Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

An alternative formula to the Cockcroft-Gault and the modification of diet in renal diseases formulas in predicting

Hassan Ibrahim1, Michael Mondress, Abel Tello

  • 1Division of Renal Diseases and Hypertension, School of Public Health, University of Minnesota, Minneapolis, MN, USA. ibrah007@umn.edu

Journal of the American Society of Nephrology : JASN
|February 18, 2005
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Identification of compounds that repress DUX4 expression in facioscapulohumeral muscular dystrophy.

Scientific reports·2026
Same author

Mechanistic Insights into Dihydromyricetin: Redox Modulation and Kinase-Mediated Control of Disease Pathogenesis.

International journal of molecular sciences·2026
Same author

Esthetic evaluation of immediate implants in the maxillary anterior region.

Bioinformation·2026
Same author

Artificial Intelligence in Low-Dose Computed Tomography Lung Cancer Screening: Clinical Integration, Validation, and Translational Challenges.

Cureus·2026
Same author

Serum Uric Acid as a Biomarker for Incident Type 2 Diabetes Mellitus: A 6-Year Cohort Study in Qatar.

Metabolites·2026
Same author

Tracking the evolution of biomarker efficacy in SARS-CoV-2: a global meta-analyses series.

Respiratory research·2026

Common formulas for estimating kidney function (GFR) are inaccurate in people with diabetes. Refitting the MDRD formula improved accuracy, but variability remained, highlighting the need for better GFR estimation in diabetic kidney disease.

Area of Science:

  • Nephrology
  • Endocrinology
  • Cardiovascular Medicine

Background:

  • Chronic kidney disease (CKD) is increasing, leading to end-stage renal disease (ESRD) and heightened cardiovascular disease (CVD) risk.
  • Glomerular filtration rate (GFR) is the gold standard for assessing kidney function but is expensive and difficult to measure.
  • Existing GFR estimation formulas based on serum creatinine lack validation in large diabetic cohorts.

Purpose of the Study:

  • To evaluate the performance of the abbreviated Modification of Diet in Renal Disease (MDRD) study formula and the Cockcroft-Gault equation for estimating GFR in individuals with type 1 diabetes.
  • To compare these estimations against measured GFR using iothalamate clearance.
  • To assess the accuracy, bias, and precision of these formulas in a large diabetic cohort.

Main Methods:

Related Experiment Videos

  • Utilized data from 1286 individuals with type 1 diabetes from the Diabetes Control and Complications Trial (DCCT).
  • Compared estimated GFR (eGFR) from MDRD and Cockcroft-Gault formulas against measured GFR (mGFR) via iothalamate clearance.
  • Assessed performance using bias, precision, and accuracy metrics, including the percentage of estimates within +/-10% of mGFR.

Main Results:

  • Both MDRD and Cockcroft-Gault formulas demonstrated significant bias and high variability when applied to the DCCT cohort.
  • MDRD substantially underestimated iothalamate GFR; Cockcroft-Gault showed underestimation below 120 ml/min/1.73 m² and overestimation above 130 ml/min/1.73 m².
  • Only one-third of estimates were within +/-10% of measured GFR, potentially flagging early kidney function decline inaccurately.

Conclusions:

  • Standard GFR estimation formulas are unreliable in individuals with type 1 diabetes due to differences in creatinine levels and excretion.
  • Refitting the MDRD formula to the DCCT data significantly improved GFR prediction accuracy to 56% within +/-10% of measured GFR.
  • Despite improvements, substantial variability in eGFR estimates persists, indicating a need for refined GFR estimation methods in diabetic kidney disease.