Skin autofluorescence as a novel marker of vascular damage in children and adolescents with chronic kidney disease

BACKGROUND: Skin autofluorescence (sAF) was examined as a marker of the accumulation of advanced glycation end products (AGEs) in tissues of children with chronic kidney disease (CKD) in relation to renal function, dialysis modality and markers of endothelial inflammation and dysfunction. METHODS: A total of 76 children with CKD were enrolled in the study, of whom 20 children were on hemodialysis (HD), 20 were on peritoneal dialysis (PD) and 36 were treated conservatively. A control group of 26 healthy subjects was also included in the study. In all children, sAF intensity, carotid intima-media (cIMT) thickness and plasma concentrations of sE-selectin, matrix metalloproteinase 9 (MMP-9), tissue inhibitor of metalloproteinase 1 (TIMP-1), asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA) and plasminogen activator inhibitor type 1 (PAI-1) were measured. RESULTS: Compared to the controls, children with CKD had significantly elevated sAF levels. sAF in the children with CKD was positively correlated with sE-selectin, MMP-9, TIMP-1, ADMA, SDMA and PAI-1 levels. In the predialysis group (conservative treatment) sAF levels were positively correlated with sE-selectin and ADMA levels and negatively correlated with glomerular filtration rate. Multiple regression analysis showed a significant association of sAF with sE-selectin and MMP-9 in CKD children. CONCLUSIONS: The results reveal that AGEs were accumulated in the children with CKD. This accumulation was related to early vascular changes and a number of biochemical vascular risk markers. sAF measurement, as a noninvasive method, may be useful for identification of clinical risk factors of vascular disease in CKD children

Ca2+-Mg2+-dependent ATP-ase activity in hemodialyzed children. Effect of a hemodialysis session

In the course of chronic kidney disease (CKD) the intracellular erythrocyte calcium (Cai2+) level increases along with the progression of the disease. The decreased activity of Ca2+-Mg2+-dependent ATP-ase (PMCA) and its endogenous modulators calmodulin (CALM), calpain (CANP), and calpastatin (CAST) are all responsible for disturbed calcium metabolism. The aim of the study was to analyze the activity of PMCA, CALM, and the CANP-CAST system in the red blood cells (RBCs) of hemodialyzed (HD) children and to estimate the impact of a single HD session on the aforementioned disturbances. Eighteen patients on maintenance HD and 30 healthy subjects were included in the study. CALM, Cai2+ levels and basal PMCA (bPMCA), PMCA, CANP, and CAST activities were determined in RBCs before HD, after HD, and before the next HD session. Prior to the HD session, the level of Cai2+ and the CAST activity were significantly higher, whereas bPMCA, PMCA, and CANP activities and the CALM level were significantly lower than in controls. After the HD session, the Cai2+ concentration and the CAST activity significantly decreased compared with the basal values, whereas the other parameters significantly increased, although they did not reach the levels of healthy children. The values observed prior to both HD sessions were similar. Cai2+ homeostasis is severely disturbed in HD children, which may be caused by the reduction in the PMCA activity, CALM deficiency, and CANP-CAST system disturbances. A single HD session improved these disturbances but the effect is transient

Heart ventricular activation in VAT difference maps from children with chronic kidney disease

Children with chronic kidney disease (CKD) are affected by cardiovascular complications, including disturbances in the intraventricular conduction system. Body surface potential mapping (BSPM) is a non-invasive method of assessing the cardioelectrical field. Our aim was to investigate conduction disturbances in young CKD patients using ventricular activation time (VAT) maps. Our study comprised 22 CKD children (mean age: 13.1 ± 2.5 years) treated conservatively and 29 control patients. For each child 12-lead electrocardiogram (ECG) readings were taken, and blood pressure and serum concentrations of iPTH, Pi, t-Ca, creatinine, Fe+3, ferritin, and Hb, as well as eGFR were measured. All children underwent registration in the 87-lead BSPM system, and group-mean VAT maps and a difference map, which presents statistically significant differences between the groups, were created. The VAT map distribution in CKD patients revealed abnormalities specific to left anterior fascicle block. The difference map displays the areas of intergroup VAT changes, which are of discriminative value in detecting intraventricular conduction disturbances. Intraventricular conduction impairments in the left bundle branch may occur in children with CKD. BSPM enables conduction disturbances in CKD children to be detected earlier than using 12-lead ECG. The difference map derived from the group-mean isochrone maps precisely localizes the sites of disturbed conduction in the heart intraventricular conduction system

The Use of Artificial Intelligence Algorithms in the Diagnosis of Urinary Tract Infections—A Literature Review

Urinary tract infections (UTIs) are among the most common infections occurring across all age groups. UTIs are a well-known cause of acute morbidity and chronic medical conditions. The current diagnostic methods of UTIs remain sub-optimal. The development of better diagnostic tools for UTIs is essential for improving treatment and reducing morbidity. Artificial intelligence (AI) is defined as the science of computers where they have the ability to perform tasks commonly associated with intelligent beings. The objective of this study was to analyze current views regarding attempts to apply artificial intelligence techniques in everyday practice, as well as find promising methods to diagnose urinary tract infections in the most efficient ways. We included six research works comparing various AI models to predict UTI. The literature examined here confirms the relevance of AI models in UTI diagnosis, while it has not yet been established which model is preferable for infection prediction in adult patients. AI models achieve a high performance in retrospective studies, but further studies are required