F BARZI1, G JONES2 , J Hughes1 , P Lawton1 , W Hoy3 , K O’Dea4 , G Jerums5 , R MacIsaac5 , A Cass1 , L Maple-Brown1
1The Menzies School of Health Research , Tiwi NT, Australia; 2St Vincent’s Hospital , Sydney NSW, Australia; 3The University of Queensland, Herston QLD, Australia; 4The University of South Australia, Adelaide SA, Australia; 5The University of Melbourne, Melbourne VIC, Australia
Aim: This analysis aimed to explore the trend of decline in eGFR over a four year period using multiple local creatinine measures. Estimates of decline using multiple local measurements were compared with estimates derived using centrally-measured enzymatic creatinine and with estimates derived using only two local measures.
Background: Being able to accurately predict kidney decline is particularly important in Indigenous Australians, a population at increased risk of developing chronic and end stage kidney disease.
Methods: The eGFR study comprised a cohort of over 600 Aboriginal Australian participants recruited from over twenty sites in urban, regional and remote Australia across five strata of health, diabetes and kidney function. Trajectories of eGFR were explored on 385 participants with at least three local creatinine records using graphical methods that compared the linear trends with non-linear trends.
Results: Mean age of the participants was 48 years, 64% were female and the median follow-up was 3 years. Decline of eGFR was accurately estimated using linear regression models and locally measured creatinine was as good as centrally measured creatinine at predicting kidney decline in people with an eGFR < 60 and an eGFR 60-90 ml/min/1.73m2 with albuminuria. Analyses showed that one baseline and one follow-up locally measured creatinine may be sufficient to estimate short term kidney function decline. The greatest yearly decline was estimated in those with eGFR 60-90 and macro-albuminuria: -6.21 (-8.20, -4.23) ml/min/1.73m2.
Conclusions: Short term predictions of kidney function decline can be reliably derived using an easy to implement and simple to interpret linear model. Locally measured creatinine did not differ to centrally measured creatinine, thus is an accurate cost-efficient and timely means to monitoring kidney function progression.