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Abstract: PO0453

Predicting Progression to ESKD: Application of Novel Statistical Methodologies

Session Information

Category: CKD (Non-Dialysis)

  • 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

  • Looper, Kristina, Fresenius Medical Care, Global Medical Office, Waltham, Massachusetts, United States
  • Preciado, Priscila, Renal Research Institute, New York, New York, United States
  • Jiao, Yue, Fresenius Medical Care, Global Medical Office, Waltham, Massachusetts, United States
  • Hahn Contino, Carly, Fresenius Medical Care, Global Medical Office, Waltham, Massachusetts, United States
  • Usvyat, Len A., Fresenius Medical Care, Global Medical Office, Waltham, Massachusetts, United States
  • Wang, Yuedong, University of California Santa Barbara, Santa Barbara, California, United States
  • Kotanko, Peter, Renal Research Institute, New York, New York, United States
Background

Estimating time to end-stage renal disease (ESRD) in chronic kidney disease patients (CKD) is important in preparing patients for a smooth transition to dialysis. In this analysis we explored patterns in trajectories of blood urea nitrogen (BUN), systolic blood pressure (SBP), and estimated glomerular filtration rate (eGFR) in patients with CKD and associated them to time to ESRD.

Methods

We used data from a registry of CKD patients from practices using Acumen electronic medical records, obtaining 8,572 patients with CKD 3 from 2003 to 2018 based on their first eGFR value. BUN, SBP, and eGFR were observed for 3 years after first eGFR measurement. Time to ESRD is calculated from the start of the follow-up period to when eGFR < 15 mL/min/1.73m2. Functional data for each patient was generated by fitting cubic splines to BUN, SBP, and eGFR, respectively. Trajectories of each variable were grouped into 3 clusters using principle component analysis (PCA) scores; time to ESRD was compared between them by Kaplan-Meier analysis. We fit Cox proportional hazards model with eGFR, SBP, BUN clusters and age, sex, and race as predictors of ESRD onset.

Results

BUN, SBP, and eGFR have stable, increasing, and decreasing trajectory clusters (Figure). In a Cox model with these clusters as well as age, gender, and race, trajectories of eGFR, BUN, and SBP were significant predictors of ESRD onset.

Conclusion

Since BUN, SBP, and eGFR trajectories were all significant predictors of progression to ESRD, it is important to consider all three to ascertain CKD progression.

Funding

  • NIDDK Support