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1. CKD-EPI and EKFC GFR Estimating Equations: Performance and Other Considerations for Selecting Equations for Implementation in Adults.

Author

Inker LA, Tighiouart H, Adingwupu OM, Shlipak MG, Doria A, Estrella MM, Froissart M, Gudnason V, Grubb A, Kalil R, Mauer M, Rossing P, Seegmiller J, Coresh J, and Levey AS

Subjects
Adult, Female, Humans, Male, Middle Aged, Creatinine, Cystatin C, Aged, Glomerular Filtration Rate, Renal Insufficiency, Chronic
Abstract

Significance Statement: New eGFR equations from Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and European Kidney Function Consortium (EKFC) using creatinine (eGFRcr), cystatin C (eGFRcys), and both (eGFRcr-cys) have sufficient accuracy for use in clinical practice, leading to uncertainty in selecting equations for implementation. The authors evaluated performance of equations in an independent population of 4050 adults and evaluated other considerations important for implementation. They found that CKD-EPI and EKFC equations are approaching convergence, with better performance of eGFRcr-cys equations in the overall group and fewer differences among race, sex, and age subgroups than eGFRcr equations. Larger differences among eGFRcr equations reflect regional population differences in creatinine, forcing a trade-off between accuracy and uniformity in global implementation of eGFRcr equations. More widespread use of cystatin C could avoid this trade-off., Background: New CKD-EPI and EKFC eGFR equations using eGFRcr, eGFRcys, and both (eGFRcr-cys) have sufficient accuracy for use in clinical practice. A better understanding of the equations, including their performance in race, sex and age subgroups, is important for selection of eGFR equations for global implementation., Methods: We evaluated performance (bias and P 30 ) of equations and methods used for equation development in an independent study population comprising 4050 adults pooled from 12 studies. The mean (SD) measured GFR was 76.4 (29.6) ml/min per 1.73 m 2 and age 57.0 (17.4) years, with 1557 (38%) women and 579 (14%) Black participants., Results: Coefficients for creatinine, cystatin C, age, and sex in the CKD-EPI and EKFC equations are similar. Performance of the eGFRcr-cys equations in the overall population (bias <±5 ml/min per 1.73 m 2 and P 30 >90%) was better than the eGFRcr or eGFRcys equations, with fewer differences among race, sex, and age subgroups. Differences in performance across subgroups reflected differences in diversity of source populations and use of variables for race and sex for equation development. Larger differences among eGFRcr equations reflected regional population differences in non-GFR determinants of creatinine., Conclusion: CKD-EPI and EKFC equations are approaching convergence. It is not possible to maximize both accuracy and uniformity in selecting one of the currently available eGFRcr equations for implementation across regions. Decisions should consider methods for equation development in addition to performance. Wider use of cystatin C with creatinine could maximize both accuracy and uniformity of GFR estimation using currently available equations., (Copyright © 2023 by the American Society of Nephrology.)

Published
2023
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2. New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race.

Author

Inker LA, Eneanya ND, Coresh J, Tighiouart H, Wang D, Sang Y, Crews DC, Doria A, Estrella MM, Froissart M, Grams ME, Greene T, Grubb A, Gudnason V, Gutiérrez OM, Kalil R, Karger AB, Mauer M, Navis G, Nelson RG, Poggio ED, Rodby R, Rossing P, Rule AD, Selvin E, Seegmiller JC, Shlipak MG, Torres VE, Yang W, Ballew SH, Couture SJ, Powe NR, and Levey AS

Subjects
Adult, Aged, Algorithms, Black People, Datasets as Topic, Female, Humans, Male, Middle Aged, Renal Insufficiency, Chronic blood, Renal Insufficiency, Chronic epidemiology, Renal Insufficiency, Chronic physiopathology, United States epidemiology, Black or African American, Creatinine blood, Cystatin C blood, Glomerular Filtration Rate, Racial Groups, Renal Insufficiency, Chronic ethnology
Abstract

Background: Current equations for estimated glomerular filtration rate (eGFR) that use serum creatinine or cystatin C incorporate age, sex, and race to estimate measured GFR. However, race in eGFR equations is a social and not a biologic construct., Methods: We developed new eGFR equations without race using data from two development data sets: 10 studies (8254 participants, 31.5% Black) for serum creatinine and 13 studies (5352 participants, 39.7% Black) for both serum creatinine and cystatin C. In a validation data set of 12 studies (4050 participants, 14.3% Black), we compared the accuracy of new eGFR equations to measured GFR. We projected the prevalence of chronic kidney disease (CKD) and GFR stages in a sample of U.S. adults, using current and new equations., Results: In the validation data set, the current creatinine equation that uses age, sex, and race overestimated measured GFR in Blacks (median, 3.7 ml per minute per 1.73 m 2 of body-surface area; 95% confidence interval [CI], 1.8 to 5.4) and to a lesser degree in non-Blacks (median, 0.5 ml per minute per 1.73 m 2 ; 95% CI, 0.0 to 0.9). When the adjustment for Black race was omitted from the current eGFR equation, measured GFR in Blacks was underestimated (median, 7.1 ml per minute per 1.73 m 2 ; 95% CI, 5.9 to 8.8). A new equation using age and sex and omitting race underestimated measured GFR in Blacks (median, 3.6 ml per minute per 1.73 m 2 ; 95% CI, 1.8 to 5.5) and overestimated measured GFR in non-Blacks (median, 3.9 ml per minute per 1.73 m 2 ; 95% CI, 3.4 to 4.4). For all equations, 85% or more of the eGFRs for Blacks and non-Blacks were within 30% of measured GFR. New creatinine-cystatin C equations without race were more accurate than new creatinine equations, with smaller differences between race groups. As compared with the current creatinine equation, the new creatinine equations, but not the new creatinine-cystatin C equations, increased population estimates of CKD prevalence among Blacks and yielded similar or lower prevalence among non-Blacks., Conclusions: New eGFR equations that incorporate creatinine and cystatin C but omit race are more accurate and led to smaller differences between Black participants and non-Black participants than new equations without race with either creatinine or cystatin C alone. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases.)., (Copyright © 2021 Massachusetts Medical Society.)

Published
2021
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3. Measured glomerular filtration rate (GFR) significantly and rapidly decreases after radical cystectomy for bladder cancer.

Author

Rouanne M, Gaillard F, Meunier ME, Soorojebally Y, Phan H, Slimani-Thevenet H, Jannot AS, Neuzillet Y, Friedlander G, Froissart M, Botto H, Houillier P, Lebret T, and Courbebaisse M

Subjects
Aged, Creatinine analysis, Disease Progression, Female, Humans, Kidney Function Tests, Male, Middle Aged, Prospective Studies, Renal Insufficiency, Chronic complications, Risk Factors, Urinary Bladder Neoplasms complications, Urinary Bladder Neoplasms surgery, Cystectomy methods, Glomerular Filtration Rate physiology, Urinary Diversion methods
Abstract

Precise determination of glomerular filtration rate (GFR) is essential for the management of patients with muscle-invasive bladder cancer (MIBC). We aim to describe the early evolution of measured GFR (mGFR) after radical cystectomy and urinary diversion (RCUD) and to identify risk factors for GFR decline. GFR measurement using 51 Cr-EDTA continuous infusion, estimated GFR (eGFR) from five published equations and renal scintigraphy with split renal function determination were performed before and 6 months after RCUD. Chronic Kidney Disease (mGFR < 60 mL/min/1.73 m 2 ) and GFR stages were defined according to the KDIGO guidelines using mGFR. Twenty-seven patients (men 85%, median age 65, IQR 59; 68 years) were included. A total of 20 (74%) patients experienced significant mGFR decline at 6 months postoperatively. Median mGFR decreased from 84.1 pre-operatively (IQR 65.3; 97.2) to 69.9 mL/min/1.73 m 2 (IQR 55.0; 77.9) 6 months after surgery (p < 0.001). Thirteen (48%) patients had a progression to a worse GFR stage. Of the 22 patients without pre-operative CKD, 5 (23%) developed post-operative CKD. Diabetes mellitus was more frequent in patients in the highest tertile of relative mGFR decline (44% vs. 11%, p = 0.02) and platinum-based adjuvant chemotherapy tended to be more frequently used in these patients (44% vs. 17%, p = 0.06). Importantly, pre-operative weight was independently and negatively associated with post-operative mGFR and with mGFR slope in multivariable analyses. In this prospective series, we demonstrated that early and significant mGFR decline occurred after RCUD and perioperative platinum-based chemotherapy, especially in patients with diabetes mellitus and overweight.

Published
2020
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4. Performance of Indexed and Nonindexed Estimated GFR.

Author

Titan S, Miao S, Tighiouart H, Chen N, Shi H, Zhang L, Li Z, Froissart M, Rossing P, Grubb A, Fan L, Mauer M, Bakoush O, Wyatt C, Shlipak MG, Shafi T, Inker LA, and Levey AS

Subjects
Adult, Aged, Biomarkers, Creatinine blood, Cystatin C blood, Diabetic Nephropathies epidemiology, Female, Humans, Kidney Failure, Chronic blood, Kidney Failure, Chronic epidemiology, Male, Middle Aged, Body Surface Area, Glomerular Filtration Rate
Published
2020
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5. Performance of creatinine-based equations for estimating glomerular filtration rate changes over time.

Author

van Rijn MHC, Metzger M, Flamant M, Houillier P, Haymann JP, van den Brand JAJG, Froissart M, and Stengel B

Subjects
Adult, Aged, Aged, 80 and over, Female, Humans, Kidney Function Tests methods, Male, Middle Aged, Predictive Value of Tests, Prospective Studies, Renal Insufficiency, Chronic blood, Young Adult, Algorithms, Creatinine blood, Diagnostic Errors prevention & control, Glomerular Filtration Rate, Renal Insufficiency, Chronic physiopathology, Severity of Illness Index
Abstract

Background: Glomerular filtration rate (GFR) is commonly used to monitor chronic kidney disease (CKD) progression, but its validity for evaluating kidney function changes over time has not been comprehensively evaluated. We assessed the performance of creatinine-based equations for estimating GFR slope according to patient characteristics and specific CKD diagnosis., Methods: In the NephroTest cohort study, we measured GFR 5324 times by chromium 51-labeled ethylenediamine tetraacetic acid renal clearance in 1955 adult patients with CKD Stages 1-4 referred to nephrologists (Stages 1-2, 19%) and simultaneously estimated GFR with both the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations for isotope dilution mass spectrometry traceable creatinine; absolute and relative GFR slopes were calculated using a linear mixed model., Results: Over a median follow-up of 3.4 [interquartile range (IQR) 2.0-5.6] years, the decline in mean absolute and relative measured GFR (mGFR) and CKD-EPI and MDRD estimated GFR (eGFR) was 1.6 ± 1.2, 1.5 ± 1.4 and 1.3 ± 1.3 mL/min/1.73 m2/year and 5.9 ± 5.3, 5.3 ± 5.3 and 4.8 ± 5.2%/year, respectively; 52% and 55% of the patients had MDRD and CKD-EPI eGFR slopes within 30% of mGFR slopes. Both equations tended to overestimate the GFR slope in the youngest patients and underestimate it in the oldest, thus producing inverse associations between age and mGFR versus eGFR slope. Other patient characteristics and specific CKD diagnoses had little effect on the performance of the equations in estimating associations., Conclusions: This study shows little bias, but poor precision in GFR slope estimation for both MDRD and CKD-EPI equations. Importantly, bias strongly varied with age, possibly due to variations in muscle mass over time, with implications for clinical care and research., (© The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)

Published
2020
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6. Urinary creatinine excretion, measured glomerular filtration rate and CKD outcomes.

Author

Tynkevich E, Flamant M, Haymann JP, Metzger M, Thervet E, Boffa JJ, Vrtovsnik F, Houillier P, Froissart M, and Stengel B

Subjects
Aged, Disease Progression, Female, Humans, Male, Middle Aged, Prognosis, Proportional Hazards Models, Prospective Studies, Renal Insufficiency, Chronic etiology, Renal Insufficiency, Chronic mortality, Risk Factors, Survival Rate, Biomarkers urine, Creatinine urine, Glomerular Filtration Rate, Proteinuria complications, Renal Insufficiency, Chronic urine
Abstract

Background: Muscle wasting predicts mortality in patients with end-stage renal disease (ESRD), but its role in the progression of chronic kidney disease (CKD) is uncertain. We studied CKD outcomes associated with low muscle mass, assessed by urinary creatinine excretion (UCr)., Methods: The NephroTest cohort included 1429 patients with CKD stages 1-4 and both measured glomerular filtration rate (mGFR) (by (51)Cr-EDTA) and estimated glomerular filtration rate (eGFR) (by CKD-Epidemiology Collaboration equation). We used cause-specific Cox models to estimate hazard ratios (HRs) for the competing risks of ESRD and death associated with gender-specific UCr quartiles., Results: UCr was 13.6 ± 3.2 mmol/24 h (0.17 ± 0.05 mmol/kg/24 h) in men and 9.2 ± 2.1 (0.14 ± 0.05) in women. It was positively associated with mGFR, but not with eGFR. Over a median follow-up of 3.6 (2.1-5.8) years, 229 patients developed ESRD and 113 patients died before ESRD. Compared with patients in the highest UCr quartile, those in the lowest quartile had a higher crude HR (95% confidence interval) for pre-ESRD death: 4.3 (2.4-7.7), which was weakened, but remained statistically significant, independent of demographics, mGFR and several other factors: 2.1 (1.04-4.3). Their crude ESRD risk was not higher: HR: 0.95 (0.65-1.4), and even tended to be lower after adjusting for mGFR and log-proteinuria: HR: 0.70 (0.45-1.1). Adjustment for eGFR instead of mGFR reversed this relationship: HR: 1.7 (1.1-2.7)., Conclusions: In early stage CKD, low UCr is associated with higher risk for mortality, but not for ESRD. Using creatinine-based equation to adjust for GFR may bias the relationship of UCr with ESRD risk., (© The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)

Published
2015
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7. Decrease in urinary creatinine excretion in early stage chronic kidney disease.

Author

Tynkevich E, Flamant M, Haymann JP, Metzger M, Thervet E, Boffa JJ, Vrtovsnik F, Houillier P, Froissart M, and Stengel B

Subjects
Age Factors, Body Mass Index, Ethnicity, Female, Humans, Kidney Function Tests, Male, Muscle, Skeletal pathology, Organ Size, Prospective Studies, Renal Insufficiency, Chronic pathology, Risk Factors, Sex Factors, Creatinine urine, Glomerular Filtration Rate, Renal Insufficiency, Chronic physiopathology
Abstract

Background: Little is known about muscle mass loss in early stage chronic kidney disease (CKD). We used 24-hour urinary creatinine excretion rate to assess determinants of muscle mass and its evolution with kidney function decline. We also described the range of urinary creatinine concentration in this population., Methods: We included 1072 men and 537 women with non-dialysis CKD stages 1 to 5, all of them with repeated measurements of glomerular filtration rate (mGFR) by (51)Cr-EDTA renal clearance and several nutritional markers. In those with stage 1 to 4 at baseline, we used a mixed model to study factors associated with urinary creatinine excretion rate and its change over time., Results: Baseline mean urinary creatinine excretion decreased from 15.3 ± 3.1 to 12.1 ± 3.3 mmol/24 h (0.20 ± 0.03 to 0.15 ± 0.04 mmol/kg/24 h) in men, with mGFR falling from ≥ 60 to <15 mL/min/1.73 m(2), and from 9.6 ± 1.9 to 7.6 ± 2.5 (0.16 ± 0.03 to 0.12 ± 0.03) in women. In addition to mGFR, an older age, diabetes, and lower levels of body mass index, proteinuria, and protein intake assessed by urinary urea were associated with lower mean urinary creatinine excretion at baseline. Mean annual decline in mGFR was 1.53 ± 0.12 mL/min/1.73 m(2) per year and that of urinary creatinine excretion rate, 0.28 ± 0.02 mmol/24 h per year. Patients with fast annual decline in mGFR of 5 mL/min/1.73 m(2) had a decrease in urinary creatinine excretion more than twice as big as in those with stable mGFR, independent of changes in urinary urea as well as of other determinants of low muscle mass., Conclusions: Decrease in 24-hour urinary creatinine excretion rate may appear early in CKD patients, and is greater the more mGFR declines independent of lowering protein intake assessed by 24-hour urinary urea. Normalizing urine analytes for creatininuria may overestimate their concentration in patients with reduced kidney function and low muscle mass.

Published
2014
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8. Glomerular filtration rate estimation using cystatin C alone or combined with creatinine as a confirmatory test.

Author

Fan L, Inker LA, Rossert J, Froissart M, Rossing P, Mauer M, and Levey AS

Subjects
Adult, Aged, Biomarkers blood, Body Mass Index, Cross-Sectional Studies, Diabetes Mellitus metabolism, Female, Humans, Kidney Function Tests standards, Male, Middle Aged, Predictive Value of Tests, Renal Insufficiency, Chronic blood, Creatinine blood, Cystatin C blood, Glomerular Filtration Rate physiology, Renal Insufficiency, Chronic physiopathology
Abstract

Background: Glomerular filtration rate (GFR) estimating equations using the combination of creatinine and cystatin C (eGFRcr-cys) are more accurate than equations using either alone (eGFRcr or eGFRcys). New guidelines suggest measuring cystatin C as a confirmatory test when eGFRcr may be inaccurate, but do not specify demographic or clinical conditions in which eGFRcys or eGFRcr-cys are more accurate than eGFRcr nor which estimate to use in such circumstances., Methods: We compared the performance of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations in 1119 subjects in the CKD-EPI cystatin C external validation dataset. Subgroups were defined by eGFRcr, age, sex, diabetes status and body mass index (BMI). The reference test was GFR measured using urinary or plasma clearance of exogenous filtration markers. Cystatin C and creatinine assays were traceable to primary reference materials. Accuracy was defined as the absolute difference in eGFR compared with mGFR., Results: The mean mGFR was 70 ± 41 (SD) mL/min/1.73 m(2). eGFRcys was more accurate than eGFRcr at lower BMI and less accurate at higher BMI, especially at higher levels of eGFRcr. There were small differences in accuracy in people according to the diabetes status. eGFRcr-cys was as accurate or more accurate than eGFRcr or eGFRcys in these and all other subgroups., Conclusions: eGFRcr-cys, but not eGFRcys, is more accurate than eGFRcr in most subgroups we studied, suggesting preferential use of eGFRcr-cys when serum cystatin C is measured as a confirmatory test to obtain more accurate eGFR. Further studies are necessary to evaluate diagnostic strategies for using eGFRcys and eGFRcr-cys., (© The Author 2014. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)

Published
2014
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9. Enzymatic creatinine assays allow estimation of glomerular filtration rate in stages 1 and 2 chronic kidney disease using CKD-EPI equation.

Author

Kuster N, Cristol JP, Cavalier E, Bargnoux AS, Halimi JM, Froissart M, Piéroni L, and Delanaye P

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Creatinine metabolism, Female, Humans, Male, Middle Aged, Renal Insufficiency, Chronic metabolism, Young Adult, Creatinine analysis, Enzyme Assays, Glomerular Filtration Rate, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic physiopathology
Abstract

The National Kidney Disease Education Program group demonstrated that MDRD equation is sensitive to creatinine measurement error, particularly at higher glomerular filtration rates. Thus, MDRD-based eGFR above 60 mL/min/1.73 m² should not be reported numerically. However, little is known about the impact of analytical error on CKD-EPI-based estimates. This study aimed at assessing the impact of analytical characteristics (bias and imprecision) of 12 enzymatic and 4 compensated Jaffe previously characterized creatinine assays on MDRD and CKD-EPI eGFR. In a simulation study, the impact of analytical error was assessed on a hospital population of 24084 patients. Ability using each assay to correctly classify patients according to chronic kidney disease (CKD) stages was evaluated. For eGFR between 60 and 90 mL/min/1.73 m², both equations were sensitive to analytical error. Compensated Jaffe assays displayed high bias in this range and led to poorer sensitivity/specificity for classification according to CKD stages than enzymatic assays. As compared to MDRD equation, CKD-EPI equation decreases impact of analytical error in creatinine measurement above 90 mL/min/1.73 m². Compensated Jaffe creatinine assays lead to important errors in eGFR and should be avoided. Accurate enzymatic assays allow estimation of eGFR until 90 mL/min/1.73 m² with MDRD and 120 mL/min/1.73 m² with CKD-EPI equation., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Published
2014
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10. Renal function can improve at any stage of chronic kidney disease.

Author

Weis L, Metzger M, Haymann JP, Thervet E, Flamant M, Vrtovsnik F, Gauci C, Houillier P, Froissart M, Letavernier E, Stengel B, and Boffa JJ

Subjects
Adult, Aged, Albuminuria complications, Albuminuria diagnosis, Albuminuria drug therapy, Angiotensin-Converting Enzyme Inhibitors therapeutic use, Blood Pressure, Chronic Disease, Disease Progression, Female, Humans, Hypertension, Renal complications, Hypertension, Renal diagnosis, Hypertension, Renal drug therapy, Kidney, Male, Middle Aged, Nephritis complications, Nephritis diagnosis, Nephritis drug therapy, Renal Insufficiency, Chronic complications, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic drug therapy, Renin-Angiotensin System drug effects, Severity of Illness Index, Treatment Outcome, Vitamin D Deficiency complications, Vitamin D Deficiency diagnosis, Vitamin D Deficiency drug therapy, Albuminuria physiopathology, Glomerular Filtration Rate physiology, Hypertension, Renal physiopathology, Nephritis physiopathology, Renal Insufficiency, Chronic physiopathology, Vitamin D Deficiency physiopathology
Abstract

Introduction: Even though renal function decline is considered relentless in chronic kidney disease (CKD), improvement has been shown in patients with hypertensive nephropathy. Whether this can occur in any type of nephropathy and at any stage is unknown as are the features of patients who improve., Methods: We identified 406 patients in the NephroTest cohort with glomerular filtration rates (mGFR) measured by (51)Cr-EDTA clearance at least 3 times during at least 2 years of follow-up. Individual examination of mGFR trajectories by 4 independent nephrologists classified patients as improvers, defined as those showing a sustained mGFR increase, or nonimprovers. Twelve patients with erratic trajectories were excluded. Baseline data were compared between improvers and nonimprovers, as was the number of recommended therapeutic targets achieved over time (specifically, for systolic and diastolic blood pressure, proteinuria, and use of renin angiotensin system blockers)., Results: Measured GFR improved over time in 62 patients (15.3%). Their median mGFR slope was +1.88[IQR 1.38, 3.55] ml/min/year; it was -2.23[-3.9, -0.91] for the 332 nonimprovers. Improvers had various nephropathies, but not diabetic glomerulopathy or polycystic kidney disease. They did not differ from nonimprovers for age, sex, cardiovascular history, or CKD stage, but their urinary albumin excretion rate was lower. Improvers achieved significantly more recommended therapeutic targets (2.74±0.87) than nonimprovers (2.44±0.80, p<0.01). They also had fewer CKD-related metabolic complications and a lower prevalence of 25OH-vitamin-D deficiency., Conclusion: GFR improvement is possible in CKD patients at any CKD stage through stage 4-5. It is noteworthy that this GFR improvement is associated with a decrease in the number of metabolic complications over time.

Published
2013
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11. Performance of GFR estimating equations in African Europeans: basis for a lower race-ethnicity factor than in African Americans.

Author

Flamant M, Vidal-Petiot E, Metzger M, Haymann JP, Letavernier E, Delatour V, Karras A, Thervet E, Boffa JJ, Houillier P, Stengel B, Vrtovsnik F, and Froissart M

Subjects
Adult, Black or African American ethnology, Aged, Aged, 80 and over, Cohort Studies, Female, Humans, Male, Middle Aged, Renal Insufficiency, Chronic diagnosis, Renal Insufficiency, Chronic physiopathology, Black People ethnology, Glomerular Filtration Rate physiology, Renal Insufficiency, Chronic ethnology, White People ethnology
Published
2013
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12. Lower estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-stage renal disease. A collaborative meta-analysis of kidney disease population cohorts.

Author

Astor BC, Matsushita K, Gansevoort RT, van der Velde M, Woodward M, Levey AS, Jong PE, Coresh J, Astor BC, Matsushita K, Gansevoort RT, van der Velde M, Woodward M, Levey AS, de Jong PE, Coresh J, El-Nahas M, Eckardt KU, Kasiske BL, Wright J, Appel L, Greene T, Levin A, Djurdjev O, Wheeler DC, Landray MJ, Townend JN, Emberson J, Clark LE, Macleod A, Marks A, Ali T, Fluck N, Prescott G, Smith DH, Weinstein JR, Johnson ES, Thorp ML, Wetzels JF, Blankestijn PJ, van Zuilen AD, Menon V, Sarnak M, Beck G, Kronenberg F, Kollerits B, Froissart M, Stengel B, Metzger M, Remuzzi G, Ruggenenti P, Perna A, Heerspink HJ, Brenner B, de Zeeuw D, Rossing P, Parving HH, Auguste P, Veldhuis K, Wang Y, Camarata L, Thomas B, and Manley T

Subjects
Adult, Aged, Albuminuria diagnosis, Albuminuria physiopathology, Biomarkers blood, Biomarkers urine, Chi-Square Distribution, Cohort Studies, Creatine blood, Disease Progression, Female, Humans, Kidney Diseases diagnosis, Kidney Diseases physiopathology, Kidney Failure, Chronic diagnosis, Kidney Failure, Chronic physiopathology, Male, Middle Aged, Predictive Value of Tests, Prognosis, Proportional Hazards Models, Regression Analysis, Risk Assessment, Risk Factors, Albuminuria etiology, Albuminuria mortality, Glomerular Filtration Rate, Kidney physiopathology, Kidney Diseases complications, Kidney Diseases mortality, Kidney Failure, Chronic etiology, Kidney Failure, Chronic mortality
Abstract

We studied here the independent associations of estimated glomerular filtration rate (eGFR) and albuminuria with mortality and end-stage renal disease (ESRD) in individuals with chronic kidney disease (CKD). We performed a collaborative meta-analysis of 13 studies totaling 21,688 patients selected for CKD of diverse etiology. After adjustment for potential confounders and albuminuria, we found that a 15 ml/min per 1.73 m² lower eGFR below a threshold of 45 ml/min per 1.73 m² was significantly associated with mortality and ESRD (pooled hazard ratios (HRs) of 1.47 and 6.24, respectively). There was significant heterogeneity between studies for both HR estimates. After adjustment for risk factors and eGFR, an eightfold higher albumin- or protein-to-creatinine ratio was significantly associated with mortality (pooled HR 1.40) without evidence of significant heterogeneity and with ESRD (pooled HR 3.04), with significant heterogeneity between HR estimates. Lower eGFR and more severe albuminuria independently predict mortality and ESRD among individuals selected for CKD, with the associations stronger for ESRD than for mortality. Thus, these relationships are consistent with CKD stage classifications based on eGFR and suggest that albuminuria provides additional prognostic information among individuals with CKD.

Published
2011
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13. Equations to estimate creatinine excretion rate: the CKD epidemiology collaboration.

Author

Ix JH, Wassel CL, Stevens LA, Beck GJ, Froissart M, Navis G, Rodby R, Torres VE, Zhang YL, Greene T, and Levey AS

Subjects
Adult, Aged, Chronic Disease, Cooperative Behavior, Female, Humans, Kidney Diseases physiopathology, Male, Middle Aged, Creatinine urine, Glomerular Filtration Rate
Abstract

Background and Objectives: Creatinine excretion rate (CER) indicates timed urine collection accuracy. Although equations to estimate CER exist, their bias and precision are untested and none simultaneously include age, sex, race, and weight., Design, Setting, Participants, & Measurements: Participants (n = 2466) from three kidney disease trials were randomly allocated into equation development (2/3) and internal validation (1/3) data sets. CER served as the dependent variable in linear regression to develop new equations. Their stability was assessed within the internal validation data set. Among 987 individuals from three additional studies the equations were externally validated and compared with existing equations., Results: Mean age was 46 years, 42% were women, and 9% were black. Age, sex, race, weight, and serum phosphorus improved model fit. Two equations were developed, with or without serum phosphorus. In external validation, the new equations showed little bias (mean difference [measured - estimated CER] -0.7% [95% confidence interval -2.5% to 1.0%] and 0.3% [95% confidence interval -2.6% to 3.1%], respectively) and moderate precision (estimated CER within 30% of measured CER among 79% [76% to 81%] and 81% [77% to 85%], respectively). Corresponding numbers within 15% were 51% [48% to 54%] and 54% [50% to 59%]). Compared with existing equations, the new equations had similar accuracy but showed less bias in individuals with high measured CER., Conclusions: CER can be estimated with commonly available variables with little bias and moderate precision, which may facilitate assessment of accuracy of timed urine collections.

Published
2011
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14. Comparative performance of the CKD Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) Study equations for estimating GFR levels above 60 mL/min/1.73 m2.

Author

Stevens LA, Schmid CH, Greene T, Zhang YL, Beck GJ, Froissart M, Hamm LL, Lewis JB, Mauer M, Navis GJ, Steffes MW, Eggers PW, Coresh J, and Levey AS

Subjects
Adult, Aged, Bias, Chronic Disease, Female, Humans, Kidney Function Tests methods, Kidney Function Tests statistics & numerical data, Male, Mathematics, Middle Aged, Reproducibility of Results, Glomerular Filtration Rate, Kidney Diseases physiopathology
Abstract

Background: The Modification of Diet in Renal Disease (MDRD) Study equation underestimates measured glomerular filtration rate (GFR) at levels>60 mL/min/1.73 m2, with variable accuracy among subgroups; consequently, estimated GFR (eGFR)>or=60 mL/min/1.73 m2 is not reported by clinical laboratories. Here, performance of a more accurate GFR-estimating equation, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, is reported by level of GFR and clinical characteristics., Study Design: Test of diagnostic accuracy., Setting & Participants: Pooled data set of 3,896 people from 16 studies with measured GFR (not used for the development of either equation). Subgroups were defined by eGFR, age, sex, race, diabetes, prior solid-organ transplant, and body mass index., Index Tests: eGFR from the CKD-EPI and MDRD Study equations and standardized serum creatinine., Reference Test: Measured GFR using urinary or plasma clearance of exogenous filtration markers., Results: Mean measured GFR was 68+/-36 (SD) mL/min/1.73 m2. For eGFR<30 mL/min/1.73 m2, both equations have similar bias (median difference compared with measured GFR). For eGFR of 30-59 mL/min/1.73 m2, bias was decreased from 4.9 to 2.1 mL/min/1.73 m2 (57% improvement). For eGFR of 60-89 mL/min/1.73 m2, bias was decreased from 11.9 to 4.2 mL/min/1.73 m2 (61% improvement). For eGFR of 90-119 mL/min/1.73 m2, bias was decreased from 10.0 to 1.9 mL/min/1.73 m2 (75% improvement). Similar or improved performance was noted for most subgroups with eGFR<90 mL/min/1.73 m2, other than body mass index<20 kg/m2, with greater variation noted for some subgroups with eGFR>or=90 mL/min/1.73 m2., Limitations: Limited number of elderly people and racial and ethnic minorities with measured GFR., Conclusions: The CKD-EPI equation is more accurate than the MDRD Study equation overall and across most subgroups. In contrast to the MDRD Study equation, eGFR>or=60 mL/min/1.73 m2 can be reported using the CKD-EPI equation., (Copyright (c) 2010 National Kidney Foundation, Inc. All rights reserved.)

Published
2010
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15. Factors other than glomerular filtration rate affect serum cystatin C levels.

Author

Stevens LA, Schmid CH, Greene T, Li L, Beck GJ, Joffe MM, Froissart M, Kusek JW, Zhang YL, Coresh J, and Levey AS

Subjects
Age Factors, Cross-Sectional Studies, Female, Humans, Kidney Function Tests methods, Male, Predictive Value of Tests, Racial Groups, Sex Factors, Creatinine blood, Cystatin C blood, Glomerular Filtration Rate
Abstract

Cystatin C is an endogenous glomerular filtration marker hence its serum level is affected by the glomerular filtration rate (GFR). To study what other factors might affect it blood level we performed a cross-sectional analysis of 3418 patients which included a pooled dataset of clinical trial participants and a clinical population with chronic kidney disease. The serum cystatin C and creatinine levels were related to clinical and biochemical parameters and errors-in-variables models were used to account for errors in GFR measurements. The GFR was measured as the urinary clearance of 125I-iothalamate and 51Cr-EDTA. Cystatin C was determined at a single laboratory while creatinine was standardized to reference methods and these were 2.1+/-1.1 mg/dL and 1.8+/-0.8 mg/L, respectively. After adjustment for GFR, cystatin C was 4.3% lower for every 20 years of age, 9.2% lower for female gender but only 1.9% lower in blacks. Diabetes was associated with 8.5% higher levels of cystatin C and 3.9% lower levels of creatinine. Higher C-reactive protein and white blood cell count and lower serum albumin were associated with higher levels of cystatin C and lower levels of creatinine. Adjustment for age, gender and race had a greater effect on the association of factors with creatinine than cystatin C. Hence, we found that cystatin C is affected by factors other than GFR which should be considered when the GFR is estimated using serum levels of cystatin C.

Published
2009
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17. [Evaluation of renal function: an update].

Author

Froissart M, Delanaye P, Séronie-Vivien S, and Cristol JP

Subjects
Chronic Disease, Cystatin C, Cystatins analysis, Humans, Glomerular Filtration Rate, Kidney Diseases diagnosis
Abstract

During the last years, GFR estimation has received substantial attention with a focus on comparing results of new formulas with GFR measurements, and standardization of creatinine assays. Calibration of creatinine should improve performances. However, frequently used equations have lower precision in high GFR populations. This is the reason why a continuous effort in improving predicting equations is still needed. The use of calibrated creatinine, the onset of new GFR markers such as cystatin C, and pooling data across many study populations are underway to develop better prediction.

Published
2008
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18. [Cystatin C: current step and future prospects].

Author

Séronie-Vivien S, Delanaye P, Pieroni L, Mariat C, Froissart M, and Cristol JP

Subjects
Biomarkers blood, Cardiovascular Diseases blood, Cardiovascular Diseases diagnosis, Cystatin C, Humans, Kidney Diseases blood, Neoplasms blood, Neoplasms diagnosis, Cystatins blood, Glomerular Filtration Rate, Kidney Diseases diagnosis
Abstract

Cystatin C is a low molecular weight-protein, which may replace creatinine for the evaluation of renal function, particularly in the clinical settings where the relationship between creatinine production and muscular mass impairs the clinical performance of creatinine. This paper intends to summarize the current knowledge about the physiology of cystatin C and about its use as a renal marker, alone or within formulas developed to estimate the glomerular filtration rate. Moreover, this paper reviews the recent data about potential other applications of cystatin C, especially in cardiology, in oncology and in clinical pharmacology.

Published
2008
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19. Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD.

Author

Stevens LA, Coresh J, Schmid CH, Feldman HI, Froissart M, Kusek J, Rossert J, Van Lente F, Bruce RD 3rd, Zhang YL, Greene T, and Levey AS

Subjects
Adult, Cardiovascular Diseases blood, Cardiovascular Diseases epidemiology, Comorbidity, Cystatin C, Female, Humans, Male, Middle Aged, Models, Statistical, Renal Insufficiency, Chronic epidemiology, Biomarkers blood, Creatinine blood, Cystatins blood, Glomerular Filtration Rate physiology, Kidney Function Tests methods, Renal Insufficiency, Chronic blood, Renal Insufficiency, Chronic physiopathology
Abstract

Background: Serum cystatin C was proposed as a potential replacement for serum creatinine in glomerular filtration rate (GFR) estimation. We report the development and evaluation of GFR-estimating equations using serum cystatin C alone and serum cystatin C, serum creatinine, or both with demographic variables., Study Design: Test of diagnostic accuracy., Setting & Participants: Participants screened for 3 chronic kidney disease (CKD) studies in the United States (n = 2,980) and a clinical population in Paris, France (n = 438)., Reference Test: Measured GFR (mGFR)., Index Test: Estimated GFR using the 4 new equations based on serum cystatin C alone, serum cystatin C, serum creatinine, or both with age, sex, and race. New equations were developed by using linear regression with log GFR as the outcome in two thirds of data from US studies. Internal validation was performed in the remaining one third of data from US CKD studies; external validation was performed in the Paris study., Measurements: GFR was measured by using urinary clearance of iodine-125-iothalamate in the US studies and chromium-51-EDTA in the Paris study. Serum cystatin C was measured by using Dade-Behring assay, standardized serum creatinine values were used., Results: Mean mGFR, serum creatinine, and serum cystatin C values were 48 mL/min/1.73 m(2) (5th to 95th percentile, 15 to 95), 2.1 mg/dL, and 1.8 mg/L, respectively. For the new equations, coefficients for age, sex, and race were significant in the equation with serum cystatin C, but 2- to 4-fold smaller than in the equation with serum creatinine. Measures of performance in new equations were consistent across the development and internal and external validation data sets. Percentages of estimated GFR within 30% of mGFR for equations based on serum cystatin C alone, serum cystatin C, serum creatinine, or both levels with age, sex, and race were 81%, 83%, 85%, and 89%, respectively. The equation using serum cystatin C level alone yields estimates with small biases in age, sex, and race subgroups, which are improved in equations including these variables., Limitations: Study population composed mainly of patients with CKD., Conclusions: Serum cystatin C level alone provides GFR estimates that are nearly as accurate as serum creatinine level adjusted for age, sex, and race, thus providing an alternative GFR estimate that is not linked to muscle mass. An equation including serum cystatin C level in combination with serum creatinine level, age, sex, and race provides the most accurate estimates.

Published
2008
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20. Monitoring of glomerular filtration rate in lithium-treated outpatients--an ambulatory laboratory database surveillance.

Author

Bassilios N, Martel P, Godard V, Froissart M, Grünfeld JP, and Stengel B

Subjects
Adult, Age Factors, Aged, Creatinine blood, Databases, Factual, Drug Monitoring, Female, Humans, Lithium Compounds adverse effects, Male, Middle Aged, Population Surveillance, Retrospective Studies, Calcium blood, Glomerular Filtration Rate drug effects, Lithium Compounds therapeutic use
Abstract

Background: The long-term risk of chronic kidney disease (CKD) in lithium (Li)-treated patients has been well established in the recent years., Methods: We have evaluated GFR and serum calcium monitoring in 1179 Li-treated outpatients from an ambulatory laboratory database study. This has been performed in a single private laboratory in Paris from February 1997 to December 2004. Estimated GFR (eGFR) has been calculated using the abbreviated MDRD equation., Results: During an 8-year period, 695 patients (59%) had at least one serum creatinine measurement, whereas 484 had no creatinine measurement. The former group had also more frequent serum Li measurements. Mean serum lithium levels, were similar in both groups, 0.65 mmol/l vs 0.62 mmol/l. The percentage of patients with CKD stage 3 (eGFR 30-59 ml/min/1.73 m(2)) were 36%, 53%, 73% and 77%, and with CKD stage 4, 3%, 5%, 5%, 8% in patients aged 20-39, 40-59, 60-69, and > or = 70 years respectively. There was no significant rise in creatinine measurements (from 35% of the patients with at least one serum creatinine in 2003 to 39% in 2004; P = 0.66) despite intervention to intensify GFR monitoring by physicians. Serum calcium was tested at least once in 212 patients (18%) of whom 15 (7%) were found with hypercalcaemia., Conclusion: A very high percentage of Li-treated outpatients have low eGFR. GFR monitoring is neglected in these patients, the majority of whom are no longer attending specialized clinics. Hypercalcaemia is less common but serum calcium monitoring is even more neglected. Ambulatory laboratory database surveillance provides a powerful means to contribute to CKD screening and monitoring.

Published
2008
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21. Predictive performance of the modification of diet in renal disease and Cockcroft-Gault equations for estimating renal function.

Author

Froissart M, Rossert J, Jacquot C, Paillard M, and Houillier P

Subjects
Adult, Age Factors, Aged, Aged, 80 and over, Bias, Body Mass Index, Body Weight, Chromium Radioisotopes, Creatinine blood, Edetic Acid, Female, Humans, Kidney Failure, Chronic diagnosis, Male, Middle Aged, Predictive Value of Tests, Sex Factors, Glomerular Filtration Rate, Kidney Failure, Chronic diet therapy, Kidney Failure, Chronic physiopathology, Models, Biological
Abstract

Recent recommendations emphasize the need to assess kidney function using creatinine-based predictive equations to optimize the care of patients with chronic kidney disease. The most widely used equations are the Cockcroft-Gault (CG) and the simplified Modification of Diet in Renal Disease (MDRD) formulas. However, they still need to be validated in large samples of subjects, including large non-U.S. cohorts. Renal clearance of (51)Cr-EDTA was compared with GFR estimated using either the CG equation or the MDRD formula in a cohort of 2095 adult Europeans (863 female and 1232 male; median age, 53.2 yr; median measured GFR, 59.8 ml/min per 1.73 m(2)). When the entire study population was considered, the CG and MDRD equations showed very limited bias. They overestimated measured GFR by 1.94 ml/min per 1.73 m(2) and underestimated it by 0.99 ml/min per 1.73 m(2), respectively. However, analysis of subgroups defined by age, gender, body mass index, and GFR level showed that the biases of the two formulas could be much larger in selected populations. Furthermore, analysis of the SD of the mean difference between estimated and measured GFR showed that both formulas lacked precision; the CG formula was less precise than the MDRD one in most cases. In the whole study population, the SD was 15.1 and 13.5 ml/min per 1.73 m(2) for the CG and MDRD formulas, respectively. Finally, 29.2 and 32.4% of subjects were misclassified when the CG and MDRD formulas were used to categorize subjects according to the Kidney Disease Outcomes Quality Initiative chronic kidney disease classification, respectively.

Published
2005
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22. [Elevated serum creatinine].

Author

Houillier P and Froissart M

Subjects
Acute Kidney Injury blood, Acute Kidney Injury diagnostic imaging, Acute Kidney Injury therapy, Acute Kidney Injury urine, Diagnosis, Differential, Humans, Kidney Failure, Chronic blood, Kidney Failure, Chronic diagnostic imaging, Kidney Failure, Chronic therapy, Kidney Failure, Chronic urine, Models, Biological, Proteinuria diagnosis, Sodium urine, Time Factors, Ultrasonography, Acute Kidney Injury diagnosis, Creatinine blood, Glomerular Filtration Rate, Kidney Failure, Chronic diagnosis
Published
2005

25. Adiposity and risk of decline in glomerular filtration rate : Meta-analysis of individual participant data in a global consortium

Author

Chang AR, Grams ME, Ballew SH, Bilo H, Correa A, Evans M, Gutierrez OM, Hosseinpanah F, Iseki K, Kenealy T, Klein B, Kronenberg F, Lee BJ, Li Y, Miura K, Navaneethan SD, Roderick PJ, Valdivielso JM, Visseren FLJ, Zhang L, Gansevoort RT, Hallan SI, Levey AS, Matsushita K, Shalev V, Woodward M, Astor B, Appel L, Greene T, Chen T, Chalmers J, Arima H, Perkovic V, Yatsuya H, Tamakoshi K, Hirakawa Y, Coresh J, Sang Y, Polkinghorne K, Chadban S, Atkins R, Levin A, Djurdjev O, Klein R, Lee K, Liu L, Zhao M, Wang F, Wang J, Tang M, Heine G, Emrich I, Zawada A, Bauer L, Nally J, Schold J, Shlipak M, Sarnak M, Katz R, Hiramoto J, Iso H, Yamagishi K, Umesawa M, Muraki I, Fukagawa M, Maruyama S, Hamano T, Hasegawa T, Fujii N, Jafar T, Hatcher J, Poulter N, Chaturvedi N, Wheeler D, Emberson J, Townend J, Landray M, Brenner H, Schöttker B, Saum KU, Rothenbacher D, Fox C, Hwang SJ, Köttgen A, Schneider MP, Eckardt KU, Green J, Kirchner HL, Ito S, Miyazaki M, Nakayama M, Yamada G, Cirillo M, Romundstad S, Øvrehus M, Langlo KA, Irie F, Sairenchi T, Rebholz CM, Young B, Boulware LE, Ishikawa S, Yano Y, Kotani K, Nakamura T, Jee SH, Kimm H, Mok Y, Chodick G, Wetzels JFM, Blankestijn PJ, van Zuilen AD, Bots M, Inker L, Peralta C, Kollerits B, Ritz E, Nitsch D, Fletcher A, Bottinger E, Nadkarni GN, Ellis SB, Nadukuru R, Fernandez E, Betriu A, Bermudez-Lopez M, Stengel B, Metzger M, Flamant M, Houillier P, Haymann JP, Froissart M, Ueshima H, Okayama A, Tanaka S, Okamura T, Elley CR, Collins JF, Drury PL, Ohkubo T, Asayama K, Metoki H, Kikuya M, Iseki C, Nelson RG, Knowler WC, Bakker SJL, Heerspink HJL, Brunskill N, Major R, Shepherd D, Medcalf J, Jassal SK, Bergstrom J, Ix JH, Barrett-Connor E, Kovesdy C, Kalantar-Zadeh K, Sumida K, Muntner P, Warnock D, Judd S, Panwar B, de Zeeuw D, Brenner B, Sedaghat S, Ikram MA, Hoorn EJ, Dehghan A, Wong TY, Sabanayagam C, Cheng CY, Banu R, Segelmark M, Stendahl M, Schön S, Tangri N, Sud M, Naimark D, Wen CP, Tsao CK, Tsai MK, Chen CH, Konta T, Hirayama A, Ichikawa K, Hadaegh F, Mirbolouk M, Azizi F, Solbu MD, Jenssen TG, Eriksen BO, Eggen AE, Lannfelt L, Larsson A, Ärnlöv J, Landman GWD, van Hateren KJJ, Kleefstra N, Chen J, Kwak L, Surapaneni A., Chang, Ar, Grams, Me, Ballew, Sh, Bilo, H, Correa, A, Evans, M, Gutierrez, Om, Hosseinpanah F, Iseki K, Kenealy, T, Klein, B, Kronenberg, F, Lee, Bj, Li, Y, Miura, K, Navaneethan, Sd, Roderick, Pj, Valdivielso, Jm, Visseren, Flj, Zhang, L, Gansevoort, Rt, Hallan, Si, Levey, A, Matsushita, K, Shalev, V, Woodward, M, Astor, B, Appel, L, Greene, T, Chen, T, Chalmers, J, Arima, H, Perkovic, V, Yatsuya, H, Tamakoshi, K, Hirakawa, Y, Coresh, J, Sang, Y, Polkinghorne, K, Chadban, S, Atkins, R, Levin, A, Djurdjev, O, Klein, R, Lee, K, Liu, L, Zhao, M, Wang, F, Wang, J, Tang, M, Heine, G, Emrich, I, Zawada, A, Bauer, L, Nally, J, Schold, J, Shlipak, M, Sarnak, M, Katz, R, Hiramoto, J, Iso, H, Yamagishi, K, Umesawa, M, Muraki, I, Fukagawa, M, Maruyama, S, Hamano, T, Hasegawa, T, Fujii, N, Jafar, T, Hatcher, J, Poulter, N, Chaturvedi, N, Wheeler, D, Emberson, J, Townend, J, Landray, M, Brenner, H, Schöttker, B, Saum, Ku, Rothenbacher, D, Fox, C, Hwang, Sj, Köttgen, A, Schneider, Mp, Eckardt, Ku, Green, J, Kirchner, Hl, Ito, S, Miyazaki, M, Nakayama, M, Yamada, G, Cirillo, M, Romundstad, S, Øvrehus, M, Langlo, Ka, Irie, F, Sairenchi, T, Rebholz, Cm, Young, B, Boulware, Le, Ishikawa, S, Yano, Y, Kotani, K, Nakamura, T, Jee, Sh, Kimm, H, Mok, Y, Chodick, G, Wetzels, Jfm, Blankestijn, Pj, van Zuilen, Ad, Bots, M, Inker, L, Peralta, C, Kollerits, B, Ritz, E, Nitsch, D, Fletcher, A, Bottinger, E, Nadkarni, Gn, Ellis, Sb, Nadukuru, R, Fernandez, E, Betriu, A, Bermudez-Lopez, M, Stengel, B, Metzger, M, Flamant, M, Houillier, P, Haymann, Jp, Froissart, M, Ueshima, H, Okayama, A, Tanaka, S, Okamura, T, Elley, Cr, Collins, Jf, Drury, Pl, Ohkubo, T, Asayama, K, Metoki, H, Kikuya, M, Iseki, C, Nelson, Rg, Knowler, Wc, Bakker, Sjl, Heerspink, Hjl, Brunskill, N, Major, R, Shepherd, D, Medcalf, J, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett-Connor, E, Kovesdy, C, Kalantar-Zadeh, K, Sumida, K, Muntner, P, Warnock, D, Judd, S, Panwar, B, de Zeeuw, D, Brenner, B, Sedaghat, S, Ikram, Ma, Hoorn, Ej, Dehghan, A, Wong, Ty, Sabanayagam, C, Cheng, Cy, Banu, R, Segelmark, M, Stendahl, M, Schön, S, Tangri, N, Sud, M, Naimark, D, Wen, Cp, Tsao, Ck, Tsai, Mk, Chen, Ch, Konta, T, Hirayama, A, Ichikawa, K, Hadaegh, F, Mirbolouk, M, Azizi, F, Solbu, Md, Jenssen, Tg, Eriksen, Bo, Eggen, Ae, Lannfelt, L, Larsson, A, Ärnlöv, J, Landman, Gwd, van Hateren, Kjj, Kleefstra, N, Chen, J, Kwak, L, Surapaneni, A., Lifestyle Medicine (LM), Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Asayama, Kei, and Sedaghat, SeyyedMah

Subjects
CHRONIC KIDNEY-DISEASE, Male, 030232 urology & nephrology, 030204 cardiovascular system & hematology, OBESITY PARADOX, Body Mass Index, BMI, eGFR, CKD-PC, Cohort Studies, 0302 clinical medicine, Risk Factors, Urologi och njurmedicin, Medicine, ALL-CAUSE MORTALITY, Adiposity, 2. Zero hunger, Aged, 80 and over, Medicine(all), education.field_of_study, Hazard ratio, ASSOCIATION, General Medicine, Middle Aged, 3. Good health, Cohort, Female, Waist Circumference, Life Sciences & Biomedicine, WAIST CIRCUMFERENCE, Obesity paradox, Glomerular Filtration Rate, Adult, Waist, Population, Renal function, 03 medical and health sciences, Medicine, General & Internal, General & Internal Medicine, CKD, Urology and Nephrology, Humans, Mortality, education, Aged, Science & Technology, business.industry, Research, medicine.disease, Body Height, BODY-MASS INDEX, Kidney Failure, Chronic, WEIGHT, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, Body mass index, Demography, Kidney disease
Abstract

ObjectiveTo evaluate the associations between adiposity measures (body mass index, waist circumference, and waist-to-height ratio) with decline in glomerular filtration rate (GFR) and with all cause mortality.DesignIndividual participant data meta-analysis.SettingCohorts from 40 countries with data collected between 1970 and 2017.ParticipantsAdults in 39 general population cohorts (n=5 459 014), of which 21 (n=594 496) had data on waist circumference; six cohorts with high cardiovascular risk (n=84 417); and 18 cohorts with chronic kidney disease (n=91 607).Main outcome measuresGFR decline (estimated GFR decline ≥40%, initiation of kidney replacement therapy or estimated GFR 2) and all cause mortality.ResultsOver a mean follow-up of eight years, 246 607 (5.6%) individuals in the general population cohorts had GFR decline (18 118 (0.4%) end stage kidney disease events) and 782 329 (14.7%) died. Adjusting for age, sex, race, and current smoking, the hazard ratios for GFR decline comparing body mass indices 30, 35, and 40 with body mass index 25 were 1.18 (95% confidence interval 1.09 to 1.27), 1.69 (1.51 to 1.89), and 2.02 (1.80 to 2.27), respectively. Results were similar in all subgroups of estimated GFR. Associations weakened after adjustment for additional comorbidities, with respective hazard ratios of 1.03 (0.95 to 1.11), 1.28 (1.14 to 1.44), and 1.46 (1.28 to 1.67). The association between body mass index and death was J shaped, with the lowest risk at body mass index of 25. In the cohorts with high cardiovascular risk and chronic kidney disease (mean follow-up of six and four years, respectively), risk associations between higher body mass index and GFR decline were weaker than in the general population, and the association between body mass index and death was also J shaped, with the lowest risk between body mass index 25 and 30. In all cohort types, associations between higher waist circumference and higher waist-to-height ratio with GFR decline were similar to that of body mass index; however, increased risk of death was not associated with lower waist circumference or waist-to-height ratio, as was seen with body mass index.ConclusionsElevated body mass index, waist circumference, and waist-to-height ratio are independent risk factors for GFR decline and death in individuals who have normal or reduced levels of estimated GFR.

Published
2019

26. Relative risks of Chronic Kidney Disease for mortality and End Stage Renal Disease across races is similar

Author

Wright, Jt, Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Coresh, J, Matsushita, K, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Liu, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, F, Curhan, G, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, J, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, L, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasard, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, J, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Inker, L, Menon, V, Fried, Lf, Kramer, H, Boer, De, I, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, J, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Jong, De, Mahmoodi, Bk, Bakker, Sj, Bernardo, R, Kaur, Jassal, S, Barrett Connor, E, Bergstrom, J, Heerspink, Hj, Brenner, B, Zeeuw, De, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Wu, Be, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, Br, Ballew, Sh, Grams, M, Sang, Y, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Wright, Jt, Jr, Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Coresh, J, Matsushita, K, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Liu, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, F, Curhan, G, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, J, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, L, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasard, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, J, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Ad, Sarnak, M, Levey, A, Inker, L, Menon, V, Fried, Lf, Kramer, H, De, Boer, I, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, J, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, De, Jong, Pe, Mahmoodi, Bk, Bakker, Sj, Bernardo, R, Kaur, Jassal, S, Barrett Connor, E, Bergstrom, J, Heerspink, Hj, Brenner, B, De, Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Be, Wu, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Hemmelgarn, Br, Ballew, Sh, Grams, M, Sang, Y, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.

Subjects
Male, GLOMERULAR-FILTRATION-RATE, Cohort Studies, Risk Factors, eGFR, Odds Ratio, ASSOCIATIONS, African Continental Ancestry Group, Aged, 80 and over, education.field_of_study, end-stage renal disease, Hazard ratio, PROTEINURIA, Urology & Nephrology, Middle Aged, CKD-EPI EQUATION, 3. Good health, PREVALENCE, Nephrology, Cardiovascular Diseases, Creatinine, ethnicity, Female, medicine.symptom, epidemiology and outcomes, Glomerular Filtration Rate, Asian Continental Ancestry Group, Adult, medicine.medical_specialty, Population, European Continental Ancestry Group, Renal function, Black People, ALL-CAUSE, Article, White People, End stage renal disease, Asian People, Internal medicine, medicine, Chronic Kidney Disease Prognosis Consortium, Albuminuria, Humans, Renal Insufficiency, Chronic, education, Aged, business.industry, 1103 Clinical Sciences, Odds ratio, POPULATION COHORTS, medicine.disease, INDIVIDUALS, Endocrinology, Relative risk, COLLABORATIVE METAANALYSIS, mortality risk, Kidney Failure, Chronic, Renal disorders Radboud Institute for Health Sciences [Radboudumc 11], business, HIGHER ALBUMINURIA, chronic kidney disease, Kidney disease
Abstract

Item does not contain fulltext Some suggest race-specific cutpoints for kidney measures to define and stage chronic kidney disease (CKD), but evidence for race-specific clinical impact is limited. To address this issue, we compared hazard ratios of estimated glomerular filtration rates (eGFR) and albuminuria across races using meta-regression in 1.1 million adults (75% Asians, 21% Whites, and 4% Blacks) from 45 cohorts. Results came mainly from 25 general population cohorts comprising 0.9 million individuals. The associations of lower eGFR and higher albuminuria with mortality and end-stage renal disease (ESRD) were largely similar across races. For example, in Asians, Whites, and Blacks, the adjusted hazard ratios (95% confidence interval) for eGFR 45-59 versus 90-104 ml/min per 1.73 m(2) were 1.3 (1.2-1.3), 1.1 (1.0-1.2), and 1.3 (1.1-1.7) for all-cause mortality, 1.6 (1.5-1.7), 1.4 (1.2-1.7), and 1.4 (0.7-2.9) for cardiovascular mortality, and 27.6 (11.1-68.7), 11.2 (6.0-20.9), and 4.1 (2.2-7.5) for ESRD, respectively. The corresponding hazard ratios for urine albumin-to-creatinine ratio 30-299 mg/g or dipstick 1+ versus an albumin-to-creatinine ratio under 10 or dipstick negative were 1.6 (1.4-1.8), 1.7 (1.5-1.9), and 1.8 (1.7-2.1) for all-cause mortality, 1.7 (1.4-2.0), 1.8 (1.5-2.1), and 2.8 (2.2-3.6) for cardiovascular mortality, and 7.4 (2.0-27.6), 4.0 (2.8-5.9), and 5.6 (3.4-9.2) for ESRD, respectively. Thus, the relative mortality or ESRD risks of lower eGFR and higher albuminuria were largely similar among three major races, supporting similar clinical approach to CKD definition and staging, across races.

Published
2014

27. Age and Association of Kidney Measures With Mortality and End-stage Renal Disease

Author

Wright, Jt, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Tonelli, M, Hemmelgarn, Br, Bello, A, James, Mt, Coresh, J, Matsushita, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Levey, As, Inker, La, Menon, V, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Jong, De, Mahmoodi, Bk, Heerspink, Hj, Jassal, Sk, Barrett Connor, E, Bergstrom, J, Brenner, Be, Zeeuw, De, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Wright JT Jr, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Woodward, M, Arima, H, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Tonelli, M, Hemmelgarn, Br, Bello, A, James, Mt, Coresh, J, Matsushita, K, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Kitamura, A, Ohira, T, Yamagishi, K, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Emberson, J, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, Sc, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, van Zuilen AD, Sarnak, M, Levey, A, Inker, La, Menon, V, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, de Jong PE, Mahmoodi, Bk, Heerspink, Hj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Brenner, Be, de Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Lim, Je, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Cp, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Drion, I, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad, H.

Subjects
Male, BLOOD-PRESSURE, urologic and male genital diseases, Kidney, età, GLOMERULAR-FILTRATION-RATE, Cohort Studies, eGFR, Young adult, Renal disorder [IGMD 9], ALL-CAUSE MORTALITY, GENERAL-POPULATION, insufficienza renale, biology, CYSTATIN C, CARDIOVASCULAR RISK, Age Factors, General Medicine, Middle Aged, female genital diseases and pregnancy complications, RISK POPULATION COHORTS, medicine.anatomical_structure, Female, medicine.symptom, Glomerular Filtration Rate, albuminuria, rischio, mortalità, Adult, Risk, medicine.medical_specialty, Adolescent, Renal function, Context (language use), End stage renal disease, Young Adult, Internal medicine, medicine, Albuminuria, Humans, OLDER-ADULTS, Aged, urogenital system, business.industry, URINARY ALBUMIN EXCRETION, medicine.disease, Endocrinology, Cystatin C, COLLABORATIVE METAANALYSIS, biology.protein, Kidney Failure, Chronic, business, Kidney disease
Abstract

Context Chronic kidney disease (CKD) is prevalent in older individuals, but the risk implications of low estimated glomerular filtration rate (eGFR) and high albuminuria across the full age range are controversial.Objective To evaluate possible effect modification (interaction) by age of the association of eGFR and albuminuria with clinical risk, examining both relative and absolute risks.Design, Setting, and Participants Individual-level meta-analysis including 2 051 244 participants from 33 general population or high-risk (of vascular disease) cohorts and 13 CKD cohorts from Asia, Australasia, Europe, and North/South America, conducted in 1972-2011 with a mean follow-up time of 5.8 years (range, 0-31 years).Main Outcome Measures Hazard ratios (HRs) of mortality and end-stage renal disease (ESRD) according to eGFR and albuminuria were meta-analyzed across age categories after adjusting for sex, race, cardiovascular disease, diabetes, systolic blood pressure, cholesterol, body mass index, and smoking. Absolute risks were estimated using HRs and average incidence rates.Results Mortality (112 325 deaths) and ESRD (8411 events) risks were higher at lower eGFR and higher albuminuria in every age category. In general and high-risk cohorts, relative mortality risk for reduced eGFR decreased with increasing age; eg, adjusted HRs at an eGFR of 45 mL/min/1.73 m(2) vs 80 mL/min/1.73 m(2) were 3.50 (95% CI, 2.55-4.81), 2.21 (95% CI, 2.02-2.41), 1.59 (95% CI, 1.42-1.77), and 1.35 (95% CI, 1.23-1.48) in age categories 18-54, 55-64, 65-74, and >= 75 years, respectively (P Conclusions Both low eGFR and high albuminuria were independently associated with mortality and ESRD regardless of age across a wide range of populations. Mortality showed lower relative risk but higher absolute risk differences at older age.

Published
2012
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28. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate

Author

Matsushita, K, Mahmoodi, Bk, Woodward, M, Emberson, Jr, Jafar, Th, Jee, Sh, Polkinghorne, Kr, Shankar, A, Smith, Dh, Tonelli, M, Warnock, Dg, Wen, Cp, Coresh, J, Gansevoort, Rt, Hemmelgarn, Br, Levey, As, Chronic, Kidney, Disease, Prognosis, Consortium, Wright, J, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Ohira, T, Kitamura, A, Yamagishi, K, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, Cs, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Johnson, Es, Thorp, Ml, Weiss, Jw, Collins, Aj, Li, S, Chen, Sc, Vassalotti, Ja, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Sarnak, M, Menon, V, Boer, De, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Nakayama, M, Metoki, H, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Jong, De, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Heerspink, Hj, Zeeuw, De, D, Brenner, Be, Muntner, P, Judd, S, Mcclellan, W, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Larsson, A, Lannfelt, L, Bilo, Hj, Kleefstra, N, Groenier, Kh, Drion, I, Joosten, H, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Matsushita, K, Mahmoodi, Bk, Woodward, M, Emberson, Jr, Jafar, Th, Jee, Sh, Polkinghorne, Kr, Shankar, A, Smith, Dh, Tonelli, M, Warnock, Dg, Wen, Cp, Coresh, J, Gansevoort, Rt, Hemmelgarn, Br, Levey, A, Chronic, Kidney, Disease, Prognosi, Consortium, Wright, J, Appel, Lj, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Yatsuya, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Sang, Y, Atkins, Rc, Chadban, S, Klein, R, Klein, Be, Lee, Ke, Wang, H, Wang, F, Zhang, L, Zuo, L, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, Lf, Iso, H, Ohira, T, Kitamura, A, Yamagishi, K, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, Landray, Mj, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Müller, H, Schöttker, B, Fox, C, Hwang, Sj, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Cirillo, Massimo, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Sairenchi, T, Johnson, E, Thorp, Ml, Weiss, Jw, Collins, Aj, Li, S, Chen, Sc, Vassalotti, Ja, Lee, Bj, Wetzels, Jf, Blankestijn, Pj, Van, Zuilen, Ad, Sarnak, M, Menon, V, De, Boer, Ih, Kramer, Hj, Kronenberg, F, Kollerits, B, Ritz, E, Roderick, P, Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, Jp, Houillier, P, Flamant, M, Ohkubo, T, Nakayama, M, Metoki, H, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, De, Jong, Pe, Bakker, Sj, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Heerspink, Hj, De, Zeeuw, D, Brenner, Be, Muntner, P, Judd, S, Mcclellan, W, Kimm, H, Jo, J, Mok, Y, Choi, E, Rossing, P, Parving, Hh, Tangri, N, Naimark, D, Wen, Sf, Tsao, Ck, Tsai, Mk, Ärnlöv, J, Larsson, A, Lannfelt, L, Bilo, Hj, Kleefstra, N, Groenier, Kh, Drion, I, Joosten, H, Ballew, Sh, Grams, M, Camarata, L, Hui, X, Seltzer, J, Winegrad, H., Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)

Subjects
CHRONIC KIDNEY-DISEASE, Gerontology, Male, EVALUATION PROGRAM KEEP, Population, Renal function, Black People, Ckd epi equation, urologic and male genital diseases, Risk Assessment, White People, Article, Decision Support Techniques, Cohort Studies, Sex Factors, Asian People, EPIDEMIOLOGY COLLABORATION EQUATION, Diabetes mellitus, CYSTATIN-C, Medicine, Humans, education, ALL-CAUSE MORTALITY, Cardiovascular mortality, Aged, Renal disorder [IGMD 9], GENERAL-POPULATION, education.field_of_study, business.industry, CARDIOVASCULAR RISK, Hazard ratio, STAGE RENAL-DISEASE, General Medicine, POPULATION COHORTS, Middle Aged, Models, Theoretical, medicine.disease, female genital diseases and pregnancy complications, Net reclassification improvement, SERUM CREATININE VALUES, Cardiovascular Diseases, Kidney Failure, Chronic, Female, business, Algorithms, Demography, Glomerular Filtration Rate
Abstract

Contains fulltext : 110640.pdf (Publisher’s version ) (Closed access) CONTEXT: The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation more accurately estimates glomerular filtration rate (GFR) than the Modification of Diet in Renal Disease (MDRD) Study equation using the same variables, especially at higher GFR, but definitive evidence of its risk implications in diverse settings is lacking. OBJECTIVE: To evaluate risk implications of estimated GFR using the CKD-EPI equation compared with the MDRD Study equation in populations with a broad range of demographic and clinical characteristics. DESIGN, SETTING, AND PARTICIPANTS: A meta-analysis of data from 1.1 million adults (aged >/= 18 years) from 25 general population cohorts, 7 high-risk cohorts (of vascular disease), and 13 CKD cohorts. Data transfer and analyses were conducted between March 2011 and March 2012. MAIN OUTCOME MEASURES: All-cause mortality (84,482 deaths from 40 cohorts), cardiovascular mortality (22,176 events from 28 cohorts), and end-stage renal disease (ESRD) (7644 events from 21 cohorts) during 9.4 million person-years of follow-up; the median of mean follow-up time across cohorts was 7.4 years (interquartile range, 4.2-10.5 years). RESULTS: Estimated GFR was classified into 6 categories (>/=90, 60-89, 45-59, 30-44, 15-29, and /=65 years), sex, race/ethnicity (white, Asian, and black), and presence or absence of diabetes and hypertension. The results in the high-risk and CKD cohorts were largely consistent with the general population cohorts. CONCLUSION: The CKD-EPI equation classified fewer individuals as having CKD and more accurately categorized the risk for mortality and ESRD than did the MDRD Study equation across a broad range of populations.

Published
2012

29. Association of a Low-Protein Diet With Slower Progression of CKD

Author

Metzger, M., Yuan, W.L., Haymann, J.P., Flamant, M., Houillier, P., Thervet, E., Boffa, J.J., Vrtovsnik, F., Froissart, M., Bankir, L., Fouque, D., Stengel, B., Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), CIC - CHU Bichat, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de recherche sur l'Inflammation (CRI (UMR_S_1149 / ERL_8252 / U1149)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Métabolisme et physiologie rénale (CRC - UMR_S 1138), Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Université Paris Descartes - Paris 5 (UPD5), Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), Service de néphrologie, Hospices Civils de Lyon (HCL)-Hôpital Edouard Herriot [CHU - HCL], Hospices Civils de Lyon (HCL), Cardiovasculaire, métabolisme, diabétologie et nutrition (CarMeN), Hospices Civils de Lyon (HCL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National de la Recherche Agronomique (INRA), The NephroTest CKD cohort study was supported by the following grants: INSERM GIS-IReSP AO 8113LS TGIR (BS), French Ministry of Health AOM 09114 (MFr), INSERM AO 8022LS (BS), Agence de la Biomédecine R0 8156LL (B.S.), AURA (MFr), and Roche 2009-152-447G (MFr)., Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC), CHU Tenon [APHP], Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), École pratique des hautes études (EPHE)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-École pratique des hautes études (EPHE)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Pillet, Lauriane, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre National de la Recherche Scientifique (CNRS)-Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
glomerular filtration rate, function, end-stage renal disease, vasopressin, [SDV]Life Sciences [q-bio], restriction, urinary urea excretion, dietary protein intake, Urology & Nephrology, lcsh:Diseases of the genitourinary system. Urology, lcsh:RC870-923, decline, mortality, rate, [SDV] Life Sciences [q-bio], term-follow-up, nutrition, prevention, Clinical Research, glomerular filtration, mdrd, adherence, chronic kidney-disease, chronic renal-disease
Abstract

Open access article; International audience; Introduction: Reducing protein intake is recommended for slowing chronic kidney disease (CKD) progression, but assessment of its true effectiveness is sparse. Methods: Using the Maroni formula, we assessed dietary protein intake (DPI) from 24-hour urinary urea excretion in 1594 patients (67% men and 33% women) with CKD, 784 of whom also had 7-day food records. Cause-specific hazard ratios (HRs) and 95% confidence intervals for the competing risks of DPI-associated end-stage renal disease (ESRD) or death were estimated in 1412 patients with baseline glomerular filtration rate \textgreater= 15 ml/min per 1.73 m(2), measured by Cr-51-EDTA renal clearance (mGFR). Results: Overall, mean DPI estimated from urea excretion was 1.09 +/- 0.30 g/kg of body weight per day (range = 0.34 - 2.76); 20% of patients had values \textgreater 1.3 g/kg per day, and 1.9% had values \textless 0.6 g/kg per day. Urea excretion and food records produced similar estimates of mean DPI. The lower the mGFR, the lower the mean DPI. Over a median follow-up of 5.6 years, there were 319 ESRD events and 189 pre-ESRD deaths. After adjusting for relevant covariates, each 0.1 g/kg daily higher baseline urea excretion - based DPI or food record - based DPI was associated with an HR for ESRD of 1.05 (95% confidence interval 1.01 - 1.10) or 1.09 (95% confidence interval 1.04 - 1.14), respectively. HRs were stronger in patients with baseline mGFR \textless 30 ml/min per 1.73 m(2). There was no association with mortality. The mean age of the patients was 59 +/- 15 years, and mean body mass index was 26.6 +/- 5.2 kg/m(2). Conclusion: In this prospective observational study, the lower the baseline DPI, the slower the progression toward ESRD. Most importantly, the absence of threshold for the relation between DPI and ESRD risk indicates that there is no optimal DPI in the range observed in this cohort.

Published
2018
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30. Past Decline Versus Current eGFR and Subsequent Mortality Risk

Author

Naimark DMJ, Grams ME, Matsushita K, Black C, Drion I, Fox CS, Inker LA, Ishani A, Jee SA, Kitamura A, Lea JP, Nally J, Peralta CA, Rothenbacher D, Ryu S, Tonelli M, Yatsuya H, Coresh J, Gansevoort RT, Warnock DG, Woodward M, de Jong PE, the CKD Prognosis Consortium, Wright JTJr, Appel LJ, Greene T, MacMahon S, Chalmers J, Arima H, Yamashita K, Toyoshima H, Tamakoshi K, Hemmelgarn B, James M, Sang Y, Atkins RC, Polkinghorne KR, Chadban S, Shankar A, Klein R, Klein BEK, Lee KE, Levin A, Djurdjev O, Sacks FM, Curhan GC, Zawada AM, Rogacev KS, Seiler S, Heine GH, Navaneethan SD, Schold JD, Shlipak M, Sarnak MJ, Katz R, Imano H, Yamagishi K, Wheeler DC, Emberson J, Townend JN, Landray MJ, Brenner H, Müller H, Schöttker B, Hwang S-J, Meigs JB, Uphadhay A, Green J, Kirchner HL, Perkins R, Chang AR, Fluck N, Prescott GJ, Cirillo M, Hallan S, Aasarød K, Øien CM, Radtke M, Irie F, Iso H, Sairenchi T, Smith DH, Thorp ML, Johnson ES, Lee BJ, Guallar E, Chang SY, Cho J, Shin H, Chodick G, Shalev V, Birnbaum YC, Shainberg B, Wetzels JFM, Blankestijn PJ, van Zuilen AD, Levey AS, Neaton JD, Froissart M, Stengel B, Metzger M, Haymann J-P, Houillier P, Flamant M, Elley CR, Kenealy T, Moyes SA, Collins JF, Drury PL, Ohkubo T, Metoki H, Nakayama M, Imai Y, Iseki K, Nelson RG, Knowler WC, Bakker SJL, LHillege H, Jassal SK, Bergstrom J, Ix JH, Barrett-Connor E, Heerspink HJL, Brenner BE, de Zeeuw D, Kimm H, Mok Y, Tangri N, Wen C-P, Wen S-F, Tsao C-K, Tsai M-K, Ärnlöv J, Lannfelt L, Larsson A, Kovesdy CP, Kalantar-Zadeh K, Bilo HJ, Kleefstra N, Groenier KH, Joosten H, Ballew SH, Naimark, Dmj, Grams, Me, Matsushita, K, Black, C, Drion, I, Fox, C, Inker, La, Ishani, A, Jee, Sa, Kitamura, A, Lea, Jp, Nally, J, Peralta, Ca, Rothenbacher, D, Ryu, S, Tonelli, M, Yatsuya, H, Coresh, J, Gansevoort, Rt, Warnock, Dg, Woodward, M, de Jong, Pe, the CKD Prognosis, Consortium, Wright, Jtjr, Appel, Lj, Greene, T, Macmahon, S, Chalmers, J, Arima, H, Yamashita, K, Toyoshima, H, Tamakoshi, K, Hemmelgarn, B, James, M, Sang, Y, Atkins, Rc, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Bek, Lee, Ke, Levin, A, Djurdjev, O, Sacks, Fm, Curhan, Gc, Zawada, Am, Rogacev, K, Seiler, S, Heine, Gh, Navaneethan, Sd, Schold, Jd, Shlipak, M, Sarnak, Mj, Katz, R, Imano, H, Yamagishi, K, Wheeler, Dc, Emberson, J, Townend, Jn, Landray, Mj, Brenner, H, Müller, H, Schöttker, B, Hwang, S-J, Meigs, Jb, Uphadhay, A, Green, J, Kirchner, Hl, Perkins, R, Chang, Ar, Fluck, N, Prescott, Gj, Cirillo, M, Hallan, S, Aasarød, K, Øien, Cm, Radtke, M, Irie, F, Iso, H, Sairenchi, T, Smith, Dh, Thorp, Ml, Johnson, E, Lee, Bj, Guallar, E, Chang, Sy, Cho, J, Shin, H, Chodick, G, Shalev, V, Birnbaum, Yc, Shainberg, B, Wetzels, Jfm, Blankestijn, Pj, van Zuilen, Ad, Levey, A, Neaton, Jd, Froissart, M, Stengel, B, Metzger, M, Haymann, J-P, Houillier, P, Flamant, M, Elley, Cr, Kenealy, T, Moyes, Sa, Collins, Jf, Drury, Pl, Ohkubo, T, Metoki, H, Nakayama, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Bakker, Sjl, Lhillege, H, Jassal, Sk, Bergstrom, J, Ix, Jh, Barrett-Connor, E, Heerspink, Hjl, Brenner, Be, de Zeeuw, D, Kimm, H, Mok, Y, Tangri, N, Wen, C-P, Wen, S-F, Tsao, C-K, Tsai, M-K, Ärnlöv, J, Lannfelt, L, Larsson, A, Kovesdy, Cp, Kalantar-Zadeh, K, Bilo, Hj, Kleefstra, N, Groenier, Kh, Joosten, H, Ballew, Sh, Cardiovascular Centre (CVC), and Groningen Kidney Center (GKC)

Subjects
Gerontology, Male, CHRONIC KIDNEY-DISEASE, medicine.medical_specialty, Time Factors, 030232 urology & nephrology, Renal function, 030204 cardiovascular system & hematology, ALL-CAUSE, GLOMERULAR-FILTRATION-RATE, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Cause of Death, Epidemiology, Risk of mortality, medicine, EQUATION, Humans, Clinical Epidemiology, Renal Insufficiency, Chronic, Aged, Proportional Hazards Models, business.industry, Hazard ratio, STAGE RENAL-DISEASE, DEATH, General Medicine, Middle Aged, POPULATION COHORTS, Confidence interval, Increased risk, Nephrology, CARDIOVASCULAR-DISEASE, COLLABORATIVE METAANALYSIS, Female, business, HIGHER ALBUMINURIA, All cause mortality, Glomerular Filtration Rate
Abstract

A single determination of eGFR associates with subsequent mortality risk. Prior decline in eGFR indicates loss of kidney function, but the relationship to mortality risk is uncertain. We conducted an individual-level meta-analysis of the risk of mortality associated with antecedent eGFR slope, adjusting for established risk factors, including last eGFR, among 1.2 million subjects from 12 CKD and 22 other cohorts within the CKD Prognosis Consortium. Over a 3-year antecedent period, 12% of participants in the CKD cohorts and 11% in the other cohorts had an eGFR slope-5 ml/min per 1.73 m(2) per year, whereas 7% and 4% had a slope5 ml/min per 1.73 m(2) per year, respectively. Compared with a slope of 0 ml/min per 1.73 m(2) per year, a slope of -6 ml/min per 1.73 m(2) per year associated with adjusted hazard ratios for all-cause mortality of 1.25 (95% confidence interval [95% CI], 1.09 to 1.44) among CKD cohorts and 1.15 (95% CI, 1.01 to 1.31) among other cohorts during a follow-up of 3.2 years. A slope of +6 ml/min per 1.73 m(2) per year also associated with higher all-cause mortality risk, with adjusted hazard ratios of 1.58 (95% CI, 1.29 to 1.95) among CKD cohorts and 1.43 (95% CI, 1.11 to 1.84) among other cohorts. Results were similar for cardiovascular and noncardiovascular causes of death and stronger for longer antecedent periods (3 versus3 years). We conclude that prior decline or rise in eGFR associates with an increased risk of mortality, independent of current eGFR.

Published
2016

31. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without hypertension: a meta-analysis

Author

Mahmoodi, Bk, Matsushita, K., Woodward, M., Blankestijn, Pj, Cirillo, Massimo, Ohkubo, T., Rossing, P., Sarnak, Mj, Stengel, B., Yamagishi, K., Yamashita, K., Zhang, L., Coresh, J., PE de Jong, Wright, BC Astor for the Chronic Kidney Disease Prognosis C. o. n. s. o. r. t. i. u. m. Investigators/Collaborators: J., Appel, L., Greene, T., Astor, Bc, Chalmers, J., Macmahon, S., Arima, H., Yatsuya, H., Toyoshima, H., Tamakoshi, K., Sang, Y., Atkins, R. C., Polkinghorne, Kr, Chadban, S., Shankar, A., Klein, R., Bek, Klein, Lee, Ke, Wang, H., Wang, F., Zuo, L., Levin, A., Djurdjev, O., Tonelli, M., Sacks, Fm, Curhan, Gc, Shlipak, M., Peralta, C., Katz, R., Fried, L., Iso, H., Kitamura, A., Ohira, T., Jafar, Th, Islam, M., Hatcher, J., Poulter, N., Chaturvedi, N., Landray, M. J., Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D., Brenner, H., Muller, H., Schottker, B., Fox, Cs, Hwang, S. J., Meigs, Jb, Perkins, Rm, Fluck, N., Clark, Le, Prescott, Gj, Marks, A., Black, C., Hallan, S., Aasarod, K., Oien, Cm, Radtke, M., Irie, F., Sairenchi, T., Smith, Dh, Weiss, Jw, Johnson, Es, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S., Chen, S. C., Lee, Bj, Wetzels, Jf, AD van Zuilen, Sarnak, M., Levey, As, Menon, V., Kramer, Hj, IH de Boer, Kronenberg, F., Kollerits, B., Roderick, E. R. i. t. z. P., Nitsch, D., Fletcher, A., Bulpitt, C., Ishani, A., Neaton, Jd, Froissart, M., Metzger, M., Haymann, J. P., Houillier, P., Flamant, M., Metoki, H., Nakayama, M., Kikuya, M., Imai, Y., Iseki, K., Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Hillege, H., Jassal, Sk, Barrett Connor, E., Bergstrom, J., HJ Lambers Heerspink, Brenner, Be, de Zeeuw, D., Warnock, Dg, Muntner, P., Judd, S., Mcclellan, W., Jee, Sh, Kimm, H., Jo, J., Mok, Y., Parving, H. H., Tangri, N., Naimark, D., Wen, C. P., Wen, S. F., Tsao, C. K., Tsai, M. K., Arnlov, J., Lannfelt, L., Larsson, A., Bilo, Hj, Joosten, H., Kleefstra, N., Groenier, Kh, Steering Committee: BC Astor, I. D. r. i. o. n., Hemmelgarn, Br, Data Coordinating Center: SH Ballew, M. W. o. o. d. w. a. r. d., Grams, M., Camarata, L., Hui, X., Seltzer, J., Winegrad, H., Mahmoodi, Bk, Matsushita, K, Woodward, M, Blankestijn, Pj, Cirillo, M, Ohkubo, T, Rossing, P, Sarnak, Mj, Stengel, B, Yamagishi, K, Yamashita, K, Zhang, L, Coresh, J, de Jong, Pe, Investigators/Collaborators: J Wright, BC Astor for the Chronic Kidney Disease Prognosis Consortium., Appel, L, Greene, T, Astor, Bc, Chalmers, J, Macmahon, S, Arima, H, Yatsuya, H, Toyoshima, H, Tamakoshi, K, Sang, Y, C Atkins, R, Polkinghorne, Kr, Chadban, S, Shankar, A, Klein, R, Klein, Bek, Lee, Ke, Wang, H, Wang, F, Zuo, L, Levin, A, Djurdjev, O, Tonelli, M, Sacks, Fm, Curhan, Gc, Shlipak, M, Peralta, C, Katz, R, Fried, L, Iso, H, Kitamura, A, Ohira, T, Jafar, Th, Islam, M, Hatcher, J, Poulter, N, Chaturvedi, N, J Landray, M, Emberson, Jr, Townend, Jn, Wheeler, Dc, Rothenbacher, D, Brenner, H, Muller, H, Schottker, B, Fox, C, Hwang, S-J, Meigs, Jb, Perkins, Rm, Fluck, N, Clark, Le, Prescott, Gj, Marks, A, Black, C, Hallan, S, Aasarod, K, Oien, Cm, Radtke, M, Irie, F, Sairenchi, T, Smith, Dh, Weiss, Jw, Johnson, E, Thorp, Ml, Collins, Aj, Vassalotti, Ja, Li, S, Chen, S-C, Lee, Bj, Wetzels, Jf, van Zuilen, Ad, Sarnak, M, Levey, A, Menon, V, Kramer, Hj, de Boer, Ih, Kronenberg, F, Kollerits, B, P Roderick, E Ritz., Nitsch, D, Fletcher, A, Bulpitt, C, Ishani, A, Neaton, Jd, Froissart, M, Metzger, M, Haymann, J-P, Houillier, P, Flamant, M, Metoki, H, Nakayama, M, Kikuya, M, Imai, Y, Iseki, K, Nelson, Rg, Knowler, Wc, Gansevoort, Rt, Hillege, H, Jassal, Sk, Barrett-Connor, E, Bergstrom, J, Lambers Heerspink, Hj, Brenner, Be, de Zeeuw, D, Warnock, Dg, Muntner, P, Judd, S, Mcclellan, W, Jee, Sh, Kimm, H, Jo, J, Mok, Y, Parving, H-H, Tangri, N, Naimark, D, Wen, C-P, Wen, S-F, Tsao, C-K, Tsai, M-K, Arnlov, J, Lannfelt, L, Larsson, A, Bilo, Hj, Joosten, H, Kleefstra, N, Groenier, Kh, Steering Committee: BC Astor, I Drion., Hemmelgarn, Br, Data Coordinating Center: SH Ballew, M Woodward., Grams, M, Camarata, L, Hui, X, Seltzer, J, and Winegrad., H

Subjects
Male, medicine.medical_specialty, hypertension, Blood Pressure, BLOOD-PRESSURE, GLOMERULAR-FILTRATION-RATE, Article, albuminuria, DIABETIC-NEPHROPATHY, End stage renal disease, CKD-PC Consortium, Risk Factors, Cause of Death, Internal medicine, REVERSE EPIDEMIOLOGY, eGFR, EQUATION, medicine, Humans, Intensive care medicine, Aged, Proportional Hazards Models, ALL-CAUSE MORTALITY, Renal disorder [IGMD 9], Aged, 80 and over, end-stage renal disease, business.industry, General Medicine, Middle Aged, medicine.disease, mortality, RISK POPULATION COHORTS, PREVALENCE, Chronic Disease, COLLABORATIVE METAANALYSIS, Kidney Failure, Chronic, Female, HIGHER ALBUMINURIA, business, Glomerular Filtration Rate, Kidney disease
Abstract

Item does not contain fulltext BACKGROUND: Hypertension is the most prevalent comorbidity in individuals with chronic kidney disease. However, whether the association of the kidney disease measures, estimated glomerular filtration rate (eGFR) and albuminuria, with mortality or end-stage renal disease (ESRD) differs by hypertensive status is unknown. METHODS: We did a meta-analysis of studies selected according to Chronic Kidney Disease Prognosis Consortium criteria. Data transfer and analyses were done between March, 2011, and June, 2012. We used Cox proportional hazards models to estimate the hazard ratios (HR) of mortality and ESRD associated with eGFR and albuminuria in individuals with and without hypertension. FINDINGS: We analysed data for 45 cohorts (25 general population, seven high-risk, and 13 chronic kidney disease) with 1,127,656 participants, 364,344 of whom had hypertension. Low eGFR and high albuminuria were associated with mortality irrespective of hypertensive status in the general population and high-risk cohorts. All-cause mortality risk was 1.1-1.2 times higher in individuals with hypertension than in those without hypertension at preserved eGFR. A steeper relative risk gradient in individuals without hypertension than in those with hypertension at eGFR range 45-75 mL/min per 1.73 m(2) led to much the same mortality risk at lower eGFR. With a reference eGFR of 95 mL/min per 1.73 m(2) in each group to explicitly assess interaction, adjusted HR for all-cause mortality at eGFR 45 mL/min per 1.73 m(2) was 1.77 (95% CI 1.57-1.99) in individuals without hypertension versus 1.24 (1.11-1.39) in those with hypertension (p for overall interaction=0.0003). Similarly, for albumin-creatinine ratio of 300 mg/g (vs 5 mg/g), HR was 2.30 (1.98-2.68) in individuals without hypertension versus 2.08 (1.84-2.35) in those with hypertension (p for overall interaction=0.019). We recorded much the same results for cardiovascular mortality. The associations of eGFR and albuminuria with ESRD, however, did not differ by hypertensive status. Results for chronic kidney disease cohorts were similar to those for general and high-risk population cohorts. INTERPRETATION: Chronic kidney disease should be regarded as at least an equally relevant risk factor for mortality and ESRD in individuals without hypertension as it is in those with hypertension. FUNDING: US National Kidney Foundation.

Published
2012

32. Improving the prognosis of patients with severely decreased glomerular filtration rate (CKD G4+): conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Author

Bertrand L. Kasiske, Manjula Kurella Tamura, Kathryn Griffith, Marie Evans, Mustafa Arici, Min Jun, David C. Wheeler, Brenda R. Hemmelgarn, Edgar V. Lerma, Hiddo J.L. Heerspink, Michael Cheung, Kamyar Kalantar-Zadeh, Matthew T. James, Wolfgang C. Winkelmayer, Elke Schäffner, Adeera Levin, Shuchi Anand, Bénédicte Stengel, Kitty J. Jager, Zofia Das-Gupta, Paul E. Stevens, Ali K. Abu-Alfa, Jamie P. Dwyer, Angela Yee-Moon Wang, Amy W. Williams, Nisha Bansal, Dorry L. Segev, Edmund J. Lamb, David M. Charytan, Carol A. Pollock, Danielle M. Nash, Danilo Fliser, Roberto Pecoits-Filho, Miguel A. Vazquez, Kai-Uwe Eckardt, Juan Carlos Julián Mauro, Kate Huffman, Mintu P. Turakhia, Rafael Burgos-Calderon, Andrew S. Levey, Lesley A. Inker, Csaba P. Kovesdy, Marc Froissart, David Harris, Charles A. Herzog, Geoffrey A. Block, Shoshana H. Ballew, Bruce M. Robinson, Donal O'Donoghue, Sankar D. Navaneethan, Josef Coresh, Vera Krane, Francesca Tentori, Navdeep Tangri, Yusuke Tsukamoto, Peter Stenvinkel, John S. Gill, Gregorio T. Obrador, Morgan E. Grams, Marcello Tonelli, Conference Participants, Abu-Alfa, A.K., Anand, S., Arici, M., Ballew, S.H., Block, G.A., Burgos-Calderon, R., Charytan, D.M., Das-Gupta, Z., Dwyer, J.P., Fliser, D., Froissart, M., Gill, J.S., Griffith, K.E., Harris, D.C., Huffman, K., Inker, L.A., Jager, K.J., Jun, M., Kalantar-Zadeh, K., Kasiske, B.L., Kovesdy, C.P., Krane, V., Lamb, E.J., Lerma, E.V., Levey, A.S., Levin, A., Julián Mauro, J.C., Nash, D.M., Navaneethan, S.D., O'Donoghue, D., Obrador, G.T., Pecoits-Filho, R., Robinson, B.M., Schäffner, E., Segev, D.L., Stengel, B., Stenvinkel, P., Tangri, N., Tentori, F., Tsukamoto, Y., Turakhia, M.P., Vazquez, M.A., Yee-Moon Wang, A., Williams, A.W., Groningen Kidney Center (GKC), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), APH - Aging & Later Life, APH - Quality of Care, APH - Global Health, and ACS - Pulmonary hypertension & thrombosis

Subjects
medicine.medical_specialty, Consensus, Clinical Decision-Making, 030232 urology & nephrology, Context (language use), HEMODIALYSIS-PATIENTS, Disease, 030204 cardiovascular system & hematology, urologic and male genital diseases, Kidney, Severity of Illness Index, OUTPUT CARDIAC-FAILURE, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, medicine, Humans, Renal Insufficiency, Chronic, Intensive care medicine, CARDIOVASCULAR EVENTS, Evidence-Based Medicine, business.industry, INCIDENT HEART-FAILURE, STAGE RENAL-DISEASE, INSUFFICIENCY COHORT, RANDOMIZED CONTROLLED-TRIAL, medicine.disease, Prognosis, female genital diseases and pregnancy complications, Clinical trial, chronic kidney disease, kidney failure, prediction, prognosis, progression, supportive care, medicine.anatomical_structure, Decreased glomerular filtration rate, Nephrology, Heart failure, business, REDUCED EJECTION FRACTION, CLINICAL-TRIALS, Kidney disease, Cohort study, DIALYSIS INITIATION, Glomerular Filtration Rate
Abstract

Patients with severely decreased glomerular filtration rate (GFR) (i.e., chronic kidney disease [CKD] G4+) are at increased risk for kidney failure, cardiovascular disease (CVD) events (including heart failure), and death. However, little is known about the variability of outcomes and optimal therapeutic strategies, including initiation of kidney replacement therapy (KRT). Kidney Disease: Improving Global Outcomes (KDIGO) organized a Controversies Conference with an international expert group in December 2016 to address this gap in knowledge. In collaboration with the CKD Prognosis Consortium (CKD-PC) a global meta-analysis of cohort studies (n = 264,515 individuals with CKD G4+) was conducted to better understand the timing of clinical outcomes in patients with CKD G4+ and risk factors for different outcomes. The results confirmed the prognostic value of traditional CVD risk factors in individuals with severely decreased GFR, although the risk estimates vary for kidney and CVD outcomes. A 2- and 4-year model of the probability and timing of kidney failure requiring KRT was also developed. The implications of these findings for patient management were discussed in the context of published evidence under 4 key themes: management of CKD G4+, diagnostic and therapeutic challenges of heart failure, shared decision-making, and optimization of clinical trials in CKD G4+ patients. Participants concluded that variable prognosis of patients with advanced CKD mandates individualized, risk-based management, factoring in competing risks and patient preferences.

Published
2017

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