Abstract: TH-PO1027
Kidney Function Variability Independently Predicts CKD Progression
Session Information
- CKD: Epidemiology, Risk Factors, and Prevention - 1
October 24, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2301 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Amdur, Richard L., Northwell Health, New Hyde Park, New York, United States
- Butler, Mark J., Northwell Health, New Hyde Park, New York, United States
- Ng, Jia Hwei, Northwell Health, New Hyde Park, New York, United States
Background
Kidney function variability (KFV) was an independent predictor of renal and cardiovascular outcomes in 15 prior studies since 2009. Here, we test three measures of KFV in a large patient sample in a US healthcare system to determine the optimal definition of KFV for predicting renal outcomes.
Methods
Using EHR data from 2016-2023 in a large hospital system in the northeastern US, we selected patients who had an inpatient admission and at least 4 serum creatinine (Scr) measurements over 18 months (baseline) and baseline eGFR > 30 ml/min/1.73 m2. We calculated eGFR slope and variability during this baseline period and examined renal outcomes for patients with 3 or more Scr measures over at least 6 and up to 80 months of follow-up. Renal outcomes included 25% eGFR decrease from baseline mean and entry into stage 4 CKD. We used quintiles of KFV as measured by standard deviation (SD), coefficient of variation (CV), and non-linearity (NL; deviation from the individual patient’s regression line of monthly minimum eGFR x year). We used Cox proportional hazard models with covariates age, race, sex, baseline mean eGFR, baseline slope of eGFR, baseline comorbidities and baseline anti-diabetic or anti-hypertensive medication class, to examine the independent predictive value of each KFV measure on renal outcomes, with censoring at death or the end of the study period.
Results
99,964 patients qualified for inclusion (mean age 62, mean baseline eGFR 82, 57% female, 17% Black, 6% Asian, 13% Hispanic, 28% with DM). 15.1% of patients had 25% eGFR drop, and 5.5% reached CKD stage 4. In Cox models adjusted for demographics, comorbidities, medications, and baseline eGFR slope and mean, all three KFV measures were significant independent predictors of both renal outcomes (all p<.0001), but the strongest effect was for CV. After adjusting for covariates, each 1-quintile increase in baseline eGFR-CV was associated with a 12% increase in hazard of 25% eGFR decline (95% ci 10-13%, p<.0001) and a 15% increase in hazard of reaching stage 4 CKD (95% ci 13-18%, p<.0001) during follow-up.
Conclusion
KFV is a powerful independent predictor of CKD progression even after accounting for baseline level and slope of eGFR and other covariates, and since it is easily obtainable, it should be considered for use in future risk stratification algorithms. CV appears to be the best measure of KFV.