CKD Risk Calculators


Below are two tools:

Calculator 1: Risk of Chronic Kidney Disease (CKD) in adults
For adults who don’t know if they have chronic kidney disease (CKD), Calculator 1 estimates the probability of having CKD (Bang et al., 2007)
  • The calculation is based on individual characteristics: age, sex, and 7 comorbidities including hypertension, diabetes and cardiovascular disease.

Calculator 2: Risk of progression of CKD to kidney failure among those who already have CKD
For adults who know they have CKD (estimated glomerular filtration rate [eGFR] <60 mL/min/1.73m2), Calculator 2 estimates the probability of progression of CKD to kidney failure in the next two or five years using a 4- or 8-variable equation (Tangri et al., 2011)
  • The 4-variable equation is based on individual characteristics: age, sex, eGFR and Urine Albumin to Creatinine Ratio (UACR)
  • The 8-variable equation also includes four laboratory tests (serum calcium, phosphate, bicarbonate, and albumin).

The intended audience is medical researchers and clinicians; the calculators should only be used by laypersons to begin dialog with their care provider. These equations should not be used for self-diagnosis or self-management.



The CKD Risk Calculators are designed for use on devices with larger displays. Please visit this page on a tablet, laptop, or desktop device.

Probability of CKD

This calculator returns the probability (expressed as a percentage from 0 to 100%) of having Stage 3-5 CKD, defined as an estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73m2, based on nine input variables1. If one or more of the values is unknown, trying different combinations of the presence or absence of the unknown characteristics will give a range of possible estimates. An elevated probability of CKD should prompt individuals to seek more comprehensive medical advice, possibly leading to further medical evaluation, earlier diagnosis and interventions to both manage the condition and slow its progression.

Details of the risk equation development (Bang et al, 2007) are available here: https://www.ncbi.nlm.nih.gov/pubmed/17325299.


Characteristic This Person U.S. National
Average
Enter Age and Sex:
Age (required):
Sex (required):
Sex  
Enter any of the following characteristics that may increase the probability of CKD:
Anemia:
Anemia  
Hypertension:
Hypertension  
(41%)
Diabetes:
Diabetes  
Dabetes Description Help
(10%)
Cardiovascular Disease (CVD):
CVD  
(8%)
Congestive Heart Failure (CHF):
CHF  
Peripheral Vascular Disease (PVD):
PVD  
Proteinuria:2
Proteinuria  
(10%)




Probability of having Stage 3-5 Chronic Kidney Disease (CKD) (expressed as a percentage between 0% and 100%):

In order to show a chart of the calculations, the following are required:
  • Age
  • Sex
1 Probability (CKD) = 1/[1 + exp(-β’ x X)], where β’ x X = -5.4 + 1.55 x (age of 50-59 years) + 2.31 x (age of 60-69 years) + 3.23 x (age ≥ 70 years) + 0.29 x (female) + 0.93 x (anemia) + 0.45 x (hypertension) + 0.44 x (DM) + 0.59 x (history of CVD) + 0.45 x (history of CHF) + 0.74 x (PVD) + 0.83 x (proteinuria), where (a) is an indicator taking 1 for event a and 0 otherwise. In this equation, β and X denote vectors of β-coefficients and risk factors used in this equation, respectively.

2 Proteinuria is a broad term for leakage of protein in the kidney. Although the Bang et al. paper uses the term proteinuria, the actual measurement was of albuminuria. Albumin is a protein found in the blood. A healthy kidney does not let albumin pass from the blood into the urine. Too much albumin in your urine is called albuminuria.


References and Sources:

Bang H, Vupputuri S, Shoham DA, Klemmer PJ, Falk RJ, Mazumdar M, Gipson D, Colindres RE, Kshirsagar AV. SCreening for Occult REnal Disease (SCORED): A simple prediction model for chronic kidney disease. Arch Intern Med. 2007 Feb 26;167(4):374-81.
www.ncbi.nlm.nih.gov/pubmed/17325299
Progression of CKD

For patients with chronic kidney disease (i.e., those with estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73m2), this calculator returns an estimated probability of developing kidney failure in the next two or five years (expressed as a percentage, or a range of percentages, from 0% to 100%). These probabilities could be used to facilitate patient and provider communication, to heighten awareness and guide optimal disease management for best outcomes.

Two versions of this calculator are provided, one with four input variables, and one with eight input variables. Using more variables, when available, will yield a more precise estimate. The ‘sliders’ for each laboratory variable in the data entry table below allow a range of values to be selected in case of uncertainty in a single value. Details of risk equation development (Tangri et al., 2011) are available here: https://www.ncbi.nlm.nih.gov/pubmed/21482743.


Sex (required):


Reset eGFR slider values to original

(Range: 10-60)

Reset Albumin/Creatinine slider values to original









Estimated probability of progression to end-stage renal disease (ESRD) in CKD patients at 2 and 5 years (expressed as a percentage between 0% and 100%):

In order to show a chart of the calculations, the following are required:
  • Age
  • Sex


References and Sources:

Tangri, Navdeep, et al. Multinational assessment of accuracy of equations for predicting risk of kidney failure: a meta-analysis JAMA 315.2(2016):164-174. supplement

Tangri N, Stevens LA, Griffith J, Tighiouart H, Djurdjev O, Naimark D, Levin A, Levey AS. A predictive model for progression of chronic kidney disease to kidney failure. JAMA. 2011 Apr 20;305(15):1553-9. doi: 10.1001/jama.2011.451. Epub 2011 Apr 11.
www.ncbi.nlm.nih.gov/pubmed/21482743