 |
||||
| 2008 JASN IMPACT FACTOR 7.505 | HOME AUTHOR INFO EDITORIAL BOARD SUBSCRIBE FEEDBACK ALERTS HELP | |||
| CURRENT ISSUE | ARCHIVES | JASN Express | ONLINE SUBMISSION | |
|
||||
| 2008 JASN IMPACT FACTOR 7.505 | HOME AUTHOR INFO EDITORIAL BOARD SUBSCRIBE FEEDBACK ALERTS HELP | |||
| CURRENT ISSUE | ARCHIVES | JASN Express | ONLINE SUBMISSION | |
CLINICAL SCIENCE |
Renal Division, Brigham and Women’s Hospital, Boston, Massachusetts
Correspondence to Dr. Julie Lin, Renal Division, Brigham and Women’s Hospital, 75 Francis Street, Boston, MA 02115. Phone: 617-732-6432; Fax: 617-734-7042;
 |
Abstract |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
|
Introduction |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
In 1999, a new prediction equation derived from 1628 subjects with renal insufficiency enrolled in the MDRD study was published (2). This equation has been subsequently evaluated in (1) blacks with chronic kidney disease (CKD) (3), (2) scleroderma patients (4), (3) potential renal transplant donors with CrCl <80 ml/min by two 24-h urine collections (5), (4) patients with kidney disease and normal serum creatinine (SCr) levels (
1.5 mg/dl) (6), and (5) 46 normal and 46 individuals with type 1 diabetes without evidence of nephropathy (7). In 2000, a simplified MDRD equation (MDRD 2) was published in abstract form that used SCr as the only serum assay (8). To our knowledge, this is the only published study that tests the MDRD 2 equation in people without renal disease compared with actual GFR measurements.
|
Materials and Methods |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Subjects who underwent 125I-iothalamate studies at BWH were asked to fast for at least 8 h and given a water load of 10 ml/kg and 5 drops of potassium iodide diluted in 15 ml of water orally (to block thyroid uptake of 125I-iothalamate) at the initiation of the study. Thirty-five micro-Curies of 125I-iothalamate was injected subcutaneously into the upper arm. Blood was drawn and urine was sampled at time 0 (before 125I-iothalamate injection) and at 60, 120, and 180 min. Total urine volume and urinary flow rates were assessed every 60 min. Oral fluid hydration was administered at 500 ml/h as tolerated. GFR measurements for two timed urine collections were averaged and standardized for a body surface area (BSA) of 1.73 m2. Intra-assay coefficients of variation (CV) were 10% for 40 of the 55 iothalamate subjects and 
10% for the remaining 15 subjects. Forty-six subjects had CV of 15%. For those with CV 15%, the recorded minimum urinary flow rates ranged from 1.1 to 2.8 ml/min. The acceptable minimum urinary flow rate in the original protocol was 3 ml/min; if this was not achieved at time 60 min, then urine was collected at time 90 min and urinary flow rate was calculated at this time.
Individuals who underwent 99mTc-DTPA studies were hydrated orally or intravenously at 10 ml/kg per h for 30 min before study initiation. 99mTc-DTPA dosed at 50 µCi/kg was injected intravenously, and blood was sampled at 120, 180, and 240 min. Three GFR measurements were averaged and standardized for a BSA of 1.73 m2. No information on intra-assay CV was available for 99mTc-DTPA studies.
Forty-one of 45 subjects who had 99mTc-DTPA studies had their SCr levels measured from their primary care provider’s office at a wide variety of laboratories; the remaining four patients had SCr assayed at the BWH laboratory. For subjects who underwent 125I-iothalamate testing, 45 of 55 (82%) SCr levels were assayed at the BWH, and the remainder were obtained through different outside laboratories. The BWH laboratory used alkaline picrate reactions with a DAX96 (Bayer) machine to measure SCr through January 31, 2000, and an Olympus 640/2700 machine from February 1, 2000, to the present. The reference normal values for SCr were 0.8 to 1.6 mg/dl in men and 0.8 to 1.3 mg/dl in women from 1992 through September 1999. This changed to 0.7 to 1.3 mg/dl for both men and women starting in September 1999. The laboratory reports that the CV of the assay is 3% for measurements in the normal range.
The prediction equations that we used are listed as follows:
Fisher’s exact test was used for proportions and t test for comparison of means. A Pearson correlation coefficient was also calculated for the normally distributed GFR data (Shapiro-Wilk test for normality, P = 0.98).
The mean and median absolute differences were calculated from absolute difference = predicted value - measured value. The % absolute difference was calculated as % absolute difference = predicted value - measured value x 100 measured value.
Bias, a measure of systematic error, was defined by the mean prediction error (ME): 
|
|
where pei = predicted value - true value and n = sample size.
The R2 statistic was derived by simple linear regression (PROC GLM) and reflects the predictive ability of the model. P = 0.05 was considered significant.
Refitting of the log-linear MDRD equation to our data set was performed with the following code using PROC REG in SAS:
SAS for Windows version 8.0 (Cary, NC) was used for all statistical calculations. Data collection by chart review was approved by the BWH Institutional Review Board.
|
Results |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
|
|
|
30 (n = 73). No improvements were noted in any of the parameters examined in any of the equations (data not shown). Refitting of the MDRD equation parameter estimates to our data set resulted in the following prediction equations:
|
Discussion |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
|
Third, we have confirmed that the simplified MDRD 2 equation loses very little predictive ability when compared with MDRD 1. Because serum albumin and BUN measurements may not be readily available, especially in the research setting, MDRD 2 is the prediction equation of choice over MDRD 1 in these situations. Likewise, estimating GFR from the CG CrCl calculation does not appreciably improve the predictive ability of the CG equation.
Last, 125I-iothalamate and 99mTc-DTPA techniques do not seem to be highly correlated with each other because the degree of bias, precision, linear correlation, and accuracy varied notably when the results were pooled (Table 2) rather than stratified by type of GFR testing (Table 3). The decreased precision observed when all 100 subjects were pooled for analysis may reflect the interassay variability that was conferred by using two different measurements of GFR for reference. However, high correlations of both 125I-iothalamate and 99mTc-DTPA to simultaneous measures of inulin clearance have been reported (r > 0.90) (16), although 125I-iothalamate measurements exceeded inulin measurements by 14.6 to 25.9 ml/min per 1.73 m2 (16) and 99mTc-DTPA overestimated inulin clearance by 3.5 to 13.5 ml/min per 1.73 m2 for (16,17). Therefore, analyses of prediction equations must take into account the type of GFR measurement, and caution should be used when comparing results of such investigations using diverse GFR measurement techniques. In this study, other factors that may have influenced the different correlations between 125I-iothalamate and 99mTc-DTPA include the higher numbers of blacks and lower mean weights in the 125I-iothalamate group.
The MDRD equations had the least bias and highest accuracy when compared with 125I-iothalamate measurements. This is not surprising considering that these equations were derived using 125I-iothalamate GFR measurements. The CG equation is understandably poorer, because it was derived by CrCl calculated by 24-h urinary creatinine collections as the "gold standard" in 249 adults ages 18 to 92 with mean SCr 0.99 to 1.78 mg/dl (9). In this original study, 96% of study subjects were male, and no information on race was given; this raises the issue of the generalizability of the CG prediction equations. The use of 24-h urine collection as the "gold standard" was also suboptimal because multiple investigations have reported the inaccuracies of using 24-h urine collections to measure CrCl, usually from under- or overcollection by the subject (5,18,19). In fact, Coresh et al. (20) concluded that there was no advantage in 24-h urine collection over the CG estimations when compared with GFR determined by 125I-iothalamate clearance.
Hsu et al. (21) reported finding systematic differences in SCr levels measured at BWH among those measured during 1997 and during 1998 when compared with values measured before 1997; therefore, the investigators adjusted their analysis by adding 0.1 mg/dl to SCr values measured in 1997 and 0.3 mg/dl to values measured in 1998. In our data set, 35 of the 45 SCr assayed at BWH in the 125I-iothalamate group were performed in 1998 or later, whereas all four of the SCr assayed at BWH in the 99mTc-DTPA group were performed after 1998. Because the vast majority of 125I-iothalamate patients were assayed between 1998 and 2000 and because there is no information (either published or provided by the BWH laboratory) of how SCr assays after 1998 are related to those performed before 1998, we did not attempt to adjust SCr and recalculate the prediction equations, although this is another likely source of measurement error.
The issue of calibration of SCr laboratory measurement is especially critical when estimating GFR in subjects with normal or mildly impaired renal function because small changes in SCr result in large changes in calculated CrCl and GFR. For example, a 40-yr-old black woman who weighs 70 kg and has a SCr of 1.0 mg/dl in steady state has a calculated CrCl of 82.6 ml/min and a calculated GFR of 78.3 ml/min per 1.73 m2; an increase of SCr by 0.1 mg/dl to 1.1 mg/dl results in a calculated CrCl of 75.1 ml/min and a calculated GFR of 71.2 ml/min per 1.73 m2. In contrast, the same patient with a SCr of 3.1 mg/dl in steady state would have an estimated CrCl of 27.5 ml/min and an estimated GFR of 26.1 ml/min per 1.73 m2; an increase in SCr to 3.2 mg/d results in very small changes in estimates to 26.7 ml/min and 25.3 ml/min per 1.73 m2 for CrCl and GFR, respectively. There is no standard calibration for SCr measurements for laboratories in the United States (22), and investigators have reported that SCr on the same stored serum samples were 0.23 mg/dl higher when assayed by the laboratory used by Third National Health and Nutrition Examination Survey study when compared with the values obtained by the laboratory used by the MDRD study, a magnitude of difference that was common across different laboratories (18).
Other potential sources of measurement error include (1) intraindividual variability in SCr; (2) intraindividual variability in other clinical or laboratory measurements; (3) intraindividual variability in GFR; and (4) intra-assay variability in GFR measurement. Despite the 125I-iothalamate protocol requirements for minimum urinary flow rates of 3 ml/min, this was not achieved in all nine subjects who had CV 15%. Intra-assay GFR measurement errors are likely minimized in those who underwent 125I-iothalamate testing with CV 10%; however, in those with high CV and those who underwent 99mTc-DTPA studies without reported intra-assay CV, we acknowledge that the questionable quality of some of the GFR measurements may not make it a true and reliable "gold standard."
In refitting the MDRD coefficients to our data, we found that the intercept terms are different for both MDRD 1 and MDRD 2, suggesting that, as expected, our study population varies considerably from the original cohort in which these equations were derived. Furthermore, the regression coefficients for all laboratory assays (Scr, BUN, and alb) are also considerably different, likely reflecting lack of calibration in a central laboratory and measurement error, whereas the regression coefficients for age and gender are similar. The coefficient for black race is in the opposite direction of those in the MDRD equations but are based on only 10 blacks. Using the MDRD predictors of GFR resulted in models that explain only 8 to 10% of the variance in our data set of normal subjects, which is not surprising in light of the relatively small sample size of 100 subjects and the various sources of measurement error as previously discussed, especially those involving SCr calibration.
Our results are consistent with other published investigations in the literature (Table 4). A study by Bostom et al. (6) of 109 patients with known kidney disease and SCr 1.5 mg/dl reported an R2 of 0.31 for MDRD1, 0.29 for MDRD 2, and 0.17 for CG (Table 4). The Bostom study differed from this current study on several points: it included patients with renal disease, there was a narrower range of weights among the subjects, the majority of subjects had some degree of proteinuria, and iohexol was used to determine GFR (Table 4). Despite the "normal serum creatinine levels" (range, 1.0 to 1.3 mg/dl), measured GFR by iohexol was as low as 18 ml/min per 1.73 m2 (25th to 75th percentile range was 88 to 138 ml/min per 1.73 m2). In addition, 25% had iohexol GFR <80 ml/min per 1.73 m2, and 59% had glomerular disease, whereas our cohort were healthy, normal adults.
Another recent study of 46 healthy adults and 46 individuals who had type 1 diabetes without evidence of nephropathy and underwent inulin clearance studies found median absolute differences of 10.7 versus 9.0, respectively, when comparing MDRD 1 and CG equations in healthy subjects; the CG equation was corrected to reflect GFR by either a multiplication factor of 0.9 and the formula Y = -0.004 + 1.54 (Table 4) (7). No analyses of bias, precision, or accuracy were presented (7). On the basis of the higher median absolute differences in the MDRD 1 equation compared with the CG equation for all subjects, the authors concluded that the MDRD 1 equation underestimated GFR, especially in women with diabetes, and that the MDRD 1 equation was less "accurate" than the CG equation. Whereas we also found that the MDRD 1 equation consistently underestimated GFR measurements (most notably in those who underwent 99mTc-DTPA), we observed that the MDRD equations were less biased, more precise, and more accurate than the CG equation.
Several limitations of this study should be noted. First, very few black individuals were included, so the findings may not be generalizable to this group. Second, these analyses were performed on a relatively small sample size with wide variability in clinical and laboratory parameters. Our study participants, however, are likely representative of the general population with normal or mildly decreased kidney function. Third, SCr measurements were not performed at the same time in the same laboratory and were not calibrated with a standardized measurement, although the vast majority (82%) of those who underwent 125I-iothalamate studies had SCr measured in the same BWH laboratory with a low reported CV. Despite these limitations, however, this is the first study to evaluate rigorously these GFR formulas in healthy individuals without chronic kidney disease. Moreover, the lack of calibration of SCr across different laboratories continues to be a reality that physicians face daily in clinical practice.
In addition to the inaccuracies of the formulas themselves, this study underscores how multiple sources of measurement error (including intra-assay SCr variability, intraindividual Scr variability, lack of calibration of Scr assays across different laboratories, intra-assay GFR variability, intraindividual GFR variability, and measurement error of other variables in the prediction equations) can affect the precision and accuracy of renal clearance prediction equations. In the future, researchers and clinicians would greatly benefit from a study of a large and racially diverse cohort of people with normal or mildly impaired kidney function that would allow investigators to derive an improved prediction equation for estimating GFR.
|
Acknowledgments |
|---|
|
References |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
This article has been cited by other articles:
 |
|
 |
|
  C. Zoccali, A. Kramer, and K. J. Jager Chronic kidney disease and end-stage renal disease--a review produced to contribute to the report 'the status of health in the European union: towards a healthier Europe' NDT Plus, October 12, 2009; (2009) sfp127v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. Tsinalis and G. T. Thiel An easy to calculate equation to estimate GFR based on inulin clearance Nephrol. Dial. Transplant., October 1, 2009; 24(10): 3055 - 3061. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. Hanai, T. Babazono, I. Nyumura, K. Toya, N. Tanaka, M. Tanaka, A. Ishii, and Y. Iwamoto Asymmetric dimethylarginine is closely associated with the development and progression of nephropathy in patients with type 2 diabetes Nephrol. Dial. Transplant., June 1, 2009; 24(6): 1884 - 1888. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Pizzarelli, F. Lauretani, S. Bandinelli, G. B. Windham, A. M. Corsi, S. V. Giannelli, L. Ferrucci, and J. M. Guralnik Predictivity of survival according to different equations for estimating renal function in community-dwelling elderly subjects Nephrol. Dial. Transplant., April 1, 2009; 24(4): 1197 - 1205. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Najafi, H. Goodarzynejad, A. Karimi, A. Ghiasi, H. Soltaninia, M. Marzban, A. Salehiomran, B. Alinejad, and M. Soleymanzadeh Is preoperative serum creatinine a reliable indicator of outcome in patients undergoing coronary artery bypass surgery? J. Thorac. Cardiovasc. Surg., February 1, 2009; 137(2): 304 - 308. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. R. den Hartog, P. P. Reese, B. Cizman, and H. I. Feldman The Costs and Benefits of Automatic Estimated Glomerular Filtration Rate Reporting Clin. J. Am. Soc. Nephrol., February 1, 2009; 4(2): 419 - 427. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. P. Moranville and H. R. Jennings Implications of using modification of diet in renal disease versus Cockcroft-Gault equations for renal dosing adjustments Am. J. Health Syst. Pharm., January 15, 2009; 66(2): 154 - 161. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A M. Peters, N. J Bird, I. Halsall, C. Peters, and A R. Michell Evaluation of the Modification of Diet in Renal Disease equation (eGFR) against simultaneous, dual-marker multi-sample measurements of glomerular filtration rate Ann Clin Biochem, January 1, 2009; 46(1): 58 - 64. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. Douville, A. R. Martel, J. Talbot, S. Desmeules, S. Langlois, and M. Agharazii Impact of age on glomerular filtration estimates Nephrol. Dial. Transplant., January 1, 2009; 24(1): 97 - 103. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. H. Brantsma, S. J. L. Bakker, H. L. Hillege, D. de Zeeuw, P. E. de Jong, R. T. Gansevoort, and for the PREVEND Study Group Cardiovascular and renal outcome in subjects with K/DOQI stage 1-3 chronic kidney disease: the importance of urinary albumin excretion Nephrol. Dial. Transplant., December 1, 2008; 23(12): 3851 - 3858. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Lin and G. C. Curhan Kidney function decline and physical function in women Nephrol. Dial. Transplant., September 1, 2008; 23(9): 2827 - 2833. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 N. Kasitanon, D.M. Fine, M. Haas, L.S. Magder, and M. Petri Estimating renal function in lupus nephritis: comparison of the Modification of Diet in Renal Disease and Cockcroft Gault equations Lupus, November 1, 2007; 16(11): 887 - 895. [Abstract] [PDF]
|
|
|
|
|
|
J. K. Inrig, B. S. Gillespie, U. D. Patel, L. P. Briley, L. She, J. D. Easton, E. Topol, and L. A. Szczech Risk for Cardiovascular Outcomes among Subjects with Atherosclerotic Cardiovascular Disease and Greater-than-Normal Estimated Glomerular Filtration Rate Clin. J. Am. Soc. Nephrol., November 1, 2007; 2(6): 1215 - 1222. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. J. Falk, L. L. Hamm, M. A. Josephson, S. Adler, and A. K. Singh The Nephrology Quiz and Questionnaire: 2006 Clin. J. Am. Soc. Nephrol., November 1, 2007; 2(6): 1375 - 1388. [Full Text] [PDF]
|
|
|
|
 |
|
 S. Gao, B. J. Manns, B. F. Culleton, M. Tonelli, H. Quan, L. Crowshoe, W. A. Ghali, L. W. Svenson, B. R. Hemmelgarn, and for the Alberta Kidney Disease Network Prevalence of Chronic Kidney Disease and Survival among Aboriginal People J. Am. Soc. Nephrol., November 1, 2007; 18(11): 2953 - 2959. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. Del Duca, S. Iqbal, E. Rahme, P. Goldberg, and B. de Varennes Renal Failure After Cardiac Surgery: Timing of Cardiac Catheterization and Other Perioperative Risk Factors Ann. Thorac. Surg., October 1, 2007; 84(4): 1264 - 1271. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. A. Stevens, J. Coresh, H. I. Feldman, T. Greene, J. P. Lash, R. G. Nelson, M. Rahman, A. E. Deysher, Y. Zhang, C. H. Schmid, et al. Evaluation of the Modification of Diet in Renal Disease Study Equation in a Large Diverse Population J. Am. Soc. Nephrol., October 1, 2007; 18(10): 2749 - 2757. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Zahran, M. Qureshi, and A. Shoker Comparison between creatinine and cystatin C-based GFR equations in renal transplantation Nephrol. Dial. Transplant., September 1, 2007; 22(9): 2659 - 2668. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. Charytan, J. P. Forman, and D. E. Cutlip Risk of target lesion revascularization after coronary stenting in patients with and without chronic kidney disease Nephrol. Dial. Transplant., September 1, 2007; 22(9): 2578 - 2585. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Kaestner and G. Sewell Dose-banding of carboplatin: rationale and proposed banding scheme Journal of Oncology Pharmacy Practice, June 1, 2007; 13(2): 109 - 117. [Abstract] [PDF]
|
|
|
|
 |
|
 A. S. Levey, J. Coresh, T. Greene, J. Marsh, L. A. Stevens, J. W. Kusek, F. Van Lente, and for Chronic Kidney Disease Epidemiology Collaborat Expressing the Modification of Diet in Renal Disease Study Equation for Estimating Glomerular Filtration Rate with Standardized Serum Creatinine Values Clin. Chem., April 1, 2007; 53(4): 766 - 772. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. L. Xue, P. W. Eggers, L. Y. Agodoa, R. N. Foley, and A. J. Collins Longitudinal Study of Racial and Ethnic Differences in Developing End-Stage Renal Disease among Aged Medicare Beneficiaries J. Am. Soc. Nephrol., April 1, 2007; 18(4): 1299 - 1306. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R. A. Chudleigh, G. Dunseath, W. Evans, J. N. Harvey, P. Evans, R. Ollerton, and D. R. Owens How Reliable Is Estimation of Glomerular Filtration Rate at Diagnosis of Type 2 Diabetes? Diabetes Care, February 1, 2007; 30(2): 300 - 305. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. E. McClintock, L. B. Ware, M. D. Eisner, N. Wickersham, B. T. Thompson, M. A. Matthay, and the National Heart, Lung, and Blood Institute ARDS Higher Urine Nitric Oxide Is Associated with Improved Outcomes in Patients with Acute Lung Injury Am. J. Respir. Crit. Care Med., February 1, 2007; 175(3): 256 - 262. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. H. Macdonald, S. M. Marcora, M. Jibani, G. Roberts, M. J. Kumwenda, R. Glover, J. Barron, and A. B. Lemmey Bioelectrical impedance can be used to predict muscle mass and hence improve estimation of glomerular filtration rate in non-diabetic patients with chronic kidney disease Nephrol. Dial. Transplant., December 1, 2006; 21(12): 3481 - 3487. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. M. Rainey Automatic Reporting of Estimated Glomerular Filtration Rate--Jumping the Gun? Clin. Chem., December 1, 2006; 52(12): 2184 - 2187. [Full Text] [PDF]
|
|
|
|
|
|
A. S. Levey, L. A. Stevens, and T. Hostetter Automatic Reporting of Estimated Glomerular Filtration Rate--Just What the Doctor Ordered Clin. Chem., December 1, 2006; 52(12): 2188 - 2193. [Full Text] [PDF]
|
|
|
|
 |
|
 A. D. Rule, R. J. Rodeheffer, T. S. Larson, J. C. Burnett Jr, F. G. Cosio, S. T. Turner, and S. J. Jacobsen Limitations of Estimating Glomerular Filtration Rate From Serum Creatinine in the General Population Mayo Clin. Proc., November 1, 2006; 81(11): 1427 - 1434. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. D.J. Smilde, D. J. van Veldhuisen, G. Navis, A. A. Voors, and H. L. Hillege Drawbacks and Prognostic Value of Formulas Estimating Renal Function in Patients With Chronic Heart Failure and Systolic Dysfunction Circulation, October 10, 2006; 114(15): 1572 - 1580. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
X. Wang, J. Lewis, L. Appel, D. Cheek, G. Contreras, M. Faulkner, H. Feldman, J. Gassman, J. Lea, J. Kopple, et al. Validation of Creatinine-Based Estimates of GFR When Evaluating Risk Factors in Longitudinal Studies of Kidney Disease J. Am. Soc. Nephrol., October 1, 2006; 17(10): 2900 - 2909. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 F. C. Brosius III, T. H. Hostetter, E. Kelepouris, M. M. Mitsnefes, S. M. Moe, M. A. Moore, S. Pennathur, G. L. Smith, and P. W.F. Wilson REPRINT Detection of Chronic Kidney Disease in Patients With or at Increased Risk of Cardiovascular Disease: A Science Advisory From the American Heart Association Kidney and Cardiovascular Disease Council; the Councils on High Blood Pressure Research, Cardiovascular Disease in the Young, and Epidemiology and Prevention; and the Quality of Care and Outcomes Research Interdisciplinary Working Group: Developed in Collaboration With the National Kidney Foundation Hypertension, October 1, 2006; 48(4): 751 - 755. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. A. Leopold Small-Molecule Glycoprotein IIb/IIIa Antagonists and Bleeding Risk in Women: Too Much of a Good Thing? Circulation, September 26, 2006; 114(13): 1344 - 1346. [Full Text] [PDF]
|
|
|
|
|
|
F. C. Brosius III, T. H. Hostetter, E. Kelepouris, M. M. Mitsnefes, S. M. Moe, M. A. Moore, S. Pennathur, G. L. Smith, and P. W.F. Wilson Detection of Chronic Kidney Disease in Patients With or at Increased Risk of Cardiovascular Disease: A Science Advisory From the American Heart Association Kidney and Cardiovascular Disease Council; the Councils on High Blood Pressure Research, Cardiovascular Disease in the Young, and Epidemiology and Prevention; and the Quality of Care and Outcomes Research Interdisciplinary Working Group: Developed in Collaboration With the National Kidney Foundation Circulation, September 5, 2006; 114(10): 1083 - 1087. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. E. de Jong, N. Halbesma, and R. T. Gansevoort Screening for early chronic kidney disease--what method fits best? Nephrol. Dial. Transplant., September 1, 2006; 21(9): 2358 - 2361. [Full Text] [PDF]
|
|
|
|
 |
|
 A. S. Levey, J. Coresh, T. Greene, L. A. Stevens, Y. Zhang, S. Hendriksen, J. W. Kusek, F. Van Lente, and for the Chronic Kidney Disease Epidemiology Collab Using Standardized Serum Creatinine Values in the Modification of Diet in Renal Disease Study Equation for Estimating Glomerular Filtration Rate Ann Intern Med, August 15, 2006; 145(4): 247 - 254. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Tonelli, F. Sacks, M. Pfeffer, Z.H. Gao, G. Curhan, for the Cholesterol and Recurrent Events (CARE) Tr, P. Rossing, K. Rossing, P. Gaede, O. Pedersen, et al. Serum Phosphate: A Novel Cardiovascular Risk Factor Even in Nonrenal Patients: Relation between Serum Phosphate Level and Cardiovascular Event Rate in People with Coronary Disease. Circulation 112: 2627-2633, 2005 J. Am. Soc. Nephrol., August 1, 2006; 17(8): 2077 - 2085. [Full Text] [PDF]
|
|
|
|
|
|
S. I. Hallan, J. Coresh, B. C. Astor, A. Asberg, N. R. Powe, S. Romundstad, H. A. Hallan, S. Lydersen, and J. Holmen International Comparison of the Relationship of Chronic Kidney Disease Prevalence and ESRD Risk J. Am. Soc. Nephrol., August 1, 2006; 17(8): 2275 - 2284. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. F. Clark, J. J. Macnab, S. J. Chen, R. Suri, L. Moist, and A. X. Garg Evaluation of GFR Estimating Equations in the General Community: Implications for Screening Clin. J. Am. Soc. Nephrol., July 1, 2006; 1(4): 787 - 795. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. A. Stevens, J. Coresh, T. Greene, and A. S. Levey Assessing kidney function--measured and estimated glomerular filtration rate. N. Engl. J. Med., June 8, 2006; 354(23): 2473 - 2483. [Full Text] [PDF]
|
|
|
|
 |
|
 M.S. MacGregor, D.E. Boag, and A. Innes Chronic kidney disease: evolving strategies for detection and management of impaired renal function QJM, June 1, 2006; 99(6): 365 - 375. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. Taylor Reply Nephrol. Dial. Transplant., May 1, 2006; 21(5): 1444 - 1444. [Full Text] [PDF]
|
|
|
|
|
|
P. Rossing, K. Rossing, P. Gaede, O. Pedersen, and H.-H. Parving Monitoring Kidney Function in Type 2 Diabetic Patients With Incipient and Overt Diabetic Nephropathy Diabetes Care, May 1, 2006; 29(5): 1024 - 1030. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R Marouf, O Mojiminiyi, N Abdella, M Kortom, and H Al Wazzan Comparison of renal function markers in Kuwaiti patients with sickle cell disease. J. Clin. Pathol., April 1, 2006; 59(4): 345 - 351. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Pedone, A. Corsonello, R. A. Incalzi, and for The GIFA Investigators Estimating renal function in older people: a comparison of three formulas Age Ageing, March 1, 2006; 35(2): 121 - 126. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. D. Rule, V. E. Torres, A. B. Chapman, J. J. Grantham, L. M. Guay-Woodford, K. T. Bae, S. Klahr, W. M. Bennett, C. M. Meyers, P. A. Thompson, et al. Comparison of Methods for Determining Renal Function Decline in Early Autosomal Dominant Polycystic Kidney Disease: The Consortium of Radiologic Imaging Studies of Polycystic Kidney Disease Cohort J. Am. Soc. Nephrol., March 1, 2006; 17(3): 854 - 862. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
Y. Kuan, M. Hossain, J. Surman, A. M. El Nahas, and J. Haylor GFR prediction using the MDRD and Cockcroft and Gault equations in patients with end-stage renal disease Nephrol. Dial. Transplant., November 1, 2005; 20(11): 2394 - 2401. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. R. Chapman, P. J. O'Connell, and B. J. Nankivell Chronic Renal Allograft Dysfunction J. Am. Soc. Nephrol., October 1, 2005; 16(10): 3015 - 3026. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
O. Viktorsdottir, R. Palsson, M. B. Andresdottir, T. Aspelund, V. Gudnason, and O. S. Indridason Prevalence of chronic kidney disease based on estimated glomerular filtration rate and proteinuria in Icelandic adults Nephrol. Dial. Transplant., September 1, 2005; 20(9): 1799 - 1807. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Cirillo, P. Anastasio, and N. G. De Santo Relationship of gender, age, and body mass index to errors in predicted kidney function Nephrol. Dial. Transplant., September 1, 2005; 20(9): 1791 - 1798. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. de Lusignan, T. Chan, P. Stevens, D. O'Donoghue, N. Hague, B. Dzregah, J. Van Vlymen, M. Walker, and S. Hilton Identifying patients with chronic kidney disease from general practice computer records Fam. Pract., June 1, 2005; 22(3): 234 - 241. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. J. W. Branten, G. Vervoort, and J. F. M. Wetzels Serum creatinine is a poor marker of GFR in nephrotic syndrome Nephrol. Dial. Transplant., April 1, 2005; 20(4): 707 - 711. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. Ibrahim, M. Mondress, A. Tello, Y. Fan, J. Koopmeiners, and W. Thomas An Alternative Formula to the Cockcroft-Gault and the Modification of Diet in Renal Diseases Formulas in Predicting GFR in Individuals with Type 1 Diabetes J. Am. Soc. Nephrol., April 1, 2005; 16(4): 1051 - 1060. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Froissart, J. Rossert, C. Jacquot, M. Paillard, and P. Houillier Predictive Performance of the Modification of Diet in Renal Disease and Cockcroft-Gault Equations for Estimating Renal Function J. Am. Soc. Nephrol., March 1, 2005; 16(3): 763 - 773. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Domrongkitchaiporn, P. Sritara, C. Kitiyakara, W. Stitchantrakul, V. Krittaphol, P. Lolekha, S. Cheepudomwit, and T. Yipintsoi Risk Factors for Development of Decreased Kidney Function in a Southeast Asian Population: A 12-Year Cohort Study J. Am. Soc. Nephrol., March 1, 2005; 16(3): 791 - 799. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. D. Poggio, X. Wang, T. Greene, F. Van Lente, and P. M. Hall Performance of the Modification of Diet in Renal Disease and Cockcroft-Gault Equations in the Estimation of GFR in Health and in Chronic Kidney Disease J. Am. Soc. Nephrol., February 1, 2005; 16(2): 459 - 466. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. D. Rule, T. S. Larson, E. J. Bergstralh, J. M. Slezak, S. J. Jacobsen, and F. G. Cosio Using Serum Creatinine To Estimate Glomerular Filtration Rate: Accuracy in Good Health and in Chronic Kidney Disease Ann Intern Med, December 21, 2004; 141(12): 929 - 937. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. A. Stevens and A. S. Levey Clinical Implications of Estimating Equations for Glomerular Filtration Rate Ann Intern Med, December 21, 2004; 141(12): 959 - 961. [Full Text] [PDF]
|
|
|
|
|
|
E. N. Liberopoulos, G. A. Miltiadous, M. Cariolou, R. Kalaitzidis, K. C. Siamopoulos, and M. S. Elisaf Influence of apolipoprotein E polymorphisms on serum creatinine levels and predicted glomerular filtration rate in healthy subjects Nephrol. Dial. Transplant., August 1, 2004; 19(8): 2006 - 2012. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. S. Fox, D. Levy, and B. Culleton Methods for Estimating Glomerular Filtration Rate--Reply JAMA, June 16, 2004; 291(23): 2820 - 2820. [Full Text] [PDF]
|
|
|
|
|
|
J. Segura, C. Campo, P. Gil, C. Roldan, L. Vigil, J. L. Rodicio, and L. M. Ruilope Development Of Chronic Kidney Disease and Cardiovascular Prognosis in Essential Hypertensive Patients J. Am. Soc. Nephrol., June 1, 2004; 15(6): 1616 - 1622. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. C. Verhave, R. T. Gansevoort, H. L. Hillege, D. de Zeeuw, G. C. Curhan, and P. E. de Jong Drawbacks of the Use of Indirect Estimates of Renal Function to Evaluate the Effect of Risk Factors on Renal Function J. Am. Soc. Nephrol., May 1, 2004; 15(5): 1316 - 1322. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
HOME
CURRENT ISSUE
ARCHIVES
JASN Express
ONLINE SUBMISSION
AUTHOR INFO
EDITORIAL BOARD SUBSCRIBE FEEDBACK ALERTS HELP |
