P6534Prognostic implication of serum cystatin C and creatinine-based glomerular filtration rate ratio in coronary disease patients receiving PCI: a surrogate of low muscle mass and a predictor of mortality

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
T.-M Rhee ◽  
K W Park ◽  
C.-H Kim ◽  
J Kang ◽  
J.-K Han ◽  
...  

Abstract Background Low muscle mass results in impaired exercise capacity and is related with poor prognosis in chronic diseases. Although the ratio of serum creatinine (Scr) to cystatin C (Scys) is known as a surrogate marker of body muscle mass, the value of this marker is unclear in the patients with coronary artery disease (CAD). Purpose We assessed the clinical significance of two markers representing body muscle mass, the ratio of Scr to Scys (Scr/Scys), and ratio of estimated glomerular filtration rate by Scys to Scr (eGFRcys/eGFRcr). Methods We analyzed patients enrolled in a single tertiary center prospective percutaneous coronary intervention (PCI) registry that had Scr and Scys levels simultaneously measured before PCI. Optimal cut-off values of Scr/Scys and eGFRcys/eGFRcr, and their prognostic impact on 3-year mortality after PCI were analyzed. Subgroup analysis according to various demographics and risk factors was performed. Results A total of 1,928 patients who underwent PCI for significant CAD were analyzed (age 65.2±9.9 years, 70.8% men). Both Scr/Scys and eGFRcys/eGFRcr showed strong correlation with estimated proportion of muscle mass. Cut-off values of Scr/Scys discriminating 3-year death were 1.0 for men and 0.8 for women, while those of eGFRcys/eGFRcr were 1.1 for men and 1.0 for women. Both Scr/Scys- and eGFRcys/eGFRcr-based low muscle mass groups showed significantly higher risk of death, after adjusting for 7 selected covariates including age. The additional discriminative power of low muscle mass group on the predictive model was greater in the group determined by eGFRcys/eGFRcr than Scr/Scys. Low eGFRcys/eGFRcr values showed additional prognostic impact especially in patients older than 65 years, non-obese, men, chronic kidney disease, and current smokers. Conclusions Low muscle mass was an independent prognostic indicator in the patients who underwent coronary stenting. eGFRcys/eGFRcr was identified as a useful surrogate of muscle mass, which may be used to detect vulnerable patients with low muscle mass at high risk for future events. Acknowledgement/Funding None

2016 ◽  
Vol 5 (34) ◽  
pp. 1869-1871
Author(s):  
Davendra Kumar ◽  
Ajay Kumar Mishra ◽  
Jalees Fatima ◽  
Mehboob Subhani Siddiqui ◽  
Moidur Rehman

2020 ◽  
pp. 44-48
Author(s):  
V. A. Aleksandrov ◽  
L. N. Shilova ◽  
A. V. Aleksandrov

The development of renal dysfunction in patients with rheumatoid arthritis (RA) is due to the presence and severity of autoimmune disorders, chronic systemic inflammation, a multiplicity of comorbid conditions, and pharmacotherapy features. The most important parameter that describes the general condition of the kidneys is glomerular filtration rate (GFR). This review presents the data on the possibilities of modern methods for determining estimated GFR (e-GFR) and the specificity of their use in various clinical situations that accompany the course of RA. For the initial assessment of GFR in patients with RA it is advisable to use the measurement of e-GFR based on serum creatinine concentration using the CKD-EPI equation (2009) (with or without indexing by body surface area). In cases where the e-GFR equations are not reliable enough or the results of this test are insufficient for clinical decision making, the serum cystatin C level should be measured and the combined GFR calculation based on creatinine and cystatin C should be used.


Renal Failure ◽  
2021 ◽  
Vol 43 (1) ◽  
pp. 1104-1114
Author(s):  
Yanan Liu ◽  
Peng Xia ◽  
Wei Cao ◽  
Zhengyin Liu ◽  
Jie Ma ◽  
...  

Author(s):  
Julie Mouron-Hryciuk ◽  
François Cachat ◽  
Paloma Parvex ◽  
Thomas Perneger ◽  
Hassib Chehade

AbstractGlomerular filtration rate (GFR) is difficult to measure, and estimating formulas are notorious for lacking precision. This study aims to assess if the inclusion of additional biomarkers improves the performance of eGFR formulas. A hundred and sixteen children with renal diseases were enrolled. Data for age, weight, height, inulin clearance (iGFR), serum creatinine, cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), parathyroid hormone (PTH), albumin, and brain natriuretic peptide (BNP) were collected. These variables were added to the revised and combined (serum creatinine and cystatin C) Schwartz formulas, and the quadratic and combined quadratic formulas. We calculated the adjusted r-square (r2) in relation to iGFR and tested the improvement in variance explained by means of the likelihood ratio test. The combined Schwartz and the combined quadratic formulas yielded best results with an r2 of 0.676 and 0.730, respectively. The addition of BNP and PTH to the combined Schwartz and quadratic formulas improved the variance slightly. NGAL and albumin failed to improve the prediction of GFR further. These study results also confirm that the addition of cystatin C improves the performance of estimating GFR formulas, in particular the Schwartz formula.Conclusion: The addition of serum NGAL, BNP, PTH, and albumin to the combined Schwartz and quadratic formulas for estimating GFR did not improve GFR prediction in our population. What is Known:• Estimating glomerular filtration rate (GFR) formulas include serum creatinine and/or cystatin C but lack precision when compared to measured GFR.• The serum concentrations of some biological parameters such as neutrophil gelatinase-associated lipocalin (NGAL), parathyroid hormone (PTH), albumin, and brain natriuretic peptide (BNP) vary with the level of renal function. What is New:• The addition of BNP and PTH to the combined quadratic formula improved its performance only slightly. NGAL and albumin failed to improve the prediction of GFR further.


2017 ◽  
Vol 50 (6) ◽  
pp. 301-308 ◽  
Author(s):  
Elizabeth LM Barr ◽  
Louise J Maple-Brown ◽  
Federica Barzi ◽  
Jaquelyne T Hughes ◽  
George Jerums ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document