BMJ  2007;334:1198-1200 (9 June), doi:10.1136/bmj.39226.400694.80

Analysis

Formula estimation of glomerular filtration rate: have we gone wrong?

¹ Department of Biochemistry, Manor Hospital, Walsall WS2 9PS , ² Department of Primary Care and General Practice, University of Birmingham, Birmingham B15 2TT

Paul D Giles and David A Fitzmaurice argue that the introduction of estimated glomerular filtration rate to screen for chronic kidney disease in primary care will lead to pressure on specialist services and create patient anxiety without clear proof of benefit

The first 150 words of the full text of this article appear below.

Chronic kidney disease is a public health problem worldwide.¹ The estimated prevalence of established renal failure is around 1400 per million in the United States and more than 600 per million in the United Kingdom. Patients with chronic kidney disease have increased risk of cardiovascular disease. A test that reliably detects early kidney disease could help minimise cardiovascular disease and renal failure.

Estimating glomerular filtration rate

The best known function of the kidneys is plasma filtration—measured by the glomerular filtration rate (GFR). Many of the kidney's functions are related to GFR (box 1). Inulin clearance and modern isotopic methods are not practical for measuring GFR in routine practice. Creatinine based tests are used instead but have several disadvantages. Creatinine clearance involves timed urine collection and is prone to error. Measuring serum creatinine is easier but this test cannot detect early kidney disease.² Routine reporting of estimated GFR using formulas based on serum creatinine concentration . . . [Full text of this article]

Box 1 Functions of the kidneys related to glomerular filtration rate³
Box 2 Estimating glomerular filtration rate (GFR) using the four variable version of the modification of diet in renal disease equation

Clinical indications for assessing glomerular function

Detecting changes in renal function over time
Disease staging in patients with chronic kidney disease
Detecting chronic kidney disease in mixed populations

Analytical considerations

Conclusion

Summary points

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