Kidney Week

Abstract: SA-PO756

Clinical Utility of the Kidney Failure Risk Equation in Determining Timing of Predialysis Education

Session Information

• CKD: Epidemiology, Risk Factors, Prevention - III
  October 27, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: CKD (Non-Dialysis)

• 1901 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

• Wainstein, Marina, St George Hospital, Sydney, Elizabeth Bay, New South Wales, Australia

Marina Wainstein,

• Pirabhahar, Saiyini, St George Hospital, Sydney, Elizabeth Bay, New South Wales, Australia

Saiyini Pirabhahar,

• Van deventer, Hendrick E., Lancet Laboratories, Johannesburg, South Africa

Hendrick E. Van deventer,

• Turner, Kylie M., St George Hospital, Sydney, Elizabeth Bay, New South Wales, Australia

Kylie M. Turner,

• Lim, Su San, St George Hospital, Sydney, Elizabeth Bay, New South Wales, Australia

Su San Lim,

• Katz, Ivor Jonathan, St George Hospital, Sydney, Elizabeth Bay, New South Wales, Australia

Ivor Jonathan Katz,

Background

The Kidney Failure Risk Equation (KFRE) has been validated to predict decline in chronic kidney disease (CKD) and proposed as a tool for dialysis planning.Timing of predialysis education is known to impact short- and long-term outcomes on dialysis. Current guidelines recommend it occurs within 12 months before initiation but little evidence exists to guide the timing of this referral. Our aim was to assess and validate the efficacy of the KFRE in predicting optimal timing for dialysis education.

Methods

A 2 year risk of end stage kidney disease (ESKD) was calculated using the 4-variable KFRE in a cohort of patients with CKD stages 3-5 and compared to eGFR with respect to predictive efficacy. The sensitivity and specificity of the test using KFRE thresholds of 10 and 20% as well as eGFR of 15 and 20 ml/min/1.73 m² were examined, reflecting KFRE risk suggestions and eGFR cut-offs currently used for referral to predialysis education. In patients who developed ESKD and commenced dialysis we searched retrospectively for an association between KFRE and time from predialysis education to initiation (dependent variable) using linear regression.

Results

Of 294 patients included in the analysis, 106 progressed to ESKD over the 2 year follow-up period. The area under the receiver operating curve for KFRE was 0.97 [95% confidence interval (CI) 0.96-0.99]) and 0.93 for eGFR (95% CI, 0.90-0.97). Using a KFRE threshold of 10% the sensitivity was 82% and specificity 97% and at 20% the sensitivity decreased to 57% but specificity was maintained (98%). Use of eGFR cut-offs of 20 and 15 ml/min/1.73 m² resulted in lower sensitivity (56% and 18% respectively) but equivalent specificity (97 and 99% respectively). There was a weak, positive association between KFRE risk and longer time from dialysis education to initiation (r² = 0.072, p = 0.016).

Conclusion

The KFRE can be considered validated in our population as a good predictor of ESKD and modestly superior to eGFR. A threshold KFRE risk of 10% over 2 years appears to be a more useful guide than eGFR for timely referral to predialysis education. However, this was not observed at a higher threshold, suggesting that other factors may impact on the rate of progression to dialysis. KFRE requires ongoing evaluation for decision-making nearing ESKD.