2018 Articles

Creatinine- versus cystatin C-based renal function assessment in the Northern Manhattan Study

Husain, Syed Ali; Willey, Joshua Zebadiah; Moon, Yeseon P.; Elkind, Mitchell S.; Sacco, Ralph L.; Wolf, Myles; Cheung, Ken; Wright, Clinton B.; Mohan, Sumit

Background
Accurate glomerular filtration rate estimation informs drug dosing and risk stratification. Body composition heterogeneity influences creatinine production and the precision of creatinine-based estimated glomerular filtration rate (eGFRcr) in the elderly. We compared chronic kidney disease (CKD) categorization using eGFRcr and cystatin C-based estimated GFR (eGFRcys) in an elderly, racially/ethnically diverse cohort to determine their concordance.

Methods
The Northern Manhattan Study (NOMAS) is a predominantly elderly, multi-ethnic cohort with a primary aim to study cardiovascular disease epidemiology. We included participants with concurrently measured creatinine and cystatin C. eGFRcr was calculated using the CKD-EPI 2009 equation. eGFRcys was calculated using the CKD-EPI 2012 equation. Logistic regression was used to estimate odds ratios and 95% confidence intervals of factors associated with reclassification from eGFRcr≥60ml/min/1.73m2 to eGFRcys<60ml/min/1.73m2.

Results
Participants (n = 2988, mean age 69±10yrs) were predominantly Hispanic, female, and overweight/obese. eGFRcys was lower than eGFRcr by mean 23mL/min/1.73m2. 51% of participants’ CKD status was discordant, and only 28% maintained the same CKD stage by both measures. Most participants (78%) had eGFRcr≥60mL/min/1.73m2; among these, 64% had eGFRcys<60mL/min/1.73m2. Among participants with eGFRcr≥60mL/min/1.73m2, eGFRcys-based reclassification was more likely in those with age >65 years, obesity, current smoking, white race, and female sex.

Conclusions
In a large, multiethnic, elderly cohort, we found a highly discrepant prevalence of CKD with eGFRcys versus eGFRcr. Determining the optimal method to estimate GFR in elderly populations needs urgent further study to improve risk stratification and drug dosing.