Explore the vast range of titles available.

Proteinuria is a hallmark of kidney disease. Therefore, measurement of urine protein content plays a central role in any diagnostic work-up for kidney disease. In many cases, proteinuria analysis is restricted to the measurement of total protein content knowing that very high levels of proteinuria (nephrotic proteinuria) are characteristic of glomerular disease. Still, proteinuria can also be a manifestation of impaired tubular protein reabsorption or even be physiological. This review will discuss the physiology of renal protein handling and give guidance on a more sophisticated analysis of proteinuria differentiating albumin, low-molecular weight proteins and immunoglobulins. These non-invasive tests are available in most routine clinical laboratories and may guide the clinician in the diagnostic process before ordering far more expensive (molecular genetic testing) and/or invasive (kidney biopsy) diagnostics.

Many different cystatin C-based equations exist for estimating glomerular filtration rate. Major reasons for this are the previous lack of an international cystatin C calibrator and the nonequivalence of results from different cystatin C assays. Use of the recently introduced certified reference material, ERM-DA471/IFCC, and further work to achieve high agreement and equivalence of 7 commercially available cystatin C assays allowed a substantial decrease of the CV of the assays, as defined by their performance in an external quality assessment for clinical laboratory investigations. By use of 2 of these assays and a population of 4690 subjects, with large subpopulations of children and Asian and Caucasian adults, with their GFR determined by either renal or plasma inulin clearance or plasma iohexol clearance, we attempted to produce a virtually assay-independent simple cystatin C-based equation for estimation of GFR. We developed a simple cystatin C-based equation for estimation of GFR comprising only 2 variables, cystatin C concentration and age. No terms for race and sex are required for optimal diagnostic performance. The equation, [Formula: see text] is also biologically oriented, with 1 term for the theoretical renal clearance of small molecules and 1 constant for extrarenal clearance of cystatin C. A virtually assay-independent simple cystatin C-based and biologically oriented equation for estimation of GFR, without terms for sex and race, was produced.

BackgroundMost validations of paediatric glomerular filtration rate (GFR) estimating equations using standardized creatinine (CR) and cystatin C (CYS) assays have comprised relatively small cohorts, which makes accuracy across subgroups of GFR, age, body mass index (BMI) and gender uncertain. To overcome this, a large cohort of children referred for GFR determination has been established from several European medical centres.MethodsThree thousand four hundred eight measurements of GFR (mGFR) using plasma clearance of exogenous substances were performed in 2218 children aged 2–17 years. Validated equations included Schwartz-2009CR/2012CR/CYS/CR+CYS, FASCR/CYS/CR+CYS, LMRCR, Schwartz-LyonCR, BergCYS, CAPACYS, CKD-EPICYS, AndersenCR+CYS and arithmetic means of the best single-marker equations in explorative analysis. Five metrics were used to compare the performance of the GFR equations: bias, precision and three accuracy measures including the percentage of GFR estimates (eGFR) within ± 10% (P10) and ± 30% (P30) of mGFR.ResultsThree of the cystatin C equations, BergCYS, CAPACYS and CKD-EPICYS, exhibited low bias and generally satisfactory accuracy across all levels of mGFR; CKD-EPICYS had more stable performance across gender than the two other equations. Among creatinine equations, Schwartz-LyonCR had the best performance but was inaccurate at mGFR < 30 mL/min/1.73 m2 and in underweight patients. Arithmetic means of the best creatinine and cystatin C equations above improved bias compared to the existing composite creatinine+cystatin C equations.ConclusionsThe present study strongly suggests that cystatin C should be the primary biomarker of choice when estimating GFR in children with decreased GFR. Arithmetic means of well-performing single-marker equations improve accuracy further at most mGFR levels and have practical advantages compared to composite equations.

Background Dent disease is a rare X-linked recessive proximal tubulopathy caused by mutations in CLCN5 (Dent-1) or OCRL (Dent-2). As a rule, total protein excretion (TPE) is low in tubular proteinuria compared with glomerular disease. Several authors have reported nephrotic-range proteinuria (NP) and glomerulosclerosis in Dent disease. Therefore, we aimed to analyze protein excretion in patients with documented CLCN5 or OCRL mutations in a systematic literature review. Design PubMed and Embase were searched for cases with documented CLCN5 or OCRL mutations and (semi-)quantitative data on protein excretion. The most reliable data (i.e., TPE > protein–creatinine ratio > Albustix) was used for NP classification. Results Data were available on 148 patients from 47 reports: 126 had a CLCN5 and 22 an OCRL mutation. TPE was not significantly different between both forms ( p  = 0.11). Fifty-five of 126 (43.7 %) Dent-1 vs 13/22 (59.1 %) Dent-2 patients met the definition of NP ( p  = 0.25). Serum albumin was normal in all reported cases (24/148). Glomerulosclerosis was noted in 20/32 kidney biopsies and was strongly related to tubulointerstitial fibrosis, but not to kidney function or proteinuria. Conclusion More than half of the patients with both forms of Dent disease have NP, and the presence of low molecular weight proteinuria in a patient with NP in the absence of edema and hypoalbuminemia should prompt genetic testing. Even with normal renal function, glomerulosclerosis and tubulointerstitial fibrosis are present in Dent disease. The role of proteinuria in the course of the disease needs to be examined further in longitudinal studies.

Background In pediatric patients treated with levamisole to prevent relapses of idiopathic nephrotic syndrome (INS), a transient and non-progressive rise in creatinine levels has been observed. It has been suggested that levamisole affects tubular secretion of creatinine. However, other potential mechanisms — nephrotoxicity and interference with the analytical assay for creatinine — have never been thoroughly investigated. Methods In three steroid-sensitive nephrotic syndrome (SSNS) patients with elevated plasma creatinine levels, treated with levamisole 2.5 mg/kg every other day, serum cystatin C was determined. The glomerular filtration rate (GFR) was estimated using the full age spectrum for creatinine and the full age spectrum for cystatin C equations. Interference of levamisole with the enzymatic creatinine assay was tested using spare human plasma of different creatinine concentrations spiked with levamisole (4, 20, and 100 µM). Results Three patients who received levamisole with elevated plasma creatinine levels had normal serum cystatin C levels and corresponding estimated GFR. There was no assay interference. Conclusion Levamisole increases plasma creatinine levels, which is most probably due to impaired tubular secretion of creatinine since there was no assay interference and patients had normal eGFR based on serum cystatin C. However, interference of metabolites of levamisole could not be excluded. To monitor GFR, cystatin C in addition to creatinine should be used and be measured before and during levamisole use.

BackgroundCombining estimated glomerular filtration rate (eGFR) equations based on creatinine and cystatin C has been shown to improve the accuracy of GFR estimation. This study aims to optimize this strategy for height-independent GFR estimation in children.MethodsRetrospective study of 408 inulin clearance tests with simultaneous International Federation of Clinical Chemistry-calibrated measurements of creatinine, cystatin C, and urea in children (mean age 12.5 years, GFR 91.2 ml/min/1.73m2) comparing the arithmetic (meanarith) and geometric means (meangeom) of a height-independent creatinine-based (full age spectrum, based on age (FASage)) and a cystatin C-based equation (FAScys), with the complex height-dependent CKiD3 equation incorporating gender, height, cystatin C, creatinine, and urea.ResultsMeangeom had a P30 accuracy of 89.2% compared to meanarith 87.7% (p = 0.030) as well as lower bias and %precision error and performed almost as well as CKiD3 (P30 accuracy 90.9%). Modifying the weight of FASage and FAScys when calculating the means showed that an equal contribution was most accurate in most patients. In spina bifida patients, FAScys alone outperformed any combination. Malignancy or nephritis patients had slightly higher accuracy with weighted means favoring cystatin C or creatinine, respectively. Disagreement between FAScys and FASage was inversely correlated with the accuracy of meangeom. When disagreement exceeded 40%, application of weighted means based on diagnosis improved the performance of eGFR.ConclusionsIn the absence of height data, the optimal strategy for estimating GFR in children is by using the geometric mean of FASage and FAScys. When there is large disagreement between the two, weighted means based on diagnosis improve accuracy.

In clinical practice, the glomerular filtration rate (GFR), a measurement of kidney functioning, is normally calculated using equations, such as the European Kidney Function Consortium (EKFC) equation. Despite being the most general equation, EKFC, just like previously proposed approaches, can still struggle to achieve satisfactory performance, limiting its clinical applicability. As a possible solution, recently machine learning (ML) has been investigated to improve GFR prediction, nonetheless the literature still lacks a general and multi-center study. Using a dataset with 19,629 patients from 13 cohorts, we investigate if ML can improve GFR prediction in comparison to EKFC. More specifically, we compare diverse ML methods, which were allowed to use age, sex, serum creatinine, cystatin C, height, weight and BMI as features, in internal and external cohorts against EKFC. The results show that the most performing ML method, random forest (RF), and EKFC are very competitive where RF and EKFC achieved respectively P10 and P30 values of 0.45 (95% CI 0.44;0.46) and 0.89 (95% CI 0.88;0.90), whereas EKFC yielded 0.44 (95% CI 0.43; 0.44) and 0.89 (95% CI 0.88; 0.90), considering the entire cohort. Small differences were, however, observed in patients younger than 12 years where RF slightly outperformed EKFC.