Diabetes mellitus: association of cystatin C versus creatinine-based estimated glomerular filtration rate with mortality and cardiovascular events

Background To explore the association between the differences between cystatin C- and creatinine-based estimated glomerular filtration rate (eGFRdiff), and the risk of mortality and cardiovascular (CV) events in individuals with diabetes.Methods Three prospective cohorts analyzed data from adults with diabetes from the Incident, Development, and Prognosis of Diabetic Kidney Disease (INDEED) study (2016-17 to 2020) in China, the National Health Nutrition Examination Survey (NHANES, 1999-2004 to 2019) in the USA and UK Biobank (UKB, 2006-10 to 2022) in the UK. Baseline eGFRdiff was calculated using both absolute difference between cystatin C- and creatinine-based calculations (eGFRabdiff), and the ratio between them (eGFRrediff). Cox proportional hazards regression models were used to investigate the association between eGFRdiff and outcomes including all-cause mortality and incident CV events.Results A total of 8129 individuals from INDEED (aged 60.7 +/- 10.0 years), 1634 from NHANES (aged 62.5 +/- 14.4 years) and 29 358 from UKB (aged 59.4 +/- 7.3 years) were included. At baseline, 43.6%, 32.4% and 42.1% of participants in INDEED, NHANES and UKB, respectively, had an eGFRabdiff value >= 15 mL/min/1.73 m2. During a median follow-up of 3.8 years for INDEED, 15.2 years for NHANES and 13.5 years for UKB, a total of 430, 936 and 6143 deaths and a total of 481, 183 and 5583 CV events occurred, respectively. Each 1-standard deviation higher baseline eGFRabdiff was independently associated with a lower risk of all-cause mortality and CV events, with hazard ratios of 0.77 and 0.82 in INDEED, 0.70 and 0.68 in NHANES, and 0.66 and 0.78 in UKB. Similar results were observed for eGFRrediff.Conclusions eGFRdiff represents a marker of adverse events for diabetes among general population. Monitoring both eGFRcys and eGFRcr yields additional prognostic information and has clinical utility in identifying high-risk individuals for mortality and CV events. Graphical Abstract 10.1093/ndt/gfae011 Video Watch the video of this contribution at https://academic.oup.com/ndt/pages/author_videos gfae011Media1 6347328042112