Introduction
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.
Objective
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).
Variations
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.
Methodology
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
Tabulation
Flow Chart for Materials and Method
Measures
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).
Results
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.
Conclusion
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.
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