Dataset Information

Brief Report: Cystatin C-Based Estimation of Glomerular Filtration Rate and Association With Atherosclerosis Imaging Markers in People Living With HIV.

ABSTRACT:

Introduction

Reduced estimated glomerular filtration rate (eGFR) is associated with increased risk of cardiovascular disease among people living with HIV (PLWH). It is unclear whether eGFR equations incorporating cystatin C (CysC) measurements are more predictive of preclinical cardiovascular disease than those using only creatinine (Cr).

Objectives

The study aimed to determine which of the 3 Chronic Kidney Disease Epidemiology (CKD-EPI) eGFR equations is most associated with carotid intima media thickness (CIMT) and coronary artery calcium (CAC) score.

Methods

This cross-sectional analysis of pooled data from 3 large cohorts compared the associations between the 3 CKD-EPI eGFR equations (Cr, CysC, and Cr-CysC) with CIMT and CAC score using multivariable regression analysis. eGFR and CIMT were analyzed as continuous variables. CAC scores were analyzed as a binary variable (detectable calcification versus nondetectable) and as a log10 Agatston score in those with detectable CAC.

Results

Thousand four hundred eighty-seven participants were included, and of these 910 (562 HIV+ and 348 HIV-) had CIMT measurements and 366 (296 HIV+ and 70 HIV-) had CAC measurements available. In HIV- participants, GFR estimated by any CKD-EPI equation did not significantly correlate with CIMT or CAC scores. When PLWH were analyzed separately including HIV-specific factors, only GFR estimated using Cr-Cys C correlated with CIMT [?= -0.90, 95% CI: (-1.67 to -0.13) ?m; P = 0.023]. Similarly, eGFR correlated with Agatston scores only when using cystatin C-based eGFR [?= -8.63, 95% CI: (-16.49 to -0.77) HU; P = 0.034]. Associations between other eGFR formulas and CAC did not reach statistical significance.

Conclusions

In PLWH, preclinical atherosclerosis may be more closely correlated with eGFR using formulae that incorporate CysC measurements than Cr alone.

SUBMITTER: McClean M

PROVIDER: S-EPMC7879707 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Brief Report: Cystatin C-Based Estimation of Glomerular Filtration Rate and Association With Atherosclerosis Imaging Markers in People Living With HIV.

McClean Mitchell M Buzkova Petra P Budoff Matthew M Estrella Michelle M Freiberg Matthew M Hodis Howard N HN Palella Frank F Shikuma Cecilia C Post Wendy S WS Gupta Samir S

Journal of acquired immune deficiency syndromes (1999) 20201201 4

<h4>Introduction</h4>Reduced estimated glomerular filtration rate (eGFR) is associated with increased risk of cardiovascular disease among people living with HIV (PLWH). It is unclear whether eGFR equations incorporating cystatin C (CysC) measurements are more predictive of preclinical cardiovascular disease than those using only creatinine (Cr).<h4>Objectives</h4>The study aimed to determine which of the 3 Chronic Kidney Disease Epidemiology (CKD-EPI) eGFR equations is most associated with caro ...[more]

PMID: 33136746

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Project description:BackgroundEquations to estimate GFR have not been well validated in the elderly and may misclassify persons with chronic kidney disease (CKD). We measured GFR and compared the performance of the Modification of Diet in Renal Disease (MDRD), the Chronic Kidney Disease-Epidemiology Collaboration (CKD-Epi) and the Berlin Initiative Study (BIS) equations based on creatinine and/or cystatin C in octogenarians and nonagenarians.MethodsUsing cross-sectional analysis we assessed 95 very elderly persons (mean 85 years) living in the community. GFR was measured by iohexol (mGFR) and compared with estimates using six equations: MDRD, CKD-Epi_creatinine, CKD-Epi_cystatin, CKD-Epi_creatinine-cystatin, BIS_creatinine and BIS_creatinine-cystatin.ResultsMean mGFR was 55 (range,19-86) ml/min/1.73 m(2). Bias was smaller with the CKD-Epi_creatinine-cystatin and the CKD-Epi_creatinine equations (-4.0 and 1.7 ml/min/1.73 m(2)). Accuracy (percentage of estimates within 30% of mGFR) was greater with the CKD-Epi_creatinine-cystatin, BIS_creatinine-cystatin and BIS_creatinine equations (85%, 83% and 80%, respectively). Among the creatinine-based equations, the BIS_creatinine had the greatest accuracy at mGFR?< 60 ml/min/1.73 m(2) and the CKD-Epi_creatinine was superior at higher GFRs (79% and 90%, respectively). The CKD-Epi_creatinine-cystatin, BIS_creatinine-cystatin and CKD-Epi_cystatin equations yielded the greatest areas under the receiver operating characteristic curve at GFR threshold = 60 ml/min/1.73 m 2 (0.88, 0.88 and 0.87, respectively). In participants classified based on the BIS_creatinine, CKD-Epi_cystatin, or BIS_creatinine-cystatin equations, the CKD-Epi_creatinine-cystatin equation tended to improve CKD classification (net reclassification index: 12.7%, p = 0.18; 6.7%, p = 0.38; and 15.9%; p = 0.08, respectively).ConclusionsGFR-estimating equations CKD-Epi_creatinine-cystatin and BIS_creatinine-cystatin showed better accuracy than other equations using creatinine or cystatin C alone in very elderly persons. The CKD-Epi_creatinine-cystatin equation appears to be advantageous in CKD classification. If cystatin C is not available, both the BIS_cr equation and the CKD-Epi_cr equation could be used, although at mGFR?< 60 ml/min/1.73 m(2), the BIS_cr equation seems to be the best alternative.

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

Project description:BackgroundAccurate evaluation of glomerular filtration rates (GFRs) is of critical importance in clinical practice. A previous study showed that models based on artificial neural networks (ANNs) could achieve a better performance than traditional equations. However, large-sample cross-sectional surveys have not resolved questions about ANN performance.MethodsA total of 1,180 patients that had chronic kidney disease (CKD) were enrolled in the development data set, the internal validation data set and the external validation data set. Additional 222 patients that were admitted to two independent institutions were externally validated. Several ANNs were constructed and finally a Back Propagation network optimized by a genetic algorithm (GABP network) was chosen as a superior model, which included six input variables; i.e., serum creatinine, serum urea nitrogen, age, height, weight and gender, and estimated GFR as the one output variable. Performance was then compared with the Cockcroft-Gault equation, the MDRD equations and the CKD-EPI equation.ResultsIn the external validation data set, Bland-Altman analysis demonstrated that the precision of the six-variable GABP network was the highest among all of the estimation models; i.e., 46.7 ml/min/1.73 m(2) vs. a range from 71.3 to 101.7 ml/min/1.73 m(2), allowing improvement in accuracy (15% accuracy, 49.0%; 30% accuracy, 75.1%; 50% accuracy, 90.5% [P<0.001 for all]) and CKD stage classification (misclassification rate of CKD stage, 32.4% vs. a range from 47.3% to 53.3% [P<0.001 for all]). Furthermore, in the additional external validation data set, precision and accuracy were improved by the six-variable GABP network.ConclusionsA new ANN model (the six-variable GABP network) for CKD patients was developed that could provide a simple, more accurate and reliable means for the estimation of GFR and stage of CKD than traditional equations. Further validations are needed to assess the ability of the ANN model in diverse populations.

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

Dataset Information

Brief Report: Cystatin C-Based Estimation of Glomerular Filtration Rate and Association With Atherosclerosis Imaging Markers in People Living With HIV.

Introduction

Objectives

Methods

Results

Conclusions

Publications

Brief Report: Cystatin C-Based Estimation of Glomerular Filtration Rate and Association With Atherosclerosis Imaging Markers in People Living With HIV.

Similar Datasets

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