Optimized robust plasma sampling for glomerular filtration rate studies

Nucl Med Commun. 2012 Sep;33(9):995-1001. doi: 10.1097/MNM.0b013e328356fb6d.


In the presence of abnormal fluid collection (e.g. ascites), the measurement of glomerular filtration rate (GFR) based on a small number (1-4) of plasma samples fails. This study investigated how a few samples will allow adequate characterization of plasma clearance to give a robust and accurate GFR measurement. A total of 68 nine-sample GFR tests (from 45 oncology patients) with abnormal clearance of a glomerular tracer were audited to develop a Monte Carlo model. This was used to generate 20 000 synthetic but clinically realistic clearance curves, which were sampled at the 10 time points suggested by the British Nuclear Medicine Society. All combinations comprising between four and 10 samples were then used to estimate the area under the clearance curve by nonlinear regression. The audited clinical plasma curves were all well represented pragmatically as biexponential curves. The area under the curve can be well estimated using as few as five judiciously timed samples (5, 10, 15, 90 and 180 min). Several seven-sample schedules (e.g. 5, 10, 15, 60, 90, 180 and 240 min) are tolerant to any one sample being discounted without significant loss of accuracy or precision. A research tool has been developed that can be used to estimate the accuracy and precision of any pattern of plasma sampling in the presence of 'third-space' kinetics. This could also be used clinically to estimate the accuracy and precision of GFR calculated from mistimed or incomplete sets of samples. It has been used to identify optimized plasma sampling schedules for GFR measurement.

MeSH terms

  • Adolescent
  • Adult
  • Area Under Curve
  • Blood Specimen Collection / methods*
  • Child
  • Child, Preschool
  • Data Interpretation, Statistical
  • Female
  • Glomerular Filtration Rate*
  • Humans
  • Infant
  • Male
  • Monte Carlo Method
  • Plasma / metabolism*
  • Retrospective Studies
  • Young Adult