Andrew D. Rule

Using Serum Creatinine To Estimate Glomerular Filtration Rate: Accuracy in Good Health and in Chronic Kidney Disease

Context Experts increasingly use the Modification of Diet in Renal Disease (MDRD) equation to estimate glomerular filtration rate (GFR). Contribution This cross-sectional study compared GFR estimated by the MDRD equation with GFR measured by iothalamate clearance in 320 patients with chronic kidney disease and 580 healthy kidney donor candidates. The MDRD equation underestimated GFR by 6% in patients with kidney disease and by 29% in healthy persons. The authors also derived a quadratic equation that better estimated GFR in the healthy people than did the MDRD equation. Implications The MDRD equation systematically underestimates GFR and may erroneously categorize some healthy persons as having kidney disease. The Editors Recently, the National Kidney Foundation endorsed a series of guidelines to assess patients with chronic kidney disease. These guidelines highlighted problems associated with using creatinine clearance to measure glomerular filtration rate (GFR). They instead recommended estimation of GFR by using prediction equations based on serum creatinine determinations (1, 2). The abbreviated Modification of Diet in Renal Disease (MDRD) equation (3, 4) was advocated because it correlated well with GFR measured by iothalamate clearance (2, 5). It also performed as well as a more complicated MDRD equation that required serum urea nitrogen and albumin determinations (3). The abbreviated MDRD equation has also been used to estimate the prevalence of chronic kidney disease in the U.S. population with serum creatinine determinations adjusted for calibration bias (6, 7). However, this equation was developed by using persons with chronic kidney disease and did not include healthy persons (3, 4). Thus, the MDRD equation may not be appropriate for determining the prevalence of chronic kidney disease. Previous studies have raised the concern that MDRD equations may underestimate GFR in healthier populations (8-12). Furthermore, in a population-based study, the relationship between cardiovascular risk factors and GFR differed when the abbreviated MDRD equation was used instead of creatinine clearance (13). The primary objective of the current study was to determine whether estimated GFR with the MDRD equation was accurate in healthy persons compared to patients with chronic kidney disease. The secondary objective was to develop a new GFR prediction equation based on both healthy persons and patients with chronic kidney disease. Methods Healthy and Chronic Kidney Disease Series Records of all potential living donors for kidney transplantation at the Mayo Clinic from 1996 to 2002 were reviewed, with institutional review board approval; this review was an expansion of a previously reported series (9). Originally, potential kidney recipients had identified the potential donors and had perceived them to be healthy enough to be evaluated for kidney donation. Most donors (71%) were related to the potential kidney recipient (9). A total of 599 potential donors had an iothalamate clearance test to measure GFR, which was routinely obtained before a clinic visit with a nephrologist (Figure 1). After exclusions for missing serum creatinine determinations or for age younger than 17 years, the healthy series consisted of 580 potential donors. Figure 1. Sampling process for healthy series and chronic kidney disease series. Records of 501 consecutive patients who had an iothalamate clearance test for any reason between October 1999 and March 2000 were also reviewed, with institutional review board approval (Figure 1). A nephrologist abstracted these records for a cystatin C study (14). Of these patients, 353 had an iothalamate clearance test to measure GFR as part of an evaluation for known or suspected chronic kidney disease. Iothalamate clearance was routinely and primarily ordered by nephrologists at the Mayo Clinic during outpatient referrals. An elevated serum creatinine level, proteinuria, abnormal urinary sediment, history of kidney disease, or kidney transplantation recipient status were typical indications for the iothalamate clearance test. Thus, chronic kidney disease was defined by clinical presentation and not by a GFR cutoff. In recipients of a nonkidney solid organ transplant, iothalamate clearance for routine monitoring only was not considered an evaluation for chronic kidney disease. After exclusions for missing serum creatinine determinations or for age younger than 17 years, the chronic kidney disease series consisted of 320 patients. Iothalamate Clearance and Serum Creatinine Assays Measurement of GFR with the renal clearance of nonradiolabeled iothalamate has previously been described (15). This test involved the subcutaneous injection of nonradiolabeled iothalamate after oral hydration with 4 to 6 glasses of water. After 2 hours, GFR was determined by the clearance equation (UV/P) using the average of 2 serum samples and 1 urine sample assayed for iothalamate concentration via capillary electrophoresis. Glomerular filtration rate was expressed per 1.73 m2 by multiplying the measured value by 1.73 and dividing by body surface area. Nonradiolabeled iothalamate clearance correlates well with radiolabeled iothalamate clearance (r= 0.998) (15) and provides a normal value range similar to that of other GFR measurement techniques (9, 16). Interassay coefficient of variation for nonradiolabeled iothalamate clearance was reported as 5%. Serum creatinine levels were all assayed with the rate-Jaffe reaction on a Hitachi 747 autoanalyzer (Roche Diagnostics Corp., Indianapolis, Indiana). This assay was calibrated daily with a Cfas calibrator (Roche Diagnostics Corp.) by using the uncompensated method during the study period. The interassay coefficient of variation for serum creatinine determinations was reported as 3.1% at 1.3 mg/dL (115 mol/L) and 1.5% at 6.1 mg/dL (539 mol/L) with stability during the study period. The 2.5th to 97.5th percentile of serum creatinine by this assay was 0.7 to 1.2 mg/dL (62 to 106 mol/L) in normal white women and 0.9 to 1.4 mg/dL (80 to 124 mol/L) in normal white men. Estimated GFR was calculated by using the abbreviated MDRD equation (Table 1, equation 1). Table 1. Prediction Equations for Glomerular Filtration Rate Statistical Analysis We compared the baseline characteristics of patients in the healthy and chronic kidney disease series by using the chi-square test (nominal factors), Wilcoxon rank-sum, or Student t-test. We defined bias as the mean of estimated GFR minus measured GFR. We defined percentage bias as the mean of individual ([estimated GFR measured GFR]/measured GFR) 100%. P30% was defined as the percentage of estimated GFR within 30% of measured GFR. We compared estimated GFR and measured GFR in the healthy and chronic kidney disease series by using bias, percentage bias, R2 (coefficient of determination), and P30%. Similar analyses were done with the CockcroftGault equation (17), adjusted for body surface area (mL/min per 1.73 m2) and adjusted to predict GFR instead of creatinine clearance (3). The log-linear form of the abbreviated MDRD equation was refit for new coefficients by using multiple linear regression in the healthy and chronic kidney disease series independently. A log-linear form of the abbreviated MDRD equation was also refit in a combined series (n= 900) with an indicator variable for healthy versus kidney disease status. Each coefficient was compared with the original MDRD study coefficient (4). To develop a new equation for use when the diagnosis of chronic kidney disease is unknown, we used an approach similar to that used to develop the MDRD equations (3, 4). The natural logarithmic (ln) transformed measured GFR was regressed on age, sex, and serum creatinine in the combined series. Because the relationship of ln GFR with ln serum creatinine was nonlinear, the following terms were considered: linear, quadratic, and cubic reciprocal serum creatinine. Linear, quadratic, and logarithmic age terms were also considered. In addition, we examined pairwise interactions between the 3 factors. Because of the large sample size, terms that were statistically significant often added little to the predictive ability of the model. In the interest of parsimony, an increase in R2 of 0.02 or more was arbitrarily required to consider a more complicated model (18). The new equation was internally validated by using bootstrapping (500 replications) to estimate its performance (R2 adjusted for optimism) on independent data sets (19). All statistical analyses were performed with JMP, version 5.1 (SAS Institute, Inc., Cary, North Carolina), except for bootstrapping, which was done with SAS, version 8.2. Role of the Funding Source The study was funded by a National Research Service Award and grants from the Division of Nephrology, Mayo Clinic, Rochester, Minnesota. The funding sources had no role in the collection, analysis, or interpretation of data or in the decision to submit the manuscript for publication. Results Comparison of Healthy and Chronic Kidney Disease Series Table 2 shows the characteristics of the patient samples. Information on race was not available in 14% of the patients. The number of African-American patients was inadequate to analyze the race component in either series. In the chronic kidney disease series, 53% of patients had native kidney disease alone, 16% of patients had a nonkidney solid organ transplant with or without a kidney transplant, and 31% of patients had a kidney transplant alone. In the patients with native kidney disease alone, 36% had hypertension or kidney disease of unknown cause, 24% had glomerulopathy, 13% had diabetes mellitus, and the remaining 27% had miscellaneous causes. Serum creatinine levels were normal (1.4 mg/dL [124 mol/L] in men and 1.2 mg/dL [106 mol/L] in women) in 93 (29%) of the chronic kidney disease series. Table 2. Clinical Characteristics in the Healthy Series and Chronic Kidney Disease Series Figure 2 displays estim

The association between age and nephrosclerosis on renal biopsy among healthy adults.

BACKGROUND Chronic kidney disease is common with older age and is characterized on renal biopsy by global glomerulosclerosis, tubular atrophy, interstitial fibrosis, and arteriosclerosis. OBJECTIVE To see whether the prevalence of these histologic abnormalities in the kidney increases with age in healthy adults and whether histologic findings are explained by age-related differences in kidney function or chronic kidney disease risk factors. DESIGN Cross-sectional study. SETTING Mayo Clinic, Rochester, Minnesota, from 1999 to 2009. PATIENTS 1203 adult living kidney donors. MEASUREMENTS Core-needle biopsy of the renal cortex obtained during surgical implantation of the kidney, and medical record data of kidney function and risk factors obtained before donation. RESULTS The prevalence of nephrosclerosis (> or =2 chronic histologic abnormalities) was 2.7% (95% CI, 1.1% to 6.7%) for patients aged 18 to 29 years, 16% (CI, 12% to 20%) for patients aged 30 to 39 years, 28% (CI, 24% to 32%) for patients aged 40 to 49 years, 44% (CI, 38% to 50%) for patients aged 50 to 59 years, 58% (CI, 47% to 67%) for patients aged 60 to 69 years, and 73% (CI, 43% to 90%) for patients aged 70 to 77 years. Adjustment for kidney function and risk factor covariates did not explain the age-related increase in the prevalence of nephrosclerosis. LIMITATION Kidney donors are selected for health and lack the spectrum or severity of renal pathologic findings in the general population. CONCLUSION Kidney function and chronic kidney disease risk factors do not explain the strong association between age and nephrosclerosis in healthy adults. PRIMARY FUNDING SOURCE National Institutes of Health, U.S. Public Health Service.

Kidney stones and the risk for chronic kidney disease.

BACKGROUND AND OBJECTIVES Kidney stones lead to chronic kidney disease (CKD) in people with rare hereditary disorders (e.g., primary hyperoxaluria, cystinuria), but it is unknown whether kidney stones are an important risk factor for CKD in the general population. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Among Olmsted County, MN, residents, all stone formers (n = 4774) whose condition was diagnosed in 1986 through 2003 were matched 1:3 to control subjects (n = 12,975). Cox proportional hazards models adjusted for age, gender, and comorbidities (hypertension, diabetes, obesity, dyslipidemia, gout, alcohol abuse, tobacco use, coronary artery disease, heart failure, cerebral infarct, and peripheral vascular disease) were used to assess the risk for incident CKD defined as a clinical diagnosis (diagnostic codes), ESRD or death with CKD, sustained (>90 d) elevated serum creatinine (>1.3 mg/dl in men, >1.1 mg/dl in women), or sustained estimated GFR <60 ml/min per 1.73 m(2). RESULTS During a mean of 8.6 yr of follow-up, stone formers were at increased risk for a clinical diagnosis of CKD, but an increased risk for ESRD or death with CKD was NS. Among patients with follow-up serum creatinine levels, stone formers were at increased risk for a sustained elevated serum creatinine and a sustained reduced GFR. CONCLUSIONS Kidney stones are a risk factor for CKD, and studies are warranted to assess screening and preventive measures for CKD in stone formers.

The implications of anatomical and functional changes of the aging kidney: with an emphasis on the glomeruli

Aging is both a natural and inevitable biological process. With advancing age, the kidneys undergo anatomical and physiological changes that are not only the consequences of normal organ senescence but also of specific diseases (such as atherosclerosis or diabetes) that occur with greater frequency in older individuals. Disentangling these two processes, one pathologic and the other physiologic, is difficult. In this review we concentrate on the glomerular structural and functional alterations that accompany natural aging. We also analyze how these changes affect the identification of individuals of advancing age as having chronic kidney disease (CKD) and how these changes can influence prognosis for adverse outcomes, including all-cause mortality, end-stage renal disease, cardiovascular events and mortality, and acute kidney injury. This review describes important shortcomings and deficiencies with our current approach and understanding of CKD in the older and elderly adult.

Temporal trends in incidence of kidney stones among children: a 25-year population based study.

PURPOSE We conducted a population based pediatric study to determine the incidence of symptomatic kidney stones during a 25-year period and to identify factors related to variation in stone incidence during this period. MATERIALS AND METHODS The Rochester Epidemiology Project was used to identify all patients younger than 18 years who were diagnosed with kidney stones in Olmsted County, Minnesota from 1984 to 2008. Medical records were reviewed to validate first time symptomatic stone formers with identification of age appropriate symptoms plus stone confirmation by imaging or passage. The incidence of symptomatic stones by age, gender and study period was compared. Clinical characteristics of incident stone formers were described. RESULTS A total of 207 children received a diagnostic code for kidney stones, of whom 84 (41%) were validated as incident stone formers. The incidence rate increased 4% per calendar year (p = 0.01) throughout the 25-year period. This finding was due to a 6% yearly increased incidence in children 12 to 17 years old (p = 0.02 for age × calendar year interaction) with an increase from 13 per 100,000 person-years between 1984 and 1990 to 36 per 100,000 person-years between 2003 and 2008. Computerized tomography identified the stone in 6% of adolescent stone formers (1 of 18) from 1984 to 1996 vs 76% (34 of 45) from 1997 to 2008. The incidence of spontaneous stone passage in adolescents did not increase significantly between these 2 periods (16 vs 18 per 100,000 person-years, p = 0.30). CONCLUSIONS The incidence of kidney stones increased dramatically among adolescents in the general population during a 25-year period. The exact cause of this finding remains to be determined.

Kidney Stones Associate with Increased Risk for Myocardial Infarction

Kidney stones are a risk factor for chronic kidney disease (CKD), which, in turn, is a risk factor for myocardial infarction (MI). The objective of this study was to determine whether kidney stones associate with an increased risk for MI. We matched 4564 stone formers (1984 through 2003) on age and gender with 10,860 control subjects among residents in Olmsted County, Minnesota. We identified incident MI by diagnostic codes and validated events by chart review through 2006. We used diagnostic codes to determine incidence of kidney stones and presence of comorbidities (CKD, hypertension, diabetes, obesity, dyslipidemia, gout, alcohol dependence, and tobacco use). During a mean of 9 years of follow-up, stone formers had a 38% (95% confidence interval 7 to 77%) increased risk for MI, which remained at 31% (95% confidence interval 2% to 69%) after adjustment for CKD and other comorbidities. In conclusion, kidney stone formers are at increased risk for MI, and this risk is independent of CKD and other risk factors.

Demographic and clinical characteristics associated with glomerular filtration rates in living kidney donors.

Due to the shortage of organs, living donor acceptance criteria are becoming less stringent. An accurate determination of the glomerular filtration rate (GFR) is critical in the evaluation of living kidney donors and a value exceeding 80 ml/min per 1.73 m(2) is usually considered suitable. To improve strategies for kidney donor screening, an understanding of factors that affect GFR is needed. Here we studied the relationships between donor GFR measured by (125)I-iothalamate clearances (mGFR) and age, gender, race, and decade of care in living kidney donors evaluated at the Cleveland Clinic from 1972 to 2005. We report the normal reference ranges for 1057 prospective donors (56% female, 11% African American). Females had slightly higher mGFR than males after adjustment for body surface area, but there were no differences due to race. The lower limit of normal for donors (5th percentile) was less than 80 ml/min per 1.73 m(2) for females over age 45 and for males over age 40. We found a significant doubling in the rate of GFR decline in donors over age 45 as compared to younger donors. The age of the donors and body mass index increased over time, but their mGFR, adjusted for body surface area, significantly declined by 1.49+/-0.61 ml/min per 1.73 m(2) per decade of testing. Our study shows that age and gender are important factors determining normal GFR in living kidney donors.

Relative Performance of the MDRD and CKD-EPI Equations for Estimating Glomerular Filtration Rate among Patients with Varied Clinical Presentations

BACKGROUND The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was developed using both CKD and non-CKD patients to potentially replace the Modification of Diet in Renal Disease (MDRD) equation that was derived with only CKD patients. The objective of our study was to compare the accuracy of the MDRD and CKD-EPI equations for estimating GFR in a large group of patients having GFR measurements for diverse clinical indications. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS A cross-sectional study was conducted of patients who underwent renal function assessment for clinical purposes by simultaneous measurements of serum creatinine and estimation of GFR using the MDRD and CKD-EPI equations and renal clearance of iothalamate (n = 5238). RESULTS Bias compared with measured GFR (mGFR) varied for each equation depending on clinical presentation. The CKD-EPI equation demonstrated less bias than the MDRD equation in potential kidney donors (-8% versus -18%) and postnephrectomy donors (-7% versus -15%). However, the CKD-EPI equation was slightly more biased than the MDRD equation in native CKD patients (6% versus 3%), kidney recipients (8% versus 1%), and other organ recipients (9% versus 3%). Among potential kidney donors, the CKD-EPI equation had higher specificity than the MDRD equation for detecting an mGFR <60 ml/min per 1.73 m(2) (98% versus 94%) but lower sensitivity (50% versus 70%). CONCLUSIONS Clinical presentation influences the estimation of GFR from serum creatinine, and neither the CKD-EPI nor MDRD equation account for this. Use of the CKD-EPI equation misclassifies fewer low-risk patients as having reduced mGFR, although it is also less sensitive for detecting mGFR below specific threshold values used to define CKD stages.

Estimating the glomerular filtration rate from serum creatinine is better than from cystatin C for evaluating risk factors associated with chronic kidney disease

Chronic kidney disease risk factors may associate with the estimated glomerular filtration rate (eGFR) differently than with the measured GFR. To examine this, we evaluated 1150 patients (mean age 65) in two community cohorts for risk factors, measured GFR by iothalamate clearance, and eGFR based on creatinine (Cr), cystatin C (CysC), or both. The interaction between each risk factor and eGFR (relative to measured GFR) identified risk factor associations with eGFR along non-GFR pathways. In a subset of 40 patients with two visits, the mean coefficient of variation was 8.2% for measured GFR, 6.4% for eGFRCr, 8.2% for eGFRCr-CysC, and 10.7% for eGFRCysC. The measured GFR was better correlated with eGFRCr-CysC (r, 0.74) than eGFRCr (r, 0.70) or eGFRCysC (r, 0.68). Lower measured GFR associated with lower 24-hour urine creatinine, albuminuria, hypertension, diabetes, higher triglycerides, and higher uric acid. Lower eGFRCr had these same associations except for an association with higher 24-hour urine creatinine along a non-GFR pathway. Lower eGFRCysC and eGFRCr-CysC also had these same associations but also associated with obesity, albuminuria, hypertension, diabetes, higher triglycerides, higher C-reactive protein, and higher uric acid along non-GFR pathways. Thus, cystatin C improves estimation of GFR over creatinine alone; however, the association between most of the risk factors and GFR was more accurate by eGFR based on creatinine alone. This is explained by the association of these risk factors with the non-GFR determinants of cystatin C.

Development and validation of GFR-estimating equations using diabetes, transplant and weight

BACKGROUND We have reported a new equation (CKD-EPI equation) that reduces bias and improves accuracy for GFR estimation compared to the MDRD study equation while using the same four basic predictor variables: creatinine, age, sex and race. Here, we describe the development and validation of this equation as well as other equations that incorporate diabetes, transplant and weight as additional predictor variables. METHODS Linear regression was used to relate log-measured GFR (mGFR) to sex, race, diabetes, transplant, weight, various transformations of creatinine and age with and without interactions. Equations were developed in a pooled database of 10 studies [2/3 (N = 5504) for development and 1/3 (N = 2750) for internal validation], and final model selection occurred in 16 additional studies [external validation (N = 3896)]. RESULTS The mean mGFR was 68, 67 and 68 ml/min/ 1.73 m(2) in the development, internal validation and external validation datasets, respectively. In external validation, an equation that included a linear age term and spline terms in creatinine to account for a reduction in the magnitude of the slope at low serum creatinine values exhibited the best performance (bias = 2.5, RMSE = 0.250) among models using the four basic predictor variables. Addition of terms for diabetes and transplant did not improve performance. Equations with weight showed a small improvement in the subgroup with BMI <20 kg/m(2). CONCLUSIONS The CKD-EPI equation, based on creatinine, age, sex and race, has been validated and is more accurate than the MDRD study equation. The addition of weight, diabetes and transplant does not significantly improve equation performance.