Progression of endothelial dysfunction, atherosclerosis, and arterial stiffness in stable kidney transplant patients: a pilot study.

BACKGROUND: Kidney transplant patients suffer from vascular abnormalities and high cardiovascular event rates, despite initial improvements post-transplantation. The nature of the progression of vascular abnormalities in the longer term is unknown. This pilot study investigated changes in vascular abnormalities over time in stable kidney transplant patients long after transplantation. METHODS: Brachial artery flow-mediated dilation (FMD), nitroglycerin-mediated dilation, carotid-femoral pulse wave velocity (cf-PWV), ankle-brachial pressure index, and common carotid artery intima-media thickness (CCA-IMT) were assessed in 18 kidney transplant patients and 17 controls at baseline and 3-6 months after. RESULTS: There was no difference in age (51 ± 13 vs. 46 ± 11; P = 0.19), body mass index (26 ± 5 vs. 25 ± 3; P = 0.49), serum cholesterol (4.54 ± 0.96 vs. 5.14 ± 1.13; P = 0.10), systolic blood pressure (BP) (132 ± 12 vs. 126 ± 12; P = 0.13), diastolic BP (82 ± 9 vs. 77 ± 8; P = 0.10), or diabetes status (3 vs. 0; P = 0.08) between transplant patients and controls. No difference existed in vascular markers between patients and controls at baseline. In transplant patients, FMD decreased (- 1.52 ± 2.74; P = 0.03), cf-PWV increased (0.62 ± 1.06; P = 0.03), and CCA-IMT increased (0.35 ± 0.53; P = 0.02). No changes were observed in controls. CONCLUSION: Markers of vascular structure and function worsen in the post-transplant period on long-term follow-up, which may explain the continued high cardiovascular event rates in this population

Reference values for serum creatinine in children younger than 1 year of age

Reliable reference values of enzymatically assayed serum creatinine categorized in small age intervals are lacking in young children. The aim of this study was to determine reference values for serum creatinine during the first year of life and study the influence of gender, weight and height on these values. Serum creatinine determinations between 2003 and 2008 were retrieved from the hospital database. Strict exclusion criteria ensured the selection of patients without kidney damage. Correlation analysis was performed to evaluate the relation between height, weight and serum creatinine; the Mann–Whitney test was used to evaluate the relation between gender and serum creatinine. A broken stick model was designed to predict normal serum creatinine values. Mean serum creatinine values were found to decrease rapidly from 55 μmol/L on day 1 to 22 μmol/L in the second month of life; they then stabilized at 20 μmol/L until the seventh month, followed by a slight increase. No significant relation was found between serum creatinine and gender, weight and height. We present here reference values of serum creatinine in infants not at risk of decreased renal function. The absence of a relationship with gender, weight and height confirms that height-based equations to estimate glomerular filtration rate are less useful in patients of this age group

PKD1 and PKD2 mutations in Slovenian families with autosomal dominant polycystic kidney disease

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is a genetically heterogeneous disorder caused by mutations in at least two different loci. Prior to performing mutation screening, if DNA samples of sufficient number of family members are available, it is worthwhile to assign the gene involved in disease progression by the genetic linkage analysis. METHODS: We collected samples from 36 Slovene ADPKD families and performed linkage analysis in 16 of them. Linkage was assessed by the use of microsatellite polymorphic markers, four in the case of PKD1 (KG8, AC2.5, CW3 and CW2) and five for PKD2 (D4S1534, D4S2929, D4S1542, D4S1563 and D4S423). Partial PKD1 mutation screening was undertaken by analysing exons 23 and 31–46 and PKD2 . RESULTS: Lod scores indicated linkage to PKD1 in six families and to PKD2 in two families. One family was linked to none and in seven families linkage to both genes was possible. Partial PKD1 mutation screening was performed in 33 patients (including 20 patients from the families where linkage analysis could not be performed). We analysed PKD2 in 2 patients where lod scores indicated linkage to PKD2 and in 7 families where linkage to both genes was possible. We detected six mutations and eight polymorphisms in PKD1 and one mutation and three polymorphisms in PKD2. CONCLUSION: In our study group of ADPKD patients we detected seven mutations: three frameshift, one missense, two nonsense and one putative splicing mutation. Three have been described previously and 4 are novel. Three newly described framesfift mutations in PKD1 seem to be associated with more severe clinical course of ADPKD. Previously described nonsense mutation in PKD2 seems to be associated with cysts in liver and milder clinical course

Cystatin C: current position and future prospects.

Abstract Cystatin C is a low-molecular-weight protein which has been proposed as a marker of renal function that could replace creatinine. Indeed, the concentration of cystatin C is mainly determined by glomerular filtration and is particularly of interest in clinical settings where the relationship between creatinine production and muscle mass impairs the clinical performance of creatinine. Since the last decade, numerous studies have evaluated its potential use in measuring renal function in various populations. More recently, other potential developments for its clinical use have emerged. This review summarises current knowledge about the physiology of cystatin C and about its use as a renal marker, either alone or in equations developed to estimate the glomerular filtration rate. This paper also reviews recent data about the other applications of cystatin C, particularly in cardiology, oncology and clinical pharmacology. Clin Chem Lab Med 2008;46:1664-86

Automatic identification of variables in epidemiological datasets using logic regression

textabstractBackground: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies