Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Type 2 diabetes is a metabolic disease affecting 8 % of total world population. One of its main complications, diabetic nephropathy, can appear few years after the onset of the disease and affects one third of patients. Chronic kidney disease is a leading cause of end-stage renal disease. Accordingly, a precise estimation of the glomerular filtration rate is essential in type 2 diabetes patients for the early diagnosis of kidney failure. The objective of this study was to assess the glomerular filtration rate of type 2 diabetic subjects. We interested in cystatin C, a new marker of renal function. We evaluated the percentage of patients with chronic kidney disease. We also assessed glycaemic control and cardiovascular risk factors. Methods: We recorded anthropometric characteristics of 350 type 2 diabetic patients followed in the Endocrinology and Nutrition departments of the Cliniques Universitaires Saint-Luc, as well as the existence of chronic complications and assessed the global glycaemic control. We estimated the glomerular filtration rate by using different equations based on the determination of plasma creatinine and cystatin C - Cockroft-Gault, Modification of Diet in Renal Disease (MORD) and Chronic Kidney Disease Epidemiology Collaboration (CKD - Epi) equations. Metabolic control was satisfactory with an A1c of 7.6 ± 1.4 %. Mean estimated glomerular filtration rate using the MORD equation was 76 ± 25 ml/min/1.73 m2 and serum cystatin C was measured 1.00 ± 0.38 mg/L. The prevalences of stages 2 and 3 chronic kidney disease were 49 % and 22 % respectively. We observed a clear negative correlation between glomerular filtration rate estimated by MORD formula and by cystatin C value.ln conclusion, our study confirms the interest of cystatin C as a marker of renal function in patients with type 2 diabetes. lt is more suitable than plasma creatinine and allows equivalent or even better estimation of renal function than old equations, Cockroft and MORD. CKD-Epi equation based on serum creatinine and cystatin C appears to be even more powerful, probably due to minimal influence of extra renal factors on both markers. However, better standardization and reduced cost for cystatin C dosage are necessary before a larger use in medical practice. Le diabète de type 2 est une maladie métabolique affectant une personne sur douze dans le monde. Il peut se compliquer après quelques années d'évolution. Une de ses principales complications est la néphropathie diabétique, touchant un tiers des patients et représentant une des principales causes d'insuffisance rénale chronique. Il est donc important d'estimer le plus précisément possible le débit de filtration glomérulaire des patients diabétiques afin de diagnostiquer précocement une altération de la fonction rénale. Objectifs Notre objectif principal était d'estimer le niveau de filtration glomérulaire des patients diabétiques de type 2. Pour ce faire, nous nous sommes intéressés à la cystatine C, nouveau marqueur de la fonction rénale. Nous avons évalué le pourcentage de patients atteints d'insuffisance rénale chronique. Nous avons également apprécié l'équilibre glycémique et le contrôle des facteurs de risque cardiovasculaire. Nous avons analysé les caractéristiques anthropométriques de 350 diabétiques de type 2 régulièrement suivis dans le service d'Endocrinologie et Nutrition des Cliniques universitaires Saint-Luc, recherché l'existence de complications chroniques et évalué l'équilibre glycémique. Nous avons estimé leur débit de filtration glomérulaire en utilisant les différentes formules, basées sur le dosage de la créatinine plasmatique et de la cystatine C - Cockroft et Gault, Modification of Diet in Renal Disease (MORD) et Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi).Résultats : Le contrôle métabolique était satisfaisant avec un taux d'HbA1c de 7.6 ± 1.4%. Le DFG était estimé à 76 ± 25 ml/min/ 1,73 m2 selon la formule MORD et le taux de cystatine C était mesuré à 1.00 ± 0.38 mg/L. Quarante-neuf pourcent des patients avaient une insuffisance rénale chronique de stade 2 et 22 % de stade 3. Nous avons retrouvé une bonne corrélation négative entre le DFG évalué par la formule MORD et par la cystatine. En conclusion, notre étude confirme l'intérêt de la cystatine C comme marqueur de la fonction rénale des patients diabétiques de type 2. Elle est plus adaptée que la créatinine plasmatique et son estimation de la fonction rénale est équivalente, sinon plus précise, à celle obtenue avec les anciennes formules, Cockroft et MORD. La formule CKD-Epi basée sur la créatinine et la cystatine C semblerait encore plus performante, l'influence des facteurs extra-rénaux sur les deux marqueurs y étant amoindrie. Cependant, pour la cystatine C, une meilleure standardisation et un moindre coût de son dosage sont nécessaires avant d'envisager une utilisation plus large en pratique clinique.

Kidney Function Tests --- Diabetes Mellitus, Type 2 --- Cystatin C

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book provides important and updated information on current research devoted to urinary biomarkers. Urinary biomarkers are characteristics that can be objectively measured and evaluated as indicators of normal biological or pathogenic processes of pharmacological responses to therapeutic intervention.

poststreptococcal acute glomerulonephritis --- infection-related glomerulonephritis --- nephritis-associated plasmin receptor --- plasmin --- acute kidney injury --- renal biomarkers --- furosemide stress test --- functional assessment --- urine --- diabetic kidney disease --- kidney function --- proteomics --- mass spectrometry --- statistical clinical model --- machine learning --- acute tubulointerstitial nephritis --- immunology --- biomarkers --- chronic kidney disease --- differential diagnosis --- label-free quantification --- renal transplant --- extracellular vesicles --- acute rejection --- chronic rejection --- chronic allograft dysfunction --- calcineurin-inhibitor nephrotoxicity --- Polyomavirus associated nephropathy --- immunosuppression --- upper urinary tract obstruction --- kidney injury --- neutrophil gelatinase-associated lipocalin --- monocyte chemotactic protein-1 --- kidney injury molecule 1 --- cystatin C --- vanin-1 --- microRNA --- uromodulin --- kidney graft function --- biomarker --- kidney transplantation --- long noncoding RNA --- rejection --- microvascular injury --- urinary aminopeptidases --- arterial hypertension --- renal function --- urinary biomarkers --- markers of AKI --- cystatin-C --- NGAL --- KIM-1 --- exercise --- end-stage kidney disease (ESKD) --- cardiovascular disease --- epidemiology --- CKD --- macrophage subpopulation --- renal fibrosis --- trichostatin A --- kidney graft --- T-cell-mediated rejection --- antibody-mediated rejection --- diagnostic test accuracy --- gentamicin --- sepsis --- miRNA --- nephrotoxicity --- vancomycin --- n/a

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Biosensor technologies have received a great amount of interest in recent decades, and this has especially been the case in recent years due to the health alert caused by the COVID-19 pandemic. The sensor platform market has grown in recent decades, and the COVID-19 outbreak has led to an increase in the demand for home diagnostics and point-of-care systems. With the evolution of biosensor technology towards portable platforms with a lower cost on-site analysis and a rapid selective and sensitive response, a larger market has opened up for this technology. The evolution of biosensor systems has the opportunity to change classic analysis towards real-time and in situ detection systems, with platforms such as point-of-care and wearables as well as implantable sensors to decentralize chemical and biological analysis, thus reducing industrial and medical costs. This book is dedicated to all the research related to biosensor technologies. Reviews, perspective articles, and research articles in different biosensing areas such as wearable sensors, point-of-care platforms, and pathogen detection for biomedical applications as well as environmental monitoring will introduce the reader to these relevant topics. This book is aimed at scientists and professionals working in the field of biosensors and also provides essential knowledge for students who want to enter the field.

Research & information: general --- Chemistry --- Analytical chemistry --- biosensors --- interdigitated electrodes --- impedance spectroscopy --- blood analysis --- whole-cell biosensor --- yeast surface display --- cholesterol oxidase --- glucose dehydrogenase --- electrochemical detection --- fiber optic sensor --- vital signs --- biosensor --- human body --- body temperature --- heart rate --- respiratory rate --- blood pressure --- torso scanning --- antennas --- processing algorithms --- electromagnetic imaging --- polymerase chain reaction --- COVID-19 --- electrochemical --- digital PCR --- point-of-care --- electroanalysis --- indigo dyes --- fast identification --- fingerprints --- differential pulse voltammetry --- cystatin C --- molecularly imprinted polymer --- electrochemical biosensor --- polypyrene --- multiwall carbon nanotubes --- acute kidney injury --- biomonitoring --- personalized healthcare --- sweat --- rolling circle amplification --- environmental monitoring --- heavy metals --- organic molecules --- microorganisms --- biorecognition --- diagnosis --- pathogens --- aptamers --- antibodies --- peptides --- enzymes --- DNAzymes --- peptide nucleic acids --- blood glucose monitoring --- diabetes --- non-invasive sensor --- PDMS --- vascular phantom --- glucometer --- RF sensor --- CD4+ T helper cells --- microfluidic chip --- microbeads --- wide-field optical system --- ImageJ --- graphene --- reduced graphene oxide --- electrochemistry --- electrochemical impedance spectroscopy --- DNA biosensor --- diazonium chemistry --- screen-printed electrodes --- DNA hybridization --- VOCs --- environmental --- packaging --- diagnostic --- pollution --- colorectal cancer --- KRAS --- lateral flow assay --- dipstick --- gold nanoparticles --- diagnostics --- multiplex --- point-of-care diagnostics --- REASSURED --- biosensors --- interdigitated electrodes --- impedance spectroscopy --- blood analysis --- whole-cell biosensor --- yeast surface display --- cholesterol oxidase --- glucose dehydrogenase --- electrochemical detection --- fiber optic sensor --- vital signs --- biosensor --- human body --- body temperature --- heart rate --- respiratory rate --- blood pressure --- torso scanning --- antennas --- processing algorithms --- electromagnetic imaging --- polymerase chain reaction --- COVID-19 --- electrochemical --- digital PCR --- point-of-care --- electroanalysis --- indigo dyes --- fast identification --- fingerprints --- differential pulse voltammetry --- cystatin C --- molecularly imprinted polymer --- electrochemical biosensor --- polypyrene --- multiwall carbon nanotubes --- acute kidney injury --- biomonitoring --- personalized healthcare --- sweat --- rolling circle amplification --- environmental monitoring --- heavy metals --- organic molecules --- microorganisms --- biorecognition --- diagnosis --- pathogens --- aptamers --- antibodies --- peptides --- enzymes --- DNAzymes --- peptide nucleic acids --- blood glucose monitoring --- diabetes --- non-invasive sensor --- PDMS --- vascular phantom --- glucometer --- RF sensor --- CD4+ T helper cells --- microfluidic chip --- microbeads --- wide-field optical system --- ImageJ --- graphene --- reduced graphene oxide --- electrochemistry --- electrochemical impedance spectroscopy --- DNA biosensor --- diazonium chemistry --- screen-printed electrodes --- DNA hybridization --- VOCs --- environmental --- packaging --- diagnostic --- pollution --- colorectal cancer --- KRAS --- lateral flow assay --- dipstick --- gold nanoparticles --- diagnostics --- multiplex --- point-of-care diagnostics --- REASSURED

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Biosensor technologies have received a great amount of interest in recent decades, and this has especially been the case in recent years due to the health alert caused by the COVID-19 pandemic. The sensor platform market has grown in recent decades, and the COVID-19 outbreak has led to an increase in the demand for home diagnostics and point-of-care systems. With the evolution of biosensor technology towards portable platforms with a lower cost on-site analysis and a rapid selective and sensitive response, a larger market has opened up for this technology. The evolution of biosensor systems has the opportunity to change classic analysis towards real-time and in situ detection systems, with platforms such as point-of-care and wearables as well as implantable sensors to decentralize chemical and biological analysis, thus reducing industrial and medical costs. This book is dedicated to all the research related to biosensor technologies. Reviews, perspective articles, and research articles in different biosensing areas such as wearable sensors, point-of-care platforms, and pathogen detection for biomedical applications as well as environmental monitoring will introduce the reader to these relevant topics. This book is aimed at scientists and professionals working in the field of biosensors and also provides essential knowledge for students who want to enter the field.

biosensors --- interdigitated electrodes --- impedance spectroscopy --- blood analysis --- whole-cell biosensor --- yeast surface display --- cholesterol oxidase --- glucose dehydrogenase --- electrochemical detection --- fiber optic sensor --- vital signs --- biosensor --- human body --- body temperature --- heart rate --- respiratory rate --- blood pressure --- torso scanning --- antennas --- processing algorithms --- electromagnetic imaging --- polymerase chain reaction --- COVID-19 --- electrochemical --- digital PCR --- point-of-care --- electroanalysis --- indigo dyes --- fast identification --- fingerprints --- differential pulse voltammetry --- cystatin C --- molecularly imprinted polymer --- electrochemical biosensor --- polypyrene --- multiwall carbon nanotubes --- acute kidney injury --- biomonitoring --- personalized healthcare --- sweat --- rolling circle amplification --- environmental monitoring --- heavy metals --- organic molecules --- microorganisms --- biorecognition --- diagnosis --- pathogens --- aptamers --- antibodies --- peptides --- enzymes --- DNAzymes --- peptide nucleic acids --- blood glucose monitoring --- diabetes --- non-invasive sensor --- PDMS --- vascular phantom --- glucometer --- RF sensor --- CD4+ T helper cells --- microfluidic chip --- microbeads --- wide-field optical system --- ImageJ --- graphene --- reduced graphene oxide --- electrochemistry --- electrochemical impedance spectroscopy --- DNA biosensor --- diazonium chemistry --- screen-printed electrodes --- DNA hybridization --- VOCs --- environmental --- packaging --- diagnostic --- pollution --- colorectal cancer --- KRAS --- lateral flow assay --- dipstick --- gold nanoparticles --- diagnostics --- multiplex --- point-of-care diagnostics --- REASSURED

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In recent years, artificial intelligence has increasingly been playing an essential role in diverse areas in medicine, assisting clinicians in patient management. In nephrology and transplantation, artificial intelligence can be utilized to enhance clinical care, such as through hemodialysis prescriptions and the follow-up of kidney transplant patients. Furthermore, there are rapidly expanding applications and validations of comprehensive, computerized medical records and related databases, including national registries, health insurance, and drug prescriptions. For this Special Issue, we made a call to action to stimulate researchers and clinicians to submit their invaluable works and present, here, a collection of articles covering original clinical research (single- or multi-center), database studies from registries, meta-analyses, and artificial intelligence research in nephrology including acute kidney injury, electrolytes and acid–base, chronic kidney disease, glomerular disease, dialysis, and transplantation that will provide additional knowledge and skills in the field of nephrology and transplantation toward improving patient outcomes.

tacrolimus --- C/D ratio --- tacrolimus metabolism --- everolimus --- conversion --- kidney transplantation --- gut microbiome --- renal transplant recipient --- diarrhea --- immunosuppressive medication --- gut microbiota --- 16S rRNA sequencing --- butyrate-producing bacteria --- Proteobacteria --- torquetenovirus --- immunosuppression --- transplantation --- immunosuppressed host --- outcome --- renal transplantation --- Goodpasture syndrome --- anti-GBM disease --- epidemiology --- hospitalization --- outcomes --- acute kidney injury --- risk prediction --- artificial intelligence --- patent ductus arteriosus --- conservative management --- blood pressure --- eradication --- interferon-free regimen --- hepatitis C infection --- kidney transplant --- allograft steatosis --- lipopeliosis --- transplant numbers --- live donors --- public awareness --- Google TrendsTM --- machine learning --- big data --- nephrology --- chronic kidney disease --- NLR --- PLR --- RPGN --- predictive value --- hemodialysis --- withdrawal --- cellular crescent --- global sclerosis --- procurement kidney biopsy --- glomerulosclerosis --- minimally-invasive donor nephrectomy --- robot-assisted surgery --- laparoscopic surgery --- organ donation --- living kidney donation --- MeltDose® --- LCPT --- renal function --- liver transplantation --- metabolism --- erythropoietin --- fibroblast growth factor 23 --- death --- weekend effect --- in-hospital mortality --- comorbidity --- dialysis --- elderly --- klotho --- α-Klotho --- FGF-23 --- kidney donor --- Nephrology --- CKD-MBD --- CKD-Mineral and Bone Disorder --- deceased donor --- Eurotransplant Senior Program --- risk stratification --- intensive care --- kidney transplant recipients --- long-term outcomes --- graft failure --- cardiovascular mortality --- lifestyle --- inflammation --- vascular calcification --- bone mineral density --- dual-energy X-ray absorptiometry --- living donation --- repeated kidney transplantation --- graft survival --- prolonged ischaemic time --- patient survival --- pre-emptive transplantation --- metabolomics --- urine --- acute rejection --- allograft --- cystatin C --- hyperfiltration --- kidney injury molecule (KIM)-1 --- tubular damage --- genetic polymorphisms --- (cardiac) surgery --- inflammatory cytokines --- clinical studies --- chronic kidney disease (CKD) --- no known kidney disease (NKD) --- ICD-10 billing codes --- phenotyping --- electronic health record (EHR) --- estimated glomerular filtration rate (eGFR) --- machine learning (ML) --- generalized linear model network (GLMnet) --- random forest (RF) --- artificial neural network (ANN), clinical natural language processing (clinical NLP) --- discharge summaries --- laboratory values --- area under the receiver operating characteristic (AUROC) --- area under the precision-recall curve (AUCPR) --- fibrosis --- extracellular matrix --- collagen type VI --- living-donor kidney transplantation --- ethnic disparity