Monitoring the GFR


Monitoring the GFR is important in both the hospital and outpatient settings, and several different methodologies are available (Hallan et al., 2006). Glomerular filtration rate (GFR) is determined by glomerular capillary pressure, which is dependent on afferent arteriolar and efferent arteriolar resistance and arterial pressures (Van Biesen et al., 2007). The functional state of the kidneys can be evaluated using several tests based on the renal clearance concept. These tests measure the rates of glomerular filtration, renal blood flow, and tubular reabsorption or secretion of various substances (Macdonald et al., 2006). Some of these tests, such as the measurement of glomerular filtration rate, are routinely used to evaluate kidney function.


To find out the normal level of the Glomerular Filtration Rate (GFR) for Omani population by using serum creatinine level and the collected 24hrs urine.

Review of Literature

Glomerular Filtration Rate

An important measurement in the evaluation of kidney function is the glomerular filtration rate (GFR), the rate at which plasma is filtered by the kidney glomeruli (Proulx et al., 2005). Therefore, substances that are cleared from the plasma with the glomerular filtration only will be providing a measure of the glomerular filtration rate (Bird et al., 2009). Inulin clearance has classically been used as a measure of GFR; however body surface area of a population is a determinant of GFR. Most of the studies determine the GFR to be 110 +/- 15 (SD) mL/min in young females and 125 +/- 15 (SD) mL/min in case of young males (Orita et al., 2005). This standard deviation indicates there is regional variation in GFR throughout the globe. It has been noted that adult values of GFR are attained towards the end of the first year of life, and depending on the population in question, the GFR tends to decline after the age of 45 to 50 years (Swinkels et al., 2000). Serum creatinine is the most widely used marker for GFR, and the GFR is related directly to the urine creatinine excretion and inversely to the serum creatinine (U Cr/PCr) (Sterner et al., 2008). Precise determination of GFR is problematic as commonly used markers, both urea and creatinine have characteristics that affect their accuracy as markers of clearance. Urea clearance is generally an underestimate of GFR because of tubule urea reabsorption and may be as low as one-half of GFR measured by other techniques (Berg, 2006).

Creatinine Clearance

For clinical purposes, the creatinine clearance (CCr) is commonly used to approximate the GFR as follows. The waste product creatinine produced by muscle is filtered at the renal corpuscle and does not undergo reabsorption (Serdar et al., 2001). It does undergo a small amount of secretion, however, so that some plasma is cleared of its creatinine by secretion. Accordingly, the CCr overestimates the GFR but is close enough to be highly useful (Bauer et al., 1982).


Literature suggests measurement of GFR is a commonly used index for detection of deterioration of renal function at the early stage, and therefore, it is important for the clinical practice to have an accurate method of GFR estimation (Stevens et al., 2006). As highlighted earlier, plasma creatinine and creatinine clearance does not provide accurate estimates since plasma creatinine usually does not increase until GFR has decreased by 50% or above (Komenda et al., 2008). The equations that estimate GFR based on creatinine include four variables, plasma creatinine, ethnicity, age, and gender (Murthy et al., 2005). However, ethnicity-based data is not available for Omani population, so this can be used in clinical practice without the risk of error. There is a paucity of literature or standard values on Omani population as opposed to Western population. Therefore, it would be worthwhile to design a study which can measure the standard reference GFR values in normal Omani population that can be compared with abnormal values to ascertain the degree of decrease in the GFR. Race has been recognised to be an important determinant of GFR estimation, and in some cases the measurement is needed to be multiplied by a coefficient to reduce the errors (Jafar et al., 2005). The purpose of this study would be to determine the coefficient for the Omani population.


This will be a study based on experimental cross sectional design. To this end, a sample of 200 Omani adult normal population across Oman will be selected from the community. After ethical clearance, a consent for participation will be sought following verbal explanation and purpose of this study. All the participating adults will be interviewed for their baseline health status, and the findings will be recorded in a customised data sheet.

Flow Chart

Sample Selection

Healthy Adult Omani  Population

Creatinine Clearance:  CCr = UCrV/PCr

GFR Measurement 7GFR = 170 x Pcr -0.999 x age -0.176 x BUN -0.170 x Albumin 0.318 x 0.762 (if female)

Correlation:  CX3 GFR = -15.91 + 1.32 x (7GFR value)

Data Set: Standard Deviation and Factor Calculation for GFR in Omani Population


Flow Chart for Materials and Method


Following that, each of the participants will be asked to collect 24-hour urine sample in a specially designed container for this study. Serum creatinine levels will be determined by Creatinine test electrode method for Beckman CX3 (Rule et al, 2004), GFR equation will be employed to calculate the GFR, and Blood Urea Nitrogen will be measured. BMI is measured to know the body surface area (Du and Du Bois 1916).


The results will be computed individually.  With Beckman CX3 analyser, the plasma creatinine levels were measured on fresh plasma samples. The creatinine clearance will be measured from the equation CCr = UCrV/PCr (Levey et al., 2000). This means the plasma creatinine measured by the Beckman method will be used with the 24 hour creatinine clearance in urine and the urine volume. This will give almost accurate estimate of GFR. The GFR will be measured through the equation 7GFR = 170 x Pcr -0.999 x age -0.176 x BUN -0.170 x Albumin 0.318 x 0.762 (if female) (Zuo et al., 2005). This data can be correlated with the GFR measured by the earlier equation through the regression equation CX3 GFR = -15.91 + 1.32 x (7GFR value) (Lamb et al., 2005). Age and sex specific data can then be collated for each age and sex groups and for a set of data, standard deviation can be calculated to yield the final set of values.


This study would in this way determine the standard GFR values for the Omani population, and this data can be used for further clinical practice. Due to limitation of the sample size, there may be limited generalisability of these data (Stevens and Levey, 2004); however, for making a broader laboratory guideline, a multicentric study with a larger sample size is necessary. Moreover, age and sex has variations which may implicate the results, and this study does not include any criteria or parameter that can discern the GFR irrespective of these parameters.

Reference List

Bauer, JH., Brooks, CS., and Burch, RN., (1982). Clinical appraisal of creatinine clearance as a measurement of glomerular filtration rate. Am J Kidney Dis, ; 2(3): 337-46.

Berg, UB., (2006). Differences in decline in GFR with age between males and females. Reference data on clearances of inulin and PAH in potential kidney donors. Nephrol. Dial. Transplant.; 21: 2577 – 2582.

Bird, NJ., Peters, C., Michell, AR., and Peters, AM., (2009). Effect of extracellular fluid volume on single-sample measurement of glomerular filtration rate

Nephrol. Dial. Transplant., Jan 2009; 24: 104 – 108.

Du BD, Du Bois EF., (1916). A formula to estimate the approximate surface area if height and weight be known. Nutrition 5: 303–311, 1916

Hallan, S., Astor, B., and Lydersen, S., (2006). Estimating glomerular filtration rate in the general population: the second Health Survey of Nord-Trondelag (HUNT II). Nephrol. Dial. Transplant.; 21: 1525 – 1533.

Komenda, P., Beaulieu, M., Seccombe, D., and Levin, A., (2008). Regional Implementation of Creatinine Measurement Standardization. J. Am. Soc. Nephrol.; 19: 164 – 169.

Macdonald, JH., Marcora, SM., Kumwenda, MJ., Jibani, M., Roberts, G., Glover, R., Barron, J., and Lemmey, AB., (2006). The relationship between estimated glomerular filtration rate, demographic and anthropometric variables is mediated by muscle mass in non-diabetic patients with chronic kidney disease. Nephrol. Dial. Transplant; 21: 3488 – 3494.

Orita, Y., Gejyo, F., Sakatsume, M., Shiigai, T., Maeda, Y., Imai, E., Fujii, T., Endoh, M., Jinde, K., Haneda, M., Sugimoto, T., Hishida, A., Takahashi, S., Hosoya, T., Yamamoto, H., Hora, K., Okada, Y., Hosaka, S., Oguchi, T., Kanno, Y., Nishio, Y., Yano, S., Aikawa, K., and Yasui, K., (2005). Estimation of glomerular filtration rate by inulin clearance: comparison with creatinine clearance. Nippon Jinzo Gakkai Shi; 47(7): 804-12.

Jafar, TH., Schmid, Levey, AS., (2005). Serum creatinine as marker of kidney function in South Asians: A study of reduced GFR in adults in Pakistan. J Am Soc Nephrol 16: 1413–1419

Lamb, EJ., Tomson, CR., and Roderick, PJ., (2005). Estimating kidney function in adults using formulae. Ann Clin Biochem 42: 321–345

Levey, AS., Greene, T., Kusek, J., Beck, GJ., and Group, MS., (2000). A simplified equation to predict glomerular filtration rate from serum creatinine. J Am Soc Nephrol 11: A0828.

Murthy, K., Stevens, LA., Stark, PC., and Levey, AS., (2005). Variation in the serum creatinine assay calibration: A practical application to glomerular filtration rate estimation. Kidney Int 68: 1884–1887.

Proulx, NL., Akbari, A., Garg, AX., Rostom, A., Jaffey, J., and Clark, HD., (2005). Measured creatinine clearance from timed urine collections substantially overestimates glomerular filtration rate in patients with liver cirrhosis: a systematic review and individual patient meta-analysis. Nephrol. Dial. Transplant.; 20: 1617 – 1622.

Rule, AD., Larson, TS., Bergstralh, EJ., Slezak, JM., Jacobsen, SJ., and Cosio, FG., (2004). Using serum creatinine to estimate glomerular filtration rate: Accuracy in good health and in chronic kidney disease. Ann Intern Med 141: 929–937

Serdar, MA., Kurt, I., Ozcelik, F., Urhan, M., Ilgan, S., Yenicesu, M., Kenar, L., and Kutluay, T., (2001). A Practical Approach to Glomerular Filtration Rate Measurements: Creatinine Clearance Estimation Using Cimetidine. Ann. Clin. Lab. Sci.; 31: 265 – 273.

Sterner, G., Frennby, B., Mansson, S., Nyman, U., Van Westen, D., and Almen, T., (2008). Determining ‘true’ glomerular filtration rate in healthy adults using infusion of inulin and comparing it with values obtained using other clearance techniques or prediction equations. Scand J Urol Nephrol; 42(3): 278-85.

Stevens, LA. and Levey, AS., (2004). Clinical implications of estimating equations for glomerular filtration rate. Ann Intern Med 141: 959–961

Stevens, LA., Coresh, J., Greene, T., and Levey, AS., (2006). Assessing Kidney Function — Measured and Estimated Glomerular Filtration Rate

N. Engl. J. Med.; 354: 2473 – 2483.

Swinkels, DW., Hendriks, JCM., Nauta, J., and de Jong, M., (2000). Glomerular filtration rate by single-injection inulin clearance: definition of a workable protocol for children. Ann Clin Biochem; 37: 60 – 66

Van Biesen, W., De Bacquer, D., Verbeke, F., Delanghe, J., Lameire, N., and Vanholder, R., (2007). The glomerular filtration rate in an apparently healthy population and its elation with cardiovascular mortality during 10 years. Eur. Heart J.; 28: 478 – 483.

Zuo, L., Ma, YC., Zhou, YH., Wang, M., Xu, GB., and Wang, HY., (2005). Application of GFR-estimating equations in Chinese patients with chronic kidney disease. Am J Kidney Dis 45: 463–472


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