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Abstract: FR-PO939

Predicting All-Cause Mortality in Patients with Advanced CKD

Session Information

Category: CKD (Non-Dialysis)

  • 2301 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention


  • Brar, Ranveer Singh, Seven Oaks General Hospital, Winnipeg, Manitoba, Canada
  • Ferguson, Thomas W., Seven Oaks General Hospital, Winnipeg, Manitoba, Canada
  • Sood, Manish M., Department of Medicine in Ottawa, Ottawa, Ontario, Canada
  • Tangri, Navdeep, Seven Oaks General Hospital, Winnipeg, Manitoba, Canada

Group or Team Name

  • Chronic Disease Innovation Centre.

Patients with advanced CKD are at high risk of mortality, kidney failure and cardiovascular events. Accurately identifying patients that are at a higher risk for mortality may aid in clinical decision making and preventing unnecessary dialysis therapies that may cause more harm. We developed and externally validated a risk prediction tool using commonly collected clinical measurements to predict all-cause mortality among patients with advanced CKD.


We developed a prediction model using demographic, clinical and laboratory data in adult patients (≥ 18 years) with advanced CKD (eGFR <30 mL/min/1.73m2) from Manitoba, Canada, between January 2012, and September 2020, with external validation from Ontario, Canada. Our primary outcome was time to all-cause mortality. If dialysis was initiated in follow-up, we ascertained all-cause mortality within 1 year of dialysis initiation. We assessed model discrimination using the area under the receiver operating characteristic curve (AUC) and calibration using plots of observed and predicted risks.


The development cohort included 397 patients (mean age 65.4 ± 13.9) with 121 events. The final model included age, sex, estimated GFR, hemoglobin, serum albumin and congestive heart failure and achieved a 2-year and 5-year AUC of 74.3 (CI: 68.4 – 80.1) and 80.2 (CI: 75.3 – 85.1), respectfully. Discrimination and calibration were adequate in the external validation data set with 2-year and 5-year AUC scores of 71.4 (CI: 70.8 – 72.0) and 73.0 (CI: 72.5 – 73.5).


We developed a simple prediction model that included commonly measured variables that can accurately predict all-cause mortality in patients with advanced CKD. This equation may aid as a support tool for nephrologists in dialysis decision making, especially in patients who are at high risk of mortality.