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Performance of cystatin C- and creatinine-based estimated glomerular filtration rate equations depends on patient characteristics.

ABSTRACT: BACKGROUND:The Kidney Disease Improving Global Outcomes (KDIGO) guideline recommends use of a cystatin C-based estimated glomerular filtration rate (eGFR) to confirm creatinine-based eGFR between 45 and 59 mL · min(-1) · (1.73 m(2))(-1). Prior studies have demonstrated that comorbidities such as solid-organ transplant strongly influence the relationship between measured GFR, creatinine, and cystatin C. Our objective was to evaluate the performance of cystatin C-based eGFR equations compared with creatinine-based eGFR and measured GFR across different clinical presentations. METHODS:We compared the performance of the CKD-EPI 2009 creatinine-based estimated GFR equation (eGFRCr) and the newer CKD-EPI 2012 cystatin C-based equations (eGFRCys and eGFRCr-Cys) with measured GFR (iothalamate renal clearance) across defined patient populations. Patients (n = 1652) were categorized as transplant recipients (n = 568 kidney; n = 319 other organ), known chronic kidney disease (CKD) patients (n = 618), or potential kidney donors (n = 147). RESULTS:eGFRCr-Cys showed the most consistent performance across different clinical populations. Among potential kidney donors without CKD [stage 2 or higher; eGFR >60 mL · min(-1) · (1.73 m(2))(-1)], eGFRCys and eGFRCr-Cys demonstrated significantly less bias than eGFRCr; however, all 3 equations substantially underestimated GFR when eGFR was <60 mL · min(-1) · (1.73 m(2))(-1). Among transplant recipients with CKD stage 3B or greater [eGFR <45 mL · min(-1) · (1.73 m(2))(-1)], eGFRCys was significantly more biased than eGFRCr. No clear differences in eGFR bias between equations were observed among known CKD patients regardless of eGFR range or in any patient group with a GFR between 45 and 59 mL · min(-1) · (1.73 m(2))(-1). CONCLUSIONS:The performance of eGFR equations depends on patient characteristics that are readily apparent on presentation. Among the 3 CKD-EPI equations, eGFRCr-Cys performed most consistently across the studied patient populations.

SUBMITTER: Meeusen JW

PROVIDER: S-EPMC4726452 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Performance of cystatin C- and creatinine-based estimated glomerular filtration rate equations depends on patient characteristics.

Meeusen Jeffrey W JW Rule Andrew D AD Voskoboev Nikolay N Baumann Nikola A NA Lieske John C JC

Clinical chemistry 20150803 10

<h4>Background</h4>The Kidney Disease Improving Global Outcomes (KDIGO) guideline recommends use of a cystatin C-based estimated glomerular filtration rate (eGFR) to confirm creatinine-based eGFR between 45 and 59 mL · min(-1) · (1.73 m(2))(-1). Prior studies have demonstrated that comorbidities such as solid-organ transplant strongly influence the relationship between measured GFR, creatinine, and cystatin C. Our objective was to evaluate the performance of cystatin C-based eGFR equations compa ...[more]

PMID: 26240296

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Project description:Accurate estimation of glomerular filtration rate (GFR) is important for diagnosis and risk stratification in chronic kidney disease and for selection of living donors. Ethnic differences have required correction factors in the originally developed creatinine-based GFR estimation equations for populations around the world. Existing equations have not been validated in the vegetarian Indian population. We examined the performance of creatinine and cystatin-based GFR estimating equations in Indians.GFR was measured by urinary clearance of inulin. Serum creatinine was measured using IDMS-traceable Jaffe's and enzymatic assays, and cystatin C by colloidal gold immunoassay. Dietary protein intake was calculated by measuring urinary nitrogen appearance. Bias, precision and accuracy were calculated for the eGFR equations.A total of 130 participants (63 healthy kidney donors and 67 with CKD) were studied. About 50% were vegetarians, and the remainder ate meat 3.8 times every month. The average creatinine excretion were 14.7 mg/kg/day (95% CI: 13.5 to 15.9 mg/kg/day) and 12.4 mg/kg/day (95% CI: 11.2 to 13.6 mg/kg/day) in males and females, respectively. The average daily protein intake was 46.1 g/day (95% CI: 43.2 to 48.8 g/day). The mean mGFR in the study population was 51.66?±?31.68 ml/min/1.73m2. All creatinine-based eGFR equations overestimated GFR (p?<?0.01 for each creatinine based eGFR equation). However, eGFR by CKD-EPICys was not significantly different from mGFR (p?=?0.38). The CKD-EPICys exhibited lowest bias [mean bias: -3.53?±?14.70 ml/min/1.73m2 (95% CI: -0.608 to -0.98)] and highest accuracy (P30: 74.6%). The GFR in the healthy population was 79.44 ± 20.19 (range: 41.90-134.50) ml/min/1.73m2.Existing creatinine-based GFR estimating equations overestimate GFR in Indians. An appropriately powered study is needed to develop either a correction factor or a new equation for accurate assessment of kidney function in the Indian population.

Project description:Estimates of glomerular filtration rate (GFR) that are based on serum creatinine are routinely used; however, they are imprecise, potentially leading to the overdiagnosis of chronic kidney disease. Cystatin C is an alternative filtration marker for estimating GFR.Using cross-sectional analyses, we developed estimating equations based on cystatin C alone and in combination with creatinine in diverse populations totaling 5352 participants from 13 studies. These equations were then validated in 1119 participants from 5 different studies in which GFR had been measured. Cystatin and creatinine assays were traceable to primary reference materials.Mean measured GFRs were 68 and 70 ml per minute per 1.73 m(2) of body-surface area in the development and validation data sets, respectively. In the validation data set, the creatinine-cystatin C equation performed better than equations that used creatinine or cystatin C alone. Bias was similar among the three equations, with a median difference between measured and estimated GFR of 3.9 ml per minute per 1.73 m(2) with the combined equation, as compared with 3.7 and 3.4 ml per minute per 1.73 m(2) with the creatinine equation and the cystatin C equation (P=0.07 and P=0.05), respectively. Precision was improved with the combined equation (interquartile range of the difference, 13.4 vs. 15.4 and 16.4 ml per minute per 1.73 m(2), respectively [P=0.001 and P<0.001]), and the results were more accurate (percentage of estimates that were >30% of measured GFR, 8.5 vs. 12.8 and 14.1, respectively [P<0.001 for both comparisons]). In participants whose estimated GFR based on creatinine was 45 to 74 ml per minute per 1.73 m(2), the combined equation improved the classification of measured GFR as either less than 60 ml per minute per 1.73 m(2) or greater than or equal to 60 ml per minute per 1.73 m(2) (net reclassification index, 19.4% [P<0.001]) and correctly reclassified 16.9% of those with an estimated GFR of 45 to 59 ml per minute per 1.73 m(2) as having a GFR of 60 ml or higher per minute per 1.73 m(2).The combined creatinine-cystatin C equation performed better than equations based on either of these markers alone and may be useful as a confirmatory test for chronic kidney disease. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases.).

Project description:ImportanceEstimating glomerular filtration rate (GFR) is useful in many clinical conditions. However, very few studies have evaluated the performance of GFR-estimating equations in older adults at various degrees of kidney impairment.ObjectiveTo determine the performance of plasma-creatinine-based equations Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI), Lund-Malmö Revised, (LMR), full age spectrum (FAS), and Berlin Initiative Study (BIS) 1 in older adults across a broad spectrum of GFRs.Design, setting, and participantsSingle-center cross-sectional study performed in France including 2247 participants aged 65 to 90 years who underwent inulin GFR measurements from July 1, 2003, to July 30, 2017, for suspected or established renal dysfunction, for renal risk, before kidney donation, or after kidney transplant.Main outcomes and measuresThe main outcome measure was GRF measured by inulin clearance. Equation performance criteria considered bias (difference between estimated and measured GFR), precision (interquartile range of the median difference), and accuracy P30 (percentage of estimated GFRs lying between [measured GFR - 30% of measured GFR] and [measured GFR + 30% of measured GFR]).ResultsThe mean (SD) age of the 2247 participants was 71.5 (5) years and 1192 (53.0%) were male. The difference in median (95% CI) bias was significant between CKD-EPI vs LMR (-4.0 [-4.0 to -3.5 mL/min/1.73 m2; P?<?.001]) and CKD-EPI vs FAS (-2.0 [-3.5 to -2.5] mL/min/1.73 m2, P?<?.001) but not significant between CKD-EPI vs BIS 1 (0.0 [-1.5 to 0.5], P?=?.07, Mood test). In patients aged 65 to 74 years with measured GFR<45 mL/min/1.73 m2, the difference in median P30 (95% CI) was not significant between CKD-EPI vs LMR (P?=?.08) and CKD-EPI vs FAS (P?=?.48) but significant vs BIS 1 (P?=?.004, McNemar test). In subjects 75 years and older, with measured GFR less than 45 mL/min/1.73 m2, LMR and BIS 1 were more accurate than CKD-EPI and FAS (P30?=?74.5 [70.0-79.5] and 73.0 [68.0-78.0] vs 69.0 [64.5-74.0] and 69.0 [65.5-72.0]). In all patients, despite small statistical differences, the performance of CKD-EPI equation was not clinically different from that of LMR, FAS, or BIS 1.Conclusions and relevanceIn a referral group of patients 65 years and older who had GFR estimated using CDK-EPI, LMR, BIS 1, and FAS equations, a comparison with renal inulin clearance found that none of the equations had a superior diagnostic performance. Each had limitations regarding accuracy.

Project description:BackgroundSerum creatinine (S-Cr)-based prediction equations are commonly used for estimating glomerular filtration rate (GFR). However, S-Cr concentration is also affected by other factors such as tubular secretion, muscle mass, diet, gender and age. Serum cystatin C (S-Cys C)-based prediction equations have been proposed as an improved potential alternative as S-Cys C levels are not influenced by many of the factors that affect creatinine concentration other than GFR. This may be of great benefit to patients with low muscle mass such as those infected with human immunodeficiency virus who are at increased risk for the development of renal impairment. The aim of this study was to develop and evaluate a S-Cys C-based prediction equation for different stages of renal disease in black South Africans.MethodsOne hundred patients with varying degrees of renal function were enrolled in the study. The plasma clearance of (51)Cr-EDTA, a gold standard method, was used to measure GFR (mGFR). In addition, serum was analysed for S-Cr and S-Cys C on each participant. This dataset was split into a development dataset (n = 50) and a test dataset (n = 50). The development dataset was used to formulate a S-Cys C- and S-Cr-based prediction equation using multiple linear regression analysis. These equations together with the four-variable MDRD and CKD-EPI equation were then tested on the test dataset.ResultsIn the test dataset, accuracy within 15% of measured GFR was 68% for the S-Cys C equation and 48% for the S-Cr equation. Root mean square error for S-Cr eGFR was 10.7 mL/min/1.73 m(2) for those patients with mGFR < 60 mL/min/1.73 m(2) and 25.5 mL/min/1.73 m(2) for those patients with mGFR > 60 mL/min/1.73 m(2). Root mean square error for S-Cys C eGFR was 10.2 mL/min/1.73 m(2) for those patients with mGFR < 60 mL/min/1.73 m(2) and 11.9 mL/min/1.73 m(2) for those patients with mGFR > 60 mL/min/1.73 m(2).ConclusionsIn this study, S-Cys C-based prediction equations appear to be more precise than those of S-Cr for those patients with mGFR > 60 mL/min/1.73 m(2) and may therefore be of benefit in the earlier detection of renal impairment.

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Performance of cystatin C- and creatinine-based estimated glomerular filtration rate equations depends on patient characteristics.

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Performance of cystatin C- and creatinine-based estimated glomerular filtration rate equations depends on patient characteristics.

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