statistically significant associations were observed for major macrovascular events and all-cause mortality. Overall results remained largely similar when alternative GFR variability measures were used.
Conclusions: Variability in eGFR predicted changes in the risk of major clinical outcomes in T2DM, which suggest prognostic value of longitudinal assessments of eGFR variability.
Min Jun is Associate Professor and Scientia Fellow at the George Institute for Global Health, UNSW Sydney Australia. He has expertise in population health research, in particular, the use of large linked data sources to assess the relationships between clinical management strategies and outcomes in people with CKD, diabetes and/or cardiovascular disease. To date, he has >80 publications (>3600 citations), ~45% published in the top 10% most cited journals globally