Bone Biomarkers Help Grading Severity of Coronary Calcifications in Non Dialysis Chronic Kidney Disease Patients

BACKGROUND: Osteoprotegerin (OPG) and fibroblast growth factor-23 (FGF23) are recognized as strong risk factors of vascular calcifications in non dialysis chronic kidney disease (ND-CKD) patients. The aim of this study was to investigate the relationships between FGF23, OPG, and coronary artery calcifications (CAC) in this population and to attempt identification of the most powerful biomarker of CAC: FGF23? OPG? METHODOLOGY/PRINCIPAL FINDINGS: 195 ND-CKD patients (112 males/83 females, 70.8 [27.4-94.6] years) were enrolled in this cross-sectional study. All underwent chest multidetector computed tomography for CAC scoring. Vascular risk markers including FGF23 and OPG were measured. Logistic regression analyses were used to study the potential relationships between CAC and these markers. The fully adjusted-univariate analysis clearly showed high OPG (≥10.71 pmol/L) as the only variable significantly associated with moderate CAC ([100-400[) (OR = 2.73 [1.03;7.26]; p = 0.04). Such association failed to persist for CAC scoring higher than 400. Indeed, severe CAC was only associated with high phosphate fractional excretion (FEPO(4)) (≥38.71%) (OR = 5.47 [1.76;17.0]; p = 0.003) and high FGF23 (≥173.30 RU/mL) (OR = 5.40 [1.91;15.3]; p = 0.002). In addition, the risk to present severe CAC when FGF23 level was high was not significantly different when OPG was normal or high. Conversely, the risk to present moderate CAC when OPG level was high was not significantly different when FGF23 was normal or high. CONCLUSIONS: Our results strongly suggest that OPG is associated to moderate CAC while FGF23 rather represents a biomarker of severe CAC in ND-CKD patients

La tuberculose chez le patient dialysé (expérience au C.H.U. de Montpellier sur 5 ans (1997 à 2002))

MONTPELLIER-BU Médecine UPM (341722108) / SudocPARIS-BIUM (751062103) / SudocMONTPELLIER-BU Médecine (341722104) / SudocSudocFranceF

Impact du freinage de l'hyperparathyroïdie secondaire par le Cinacalcet® sur la réponse érythropoïétique chez les patients dialysés chroniques

MONTPELLIER-BU Médecine UPM (341722108) / SudocPARIS-BIUM (751062103) / SudocMONTPELLIER-BU Médecine (341722104) / SudocSudocFranceF

Hémodiafiltration en ligne : modalités pratiques, sécurité et efficacité de la méthode

International audienc

Digital Health Support: Current Status and Future Development for Enhancing Dialysis Patient Care and Empowering Patients

International audienceChronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments

Hemodiafiltration improves free light chain removal and normalizes κ/λ ratio in hemodialysis patients

International audienceSerum free light chain (FLC) levels are correlated with chronic kidney disease (CKD) stages and are highest in patients on hemodialysis (HD). Aim of this study was to assess the FLC removal efficiency of Elisio™-210H dialyzer using either high-flux HD or on line high efficiency hemodiafiltration (HDF) modalities in CKD-5D patients

Creatinine index as a surrogate of lean body mass derived from urea Kt/V, pre-dialysis serum levels and anthropometric characteristics of haemodialysis patients.

BACKGROUND AND OBJECTIVES: Protein-energy wasting is common in long-term haemodialysis (HD) patients with chronic kidney disease and is associated with increased morbidity and mortality. The creatinine index (CI) is a simple and useful nutritional parameter reflecting the dietary skeletal muscle protein intake and skeletal muscle mass of the patient. Because of the complexity of creatinine kinetic modeling (CKM) to derive CI, we developed a more simplified formula to estimate CI in HD patients. DESIGN, SETTING, PARTICIPANTS & MEASUREMENTS: A large database of 549 HD patients followed over more than 20 years including monthly CKM-derived CI values was used to develop a simple equation based on patient demographics, predialysis serum creatinine values and dialysis dose (spKt/V) using mixed regression models. RESULTS: The equation to estimate CI was developed based on age, gender, pre-dialysis serum creatinine concentrations and spKt/V urea. The equation-derived CI correlated strongly with the measured CI using CKM (correlation coefficient  = 0.79, p-value <0.001). The mean error of CI prediction using the equation was 13.47%. Preliminary examples of few typical HD patients have been used to illustrate the clinical relevance and potential usefulness of CI. CONCLUSIONS: The elementary equation used to derive CI using demographic parameters, pre-dialysis serum creatinine concentrations and dialysis dose is a simple and accurate surrogate measure for muscle mass estimation. However, the predictive value of the simplified CI assessment method on mortality deserves further evaluation in large cohorts of HD patients

Osteoprotegerin and sclerostin in chronic kidney disease prior to dialysis: potential partners in vascular calcifications

International audienc