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Predicting 5-Year Risk of RRT in Stage 3 or 4 CKD: Development and External Validation.

Emily B Schroeder1,2, Xiuhai Yang3, Micah L Thorp4

  • 1Institute for Health Research and.

Clinical Journal of the American Society of Nephrology : CJASN
|December 29, 2016
PubMed
Summary
This summary is machine-generated.

A new prediction model accurately identifies patients with chronic kidney disease (CKD) at high risk of progressing to kidney failure within five years. This tool aids clinicians in managing CKD progression and planning care.

Keywords:
Antihypertensive AgentsCalibrationColoradoFistulaHemoglobinsHumansPrimary Health CareReferral and ConsultationRenal Insufficiencyalbuminuriablood pressurechronic kidney diseaseclinical prediction rulediabetes mellitusdisease progressionglomerular filtration ratenephrologyprognosisproteinuriarenal failurerenal insufficiency, chronicrenal replacement therapyretrospective studiesrisk assessment

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Area of Science:

  • Nephrology
  • Clinical Prediction Modeling
  • Public Health

Background:

  • Chronic kidney disease (CKD) affects millions, with a minority progressing to end-stage renal disease.
  • Risk stratification is crucial for managing CKD, yet prediction models are underutilized.
  • Developing a pragmatic model for 5-year risk of renal replacement therapy (RRT) in stages 3-4 CKD is needed.

Purpose of the Study:

  • To develop and externally validate a clinically useful prediction model for 5-year RRT risk in patients with stage 3 or 4 CKD.
  • To create a pragmatic risk score using routinely available variables.
  • To aid clinical decision-making regarding nephrology referral and treatment planning.

Main Methods:

  • Retrospective cohort design using two large healthcare system datasets (Kaiser Permanente Northwest and Colorado).
  • Development cohort: 22,460 members with stage 3-4 CKD (2002-2008).
  • Validation cohort: 16,553 members with stage 3-4 CKD (2006-2008).
  • Model predictors included age, sex, eGFR, hemoglobin, proteinuria/albuminuria, systolic BP, antihypertensive medication use, and diabetes complications.

Main Results:

  • The prediction model demonstrated excellent performance in both development (c-statistic=0.96) and external validation (c-statistic=0.95) cohorts.
  • Observed 5-year RRT risks were 4.72% (Northwest) and 2.57% (Colorado).
  • The model showed high sensitivity (92.2%) for identifying high-risk individuals when using the top quintile.

Conclusions:

  • A pragmatic prediction model and risk score for 5-year RRT risk in stage 3-4 CKD were successfully developed and validated.
  • The model incorporates variables readily available in primary care settings.
  • This tool can inform critical clinical decisions, including the timing of nephrology referral and fistula placement.