Angela

Angela is 45 years old and has been diagnosed with ADPKD by a kidney ultrasound. Angela has one risk factor that is associated with rapid disease progression: urologic events before age 35. Let's take a closer look with some prognostic tools to assess her likely rate of disease progression.1,2

  • Age45
  • Height5'7"
  • Weight150 lbs
  • SexF
  • Race (AA/O)O

Baseline Assessment3-7

  • Serum creatinine (mg/dL)0.92
  • eGFR (mL/min/1.73m2)75.2
    1
  • Ultrasound kidney length (cm)12.8
    3
  • Hypertension before 35?No
  • Urological event before 35?Yes
  • Family members with ESKD?Yes (70 yrs)
  • MutationsNot available
  • PROPKD ScoreNot available
  • htTKV (mL/m)Not needed
  • Other risk factorsNone
  • ADPKD Imaging ClassificationAngela does not need an MRI or CT scan since she is likely at low risk for rapid progression, as confirmed by her ultrasound kidney length and having only one risk factor.

    Although Angela may not be at risk for ADPKD progression, she needs to be checked for other kidney disease due to history of UTI.

Disease Progression3,6-10

Kidney Size (height adjusted Total Kidney Volume)
Normal htTKV range: 150-250Years303540455055606570mL/m0100200300400500
2
Kidney function (eGFR): 75.2 mL/min/1.73m2
CKD 1CKD 2CKD 3CKD 4CKD 5/ESRDYears303540455055606570mL/min/1.73m²0102030405060708090100
30
35
40
45
50
55
60
65
70

Years

4

Click on the flags below to walk through an assessment of Angela’s likely rate of disease progression

ADPKD=autosomal dominant polycystic kidney disease; AA=African American; O=other; eGFR=estimated glomerular filtration rate; ESKD=end stage kidney disease; PKD=polycystic kidney disease; htTKV=height-adjusted total kidney volume; MRI=magnetic resonance imaging; CT=computed tomography; CKD=chronic kidney disease.
References:
  1. Schrier RW, et al. Predictors of autosomal dominant polycystic kidney disease progression. J Am Soc Nephrol. 2014;25:2399-2418.

  2. Gansevoort RT, et al. Recommendations for the use of tolvaptan in autosomal dominant polycystic kidney disease: a position statement on behalf of the ERA-EDTA Working Groups on Inherited Kidney Disorders and European Renal Best Practice. Nephrol Dial Transplant. 2016;31(3):337-48.

  3. Wetzels JFM, et al. Age- and gender-specific reference values of estimated GFR in caucasians: the Nijmegen biomedical study. Kidney Int. 2007;72:632-637.

  4. Cornec-Le Gall E, et al. The PROPKD score: a new algorithm to predict renal survival in autosomal dominant polycystic kidney disease. J Am Soc Nephrol. 2016;27(3):942-951.

  5. Bhutani H, et al. A comparison of ultrasound and magnetic resonance imaging shows that kidney length predicts chronic kidney disease in autosomal dominant polycystic kidney disease. Kidney Int. 2015;88:146-151.

  6. Imaging classification of ADPKD: a simple model for selecting patients for clinical trials. http://www.mayo.edu/research/documents/pkd-center-adpkd-classification/doc-20094754. Accessed January 09, 2019.

  7. Cheong B, et al. Normal values for renal length and volume as measured by magnetic resonance imaging. Clin J Am Soc Nephrol. 2007;2:38-45.

  8. Levey AS, et al. Definition and classification of chronic kidney disease: a position statement from kidney disease: improving global outcomes (KDIGO). Kidney Int. 2005;67:2089-2100.

  9. PKD Charity. Fast Facts about ADPKD. The Polycystic Kidney Disease Charity. 2017. https://pkdcharity.org.uk/about-adpkd/just-diagnosed/fast-facts-about-adpkd Accessed January 09, 2019.

  10. Rangan GK, et al. Autosomal dominant polycystic kidney disease: a path forward. Semin Nephrol. 2015;35(6):524-537.

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