A simple tool to predict end-stage renal disease within 1 year in elderly adults with advanced chronic kidney disease

Paul E. Drawz, Puja Goswami, Reem Azem, Denise C. Babineau, Mahboob Rahman

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Objectives To develop and validate a model to predict 1-year risk of end-stage renal disease (ESRD) in elderly subjects with advanced chronic kidney disease (CKD). Design Retrospective. Setting Veterans Affairs Medical Center. Participants Individuals aged 65 and older with CKD with an estimated glomerular filtration rate (eGFR) less than 30 mL/min per 1.73 m2. Measurements The outcome was ESRD within 1 year of the index eGFR. Cox regression was used to develop a predictive model (Veterans Affairs (VA) risk score) that was validated in a separate cohort. Results Of the 1,866 participants in the developmental cohort, 77 developed ESRD. Risk factors for ESRD in the final model were age, congestive heart failure, systolic blood pressure, eGFR, potassium, and albumin. In the validation cohort, the C index for the VA risk score was 0.823. The risk for developing ESRD at 1 year from lowest to highest tertile was 0.08%, 2.7%, and 11.3% (P <.001). The C-index for the recently published Tangri model in the validation cohort was 0.780. Conclusion A new model using commonly available clinical measures shows excellent ability to predict the onset of ESRD within the next year in elderly adults. The Tangri model also had good predictive ability. Individuals and physicians can use these risk models to inform decisions regarding preparation for renal replacement therapy in individuals with advanced CKD.

Original languageEnglish (US)
Pages (from-to)762-768
Number of pages7
JournalJournal of the American Geriatrics Society
Volume61
Issue number5
DOIs
StatePublished - 2013

Keywords

  • aging
  • chronic kidney failure
  • chronic renal insufficiency
  • hypertension

Fingerprint Dive into the research topics of 'A simple tool to predict end-stage renal disease within 1 year in elderly adults with advanced chronic kidney disease'. Together they form a unique fingerprint.

Cite this