Nuclear Magnetic Resonance-Based Glomerular Filtration Rate Estimation Is More Closely Associated with Serum Vancomycin Target Trough Achievement vs. Serum Creatinine-Based Equations
Journal of the American Society of Nephrology | October 28, 2024 | Volume: 35 | Issue: 10S | Pages: No page available
Correction: Stämmler et al. Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C. Diagnostics 2021, 11, 2291
Abstract Background An accurate and reliable measurement of glomerular filtration rate (GFR) is essential to monitor for rejection and disease progression post-kidney transplantation. Measured GFR (mGFR) is the current gold standard. However, it has scarce availability at many centers and is labor intensive. Newer estimated GFR (eGFR) methods containing cystatin-C and/or other biomarkers have not been clinically validated in a post-transplant cohort. In this study, we evaluated a new NMR-based GFR (GFRNMR) equation that contains serum creatinine, cystatin C, myoinositol, and valine in post-kidney transplant recipients in a clinical routine setting. Methods Venipuncture for serum collection was performed immediately prior to mGFR measurement with urinary iothalamate clearance in 67 post-kidney transplant recipients. Serum was stored at 4°C and measured by NMR no later than four days after collection. eGFR was assessed using the following equations: i) GFRNMR, ii) CKD-EPI2021Cr (creatinine) and iii) CKD-EPI2021Cr,Cys (creatinine and cystatin-C). Bias was calculated as “eGFR—mGFR” for all equations. The Bootstrap method was employed to assess pairwise significance levels between bias distributions interquartile ranges (IQR), and P-value correction was determined with the Benjamini & Hochberg method. Precision, which was defined as percentage of samples within ±30% and ±15% from the mGFR value (P30 and P15, respectively), was calculated for each equation. Pairwise comparisons were made using McNemar’s Chi-squared and Benjamini & Hochberg correction. Precision was defined as the proportion of eGFR values concordant with mGFR values by CKD clinical stage. Results P30 for GFRNMR was significantly higher than CKD-EPI2021 Cr,Cys (97% vs 84%, P < 0.01) and higher than CKD-EPI2021 Cr (88%, P = 0.08). Similarly, P15 for GFRNMR was 63%; higher than for CKD-EPI2021 Cr (54%, P = 0.35) and CKD-EPI2021 Cr,Cys (51%, P = 0.19). Bias IQR for GFRNMR was 9.5 mL/min/1.73 m2 (median bias 2.0 mL/min/1.73 m2); significantly smaller than for CKD-EPI2021 Cr (Bias IQR 15.55 mL/min/1.73 m2, P < 0.05; median bias 1.47 mL/min/1.73 m2), and smaller than CKD-EPI2021 Cr,Cys (Bias IQR 14.4 mL/min/1.73 m2, P = 0.09; median bias 2.3 mL/min/1.73 m2). A broad range of medications such as immune modulators, and comorbidities such as hypertension, thyroid dysfunction, and coronary artery disease, did not interfere with GFRNMR performance. Conclusion NMR-based eGFR was less biased, more precise, and more accurate compared to creatinine and cystatin-C CKD-EPI eGFR equations in a post-kidney transplant setting. These findings suggest GFRNMR may more closely resemble mGFR in post-transplant patients and warrants further study on its potential use to improve clinical management in this patient group.
Performance of Nuclear Magnetic Resonance-Based Estimated Glomerular Filtration Rate in a Real-World Setting
An accurate estimate of glomerular filtration rate (eGFR) is essential for proper clinical management, especially in patients with kidney dysfunction. This prospective observational study evaluated the real-world performance of the nuclear magnetic resonance (NMR)-based GFRNMR equation, which combines creatinine, cystatin C, valine, and myo-inositol with age and sex. We compared GFRNMR performance to that of the 2021 CKD-EPI creatinine and creatinine-cystatin C equations (CKD-EPI2021Cr and CKD-EPI2021CrCys), using 115 fresh routine samples of patients scheduled for urinary iothalamate clearance measurement (mGFR). Median bias to mGFR of the three eGFR equations was comparably low, ranging from 0.4 to 2.0 mL/min/1.73 m2. GFRNMR outperformed the 2021 CKD-EPI equations in terms of precision (interquartile range to mGFR of 10.5 vs. 17.9 mL/min/1.73 m2 for GFRNMR vs. CKD-EPI2021CrCys; p = 0.01) and accuracy (P15, P20, and P30 of 66.1% vs. 48.7% [p = 0.007], 80.0% vs. 60.0% [p < 0.001] and 95.7% vs. 86.1% [p = 0.006], respectively, for GFRNMR vs. CKD-EPI2021CrCys). Clinical parameters such as etiology, comorbidities, or medications did not significantly alter the performance of the three eGFR equations. Altogether, this study confirmed the utility of GFRNMR for accurate GFR estimation, and its potential value in routine clinical practice for improved medical care.
Impact of race-independent equations on estimating glomerular filtration rate for the assessment of kidney dysfunction in liver disease
No container title available | September 15, 2022 | Volume: No volume available | Issue: No issue available | Pages: No page available
Abstract Background: Altered hemodynamics in liver disease often results in overestimation of glomerular filtration rate (GFR) by creatinine-based GFR estimating (eGFR) equations. Recently, we have validated a novel eGFR equation based on serum myo-inositol, valine, and creatinine quantified by nuclear magnetic resonance spectroscopy in combination with cystatin C, age and sex (GFRNMR). We hypothesized that GFRNMRcould improve chronic kidney disease (CKD) classification in the setting of liver disease. Results: We conducted a retrospective multicenter study in 205 patients with chronic liver disease (CLD), comparing the performance of GFRNMRto that of validated CKD-EPI eGFR equations, including eGFRcr (based on creatinine) and eGFRcr-cys (based on both creatinine and cystatin C), using measured GFR as reference standard. GFRNMR outperformed all other equations with a low overall median bias (-1 vs. -6 to 4 ml/min/1.73 m2 for the other equations; p < 0.05) and the lowest difference in bias between reduced and preserved liver function (-3 vs. -16 to -8 ml/min/1.73 m2for other equations). Concordant classification by CKD stage was highest for GFRNMR (59% vs. 48% to 53%) and less biased in estimating CKD severity compared to the other equations. GFRNMR P30 accuracy (83%) was higher than that of eGFRcr (75%; p = 0.019) and comparable to that of eGFRcr-cys (86%; p = 0.578). Conclusions: Addition of myo-inositol and valine to creatinine and cystatin C in GFRNMR further improved GFR estimation in CLD patients and accurately stratified liver disease patients into CKD stages.
Analytical Validation of GFRNMR: A Blood-Based Multiple Biomarker Assay for Accurate Estimation of Glomerular Filtration Rate
Accurate and precise monitoring of kidney function is critical for a timely and reliable diagnosis of chronic kidney disease (CKD). The determination of kidney function usually involves the estimation of the glomerular filtration rate (eGFR). We recently reported the clinical performance of a new eGFR equation (GFRNMR) based on the nuclear magnetic resonance (NMR) measurement of serum myo-inositol, valine, and creatinine, in addition to the immunoturbidometric quantification of serum cystatin C, age and sex. We now describe the analytical performance evaluation of GFRNMR according to the Clinical and Laboratory Standards Institute guidelines. Within-laboratory coefficients of variation (CV%) of the GFRNMR equation did not exceed 4.3%, with a maximum CV% for repeatability of 3.7%. Between-site reproducibility (three sites) demonstrated a maximum CV% of 5.9%. GFRNMR stability was demonstrated for sera stored for up to 8 days at 2–10°C and for NMR samples stored for up to 10 days in the NMR device at 6 ± 2°C. Substance interference was limited to 4/40 (10.0%) of the investigated substances, resulting in an underestimated GFRNMR (for glucose and metformin) or a loss of results (for naproxen and ribavirin) for concentrations twice as high as usual clinical doses. The analytical performances of GFRNMR, combined with its previously reported clinical performance, support the potential integration of this NMR method into clinical practice.
Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C
Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived ‘metabolite constellation’ (GFRNMR). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFRNMR equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFRNMR had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (−1.0; 1.0) mL/min/1.73 m2 for GFRNMR vs. −6.0 (−7.0; −5.0) mL/min/1.73 m2 for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI2012) (p < 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFRNMR vs. 47.3% (43.2; 51.5) for CKD-EPI2012 (p < 0.010). Thus, GFRNMR holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.