Kidney Week

Abstract: TH-PO1020

Outcomes and Risk Factors of Widened Difference in Estimated Glomerular Filtration Rate by Creatinine or Cystatin C: Adjust Model Development with More than 300,000 UK Biobank Participants

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

• Kang, Min Woo, Seoul National University College of Medicine, Jongno-gu, Seoul, Korea (the Republic of)

Min Woo Kang

• Kim, Yong Chul, Seoul National University College of Medicine, Jongno-gu, Seoul, Korea (the Republic of)

Yong Chul Kim, MD, PhD

• Oh, Kook-Hwan, Seoul National University College of Medicine, Jongno-gu, Seoul, Korea (the Republic of)

Kook-Hwan Oh, MD, PhD

• Kim, Dong Ki, Seoul National University College of Medicine, Jongno-gu, Seoul, Korea (the Republic of)

Dong Ki Kim, MD, PhD

• Park, Sehoon, Seoul National University College of Medicine, Jongno-gu, Seoul, Korea (the Republic of)

Sehoon Park, MD, PhD

Background

Recent studies have highlighted the significance of discrepancies between cystatin C-based(eGFRcys) and creatinine-based(eGFRcr) CKD-EPI eGFR. This study explores the implications of differences between eGFRcys and eGFRcr(eGFRdiff) on clinical outcomes and develops an adjusted model using eGFRcr and variables.

Methods

Using data from the UK Biobank cohort of 343,854 participants, we stratified them into three groups based on eGFRdiff: lower(eGFRcys-eGFRcr<-15), middle(-15≤eGFRcys-eGFRcr≤15), and upper(eGFRcys-eGFRcr>15). We analyzed the risks of death, MI, and ischemic stroke in the eGFRdiff<-15 and eGFRdiff>15 groups using Cox regression models. Logistic regression identified variables associated with eGFRdiff. And we developed and validated a regression model using eGFRcr and associated variables to approximate eGFRcys.

Results

Individuals with eGFRdiff<-15 had increased risks of death (HR:1.37[1.30-1.44]), MI (HR:1.23[1.15-1.33]), and ischemic stroke (HR:1.19[1.08-1.31]). Variables associated with eGFRdiff<-15 included high waist/hip circumference, high body weight, low fat-free mass, high total food intake, low protein intake, diabetes, and larger kidney volumes. A regression model was developed using eGFRcr, sex, age, height, weight, and BMI. In the validation set, this model achieved an adjusted R^2 of 0.47, improved from the initial R^2 of 0.32 between eGFRcys and eGFRcr. The adjusted model improved clinical outcome prediction.

Conclusion

This study confirmed that eGFRdiff<-15 is associated with increased risks of clinical outcomes and identified factors associated with eGFRdiff. We developed an adjusted model, demonstrating superior clinical outcome association.

ROC and AUROC of adjust models.