Nephrologie & Therapeutique最新文献

Chronic kidney disease-associated pruritus (CKD-aP) is a frequent complication, with an estimated prevalence of 24-37% in patients treated with hemodialysis. Its pathophysiology is complex and includes four interrelated axes: accumulation of uremic toxins, peripheral neuropathy, an imbalance in the opioid receptors balance, and abnormal activation of immune cells. This symptom which is associated with impaired quality of life is underestimated by caregivers and underreported by patients. Management is not uniformly codified. It includes the use of skin emollients, optimization of dialysis parameters and management of chronic kidney disease complications, and specifically the use of difelikefalin. Patients treated with hemodialysis have an increased risk of calcifications that can affect the arteries and heart valves. These calcifications are associated with decreased survival and several scores based on radiological examinations have been proposed for screening. Although recommended, this screening is rarely performed in dialysis centers. Prevention and treatment against the development of cardiovascular calcifications are the control of risk factors associated with atherosclerosis, control of phosphatemia, and new therapeutic strategies such as sodium thiosulfate, rheopheresis, vitamin K, magnesium supplementation or SNF-472, a calcium chelator currently in clinical development.

Missing data may lead to bias and loss of information in epidemiological research. In this article, we propose an approach to analyze missing data on comorbidity variables in a register with consideration of the territorialized organization of the collection. To illustrate this approach, we used the national REIN registry as an application case.

Hyperoxaluria is defined by an increase of urinary oxalate, leading to kidney stones, nephrocalcinosis and/or chronic kidney disease. There are different diseases related to hyperoxaluria: (1) kidney stones, 50% of them being explained by intermittent hyperoxaluria, secondary to dietary mistakes such as low hydration, excess of oxalate consumption and/or low calcium consumption; (2) primary hyperoxaluria, a genetic orphan disease inducing a massive production of oxalate by the liver, leading to increased plasma oxalate increase and saturation, and further systemic oxalosis with oxalate deposition, nephrocalcinosis and ultimately kidney failure, the management of this disease being currently dramatically modified by the onset of new therapeutic tools such as RNA interference; and (3) enteric hyperoxaluria, resulting from increased intestinal oxalate absorption because of intestinal malabsorption (short bowel syndrome, bariatric surgery, exocrine pancreatic insufficiency, etc.). Diagnosis and therapeutic management of these diseases require a full understanding of oxalate physiology that we detail in this review.

The presence of missing data, a constant problem in medical research, has several consequences: systematic loss of power, associated or not with a reduction in the representativeness of the sample analyzed. There are three types of missing data: 1) missing completely at random (MCAR); 2) missing at random (MAR); 3) missing not at random (MNAR). Multiple imputation by chained equations allows for the correct handling of missing data under the MCAR and MAR assumptions. It allows to simulate for each missing data j, a number m of simulated values which seem plausible with regard to the other variables. A random effect is included in this simulation to express the uncertainty. Several data sets are thus created and analyzed individually, in an identical way. Then the estimators of each data set are combined to obtain a global estimator. Multiple imputation increases power, corrects for some biases and has the advantage of being applicable to many types of variables. Complete case analysis should no longer be the norm. The objective of this guide is to help the reader in conducting an analysis with multiple imputed data. We cover the following points: the different types of missing data, the different historical approaches to handling them, and then we detail the multiple imputation method using chained equations. We provide a code example for the mice package of R®.

Over the course of their disease, patients with chronic kidney disease (CKD) will be treated by several kidney replacement therapy (KRT) modalities. The transitions between KRT modalities can be experienced as traumatic by patients, and are associated with an increased morbidity and mortality, notably when they are not anticipated. Planning these transition phases could reduce the psychological trauma induced by the transfer, as well as reduce the risk of morbidity and mortality. However, the lack of a clear definition of a transfer, and the lack of criteria enabling the identification of patients at risk of transfer, prevents the anticipation of these transition phases at high risk for patients. We here discuss the various possible causes and risk factors of transfer from peritoneal dialysis (PD) to hemodialysis as well as transfer from hemodialysis to PD. The dialysis Commission of the Société francophone de néphrologie, dialyse et transplantation (SFNDT) makes some proposals to improve transition phases, such as the identification of patients at risk, specific PD programs for unplanned PD start, transition unit and hybrid therapy.

Healthcare professionals and patient associations want to identify any disparities within the different regions, particularly in access to the waiting list for a kidney transplant and to home dialysis. An application containing the results of two REIN studies on these two issues was created to meet this need. It is now available for consultation on the professional portal of the Biomedicine Agency.

Introduction: In a context of tension on the number of available kidney transplants compared to the number needed, the practices of refusal of transplants in the Rennes transplantation center were evaluated.

Materials and methods: The donors completely refused by our team (no kidney accepted for any Rennes recipient) between January 1st 2012 and December 31st 2015 were identified from the national CRISTAL registry. The outcome of these refused transplants (possible transplantation in another center), the data of the recipients (from Rennes and other centers) and the data of the donors (refused and then finally accepted) were extracted. The outcome of recipients (from Rennes and other centers) was compared: graft survival (censored on death) and patient survival (not censored on cessation of function). The Kidney Donor Profile Index (KDPI) score was calculated and its usefulness studied.

Results: Among the 203 rejected donors, 172 (85 %) were accepted for transplantation in another center; 89% of these grafts were functional at one year. In univariate analysis, Rennes recipients transplanted after a refusal had a better graft survival (censored on death) than recipients transplanted in another center with the refused graft (p < 0.001). The main limitation of this analysis is the non-comparability of the groups. The KDPI score was significantly associated with graft survival (censored on death). Of the 151 Rennes patients who had a refusal, 3% were still on the waiting list at the end of the observation period, the others spent a median additional time on dialysis of 220 days (Q1-Q3 81-483).

Conclusion: Rennes recipients transplanted after a first refusal seem to have a better graft survival (censored on death) than recipients from other centers transplanted with refused grafts. This is to be weighed against the additional time on dialysis and even the risk of non-transplantation.