Phylogenetic analysis of hepatitis C virus isolates from hemodialysis patients

Phylogenetic analysis of hepatitis C virus isolates from hemodialysis patients. A high prevalence of hepatitis C virus (HCV) infection has been reported in hemodialysis patients. Main risk factors for transmission are previous blood transfusions and possibly nosocomial infections within the dialytic environment. In the present study 224 hemodialysis patients from the same department were tested for the presence of anti-HCV antibodies and HCV-RNA. The presence of anti-HCV in hemodialysis patients was correlated with a history of more than 10 blood transfusions (P = 0.001) and with a duration of hemodialysis treatment for more than 10 years (P = 0.001). The issue of possible patient-to-patient infection was addressed by sequence analysis of all HCV-RNA positive hemodialysis patients (N = 14) together with a control panel of HCV isolates from 56 unrelated non-hemodialysis patients with hepatitis C from the same geographical area. Subsequent phylogenetic analysis of nucleotide sequences obtained from the 5′-noncoding region and the nonstructural NS-5 region of the HCV genome revealed that only two hemodialysis patients were infected by a highly related HCV isolate. The remaining HCV-RNA positive hemodialysis patients including those without previous blood transfusions were all infected by phylogenetically-distant HCV isolates, providing evidence against a nosocomial transmission route. The data of the present study show that molecular epidemiological techniques are important to investigate the issue of nosocomial infection. In our hemodialysis unit patient-to-patient infection appears uncommon and draws attention towards other possible (such as, blood products such as human serum albumin, immunoglobulins) or even yet unrecognized transmission routes

Associations between depressive symptoms and disease progression in older patients with chronic kidney disease: results of the EQUAL study

Background Depressive symptoms are associated with adverse clinical outcomes in patients with end-stage kidney disease; however, few small studies have examined this association in patients with earlier phases of chronic kidney disease (CKD). We studied associations between baseline depressive symptoms and clinical outcomes in older patients with advanced CKD and examined whether these associations differed depending on sex. Methods CKD patients (>= 65 years; estimated glomerular filtration rate <= 20 mL/min/1.73 m(2)) were included from a European multicentre prospective cohort between 2012 and 2019. Depressive symptoms were measured by the five-item Mental Health Inventory (cut-off <= 70; 0-100 scale). Cox proportional hazard analysis was used to study associations between depressive symptoms and time to dialysis initiation, all-cause mortality and these outcomes combined. A joint model was used to study the association between depressive symptoms and kidney function over time. Analyses were adjusted for potential baseline confounders. Results Overall kidney function decline in 1326 patients was -0.12 mL/min/1.73 m(2)/month. A total of 515 patients showed depressive symptoms. No significant association was found between depressive symptoms and kidney function over time (P = 0.08). Unlike women, men with depressive symptoms had an increased mortality rate compared with those without symptoms [adjusted hazard ratio 1.41 (95% confidence interval 1.03-1.93)]. Depressive symptoms were not significantly associated with a higher hazard of dialysis initiation, or with the combined outcome (i.e. dialysis initiation and all-cause mortality). Conclusions There was no significant association between depressive symptoms at baseline and decline in kidney function over time in older patients with advanced CKD. Depressive symptoms at baseline were associated with a higher mortality rate in men

Erratum : Sorafenib promotes graft-versus-leukemia activity in mice and humans through IL-15 production in FLT3-ITD-mutant leukemia cells

This corrects the article DOI: 10.1038/nm.4484

Probabilistic Tsunami Hazard Analysis: Multiple Sources and Global Applications

International audienceApplying probabilistic methods to infrequent but devastating natural events is intrinsicallychallenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluatedbecause of the different causes generating tsunamis (earthquakes, landslides, volcanic activity,meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic TsunamiHazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scaleswith the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhanceknowledge of the potential tsunamigenic threat by estimating the probability of exceeding specificlevels of tsunami intensity metrics (e.g., run-up or maximum inundation heights) within a certain period oftime (exposure time) at given locations (target sites); these estimates can be summarized in hazard mapsor hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanismsof tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generationmechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii)statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoricuncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of therapid development of PTHA methods during the last decade and the globally distributed applications,including the importance of considering multiple sources, their relative intensities, probabilities ofoccurrence, and uncertainties in an integrated and consistent probabilistic framework

Kidney Failure Prediction Models: A Comprehensive External Validation Study in Patients with Advanced CKD

Background: Various prediction models have been developed to predict the risk of kidney failure in patients with CKD. However, guideline-recommended models have yet to be compared head to head, their validation in patients with advanced CKD is lacking, and most do not account for competing risks.Methods: To externally validate 11 existing models of kidney failure, taking the competing risk of death into account, we included patients with advanced CKD from two large cohorts: the European Quality Study (EQUAL), an ongoing European prospective, multicenter cohort study of older patients with advanced CKD, and the Swedish Renal Registry (SRR), an ongoing registry of nephrology-referred patients with CKD in Sweden. The outcome of the models was kidney failure (defined as RRT-treated ESKD). We assessed model performance with discrimination and calibration.Results: The study included 1580 patients from EQUAL and 13,489 patients from SRR. The average c statistic over the 11 validated models was 0.74 in EQUAL and 0.80 in SRR, compared with 0.89 in previous validations. Most models with longer prediction horizons overestimated the risk of kidney failure considerably. The 5-year Kidney Failure Risk Equation (KFRE) overpredicted risk by 10%-18%. The four- and eight-variable 2-year KFRE and the 4-year Grams model showed excellent calibration and good discrimination in both cohorts.Conclusions: Some existing models can accurately predict kidney failure in patients with advanced CKD. KFRE performed well for a shorter time frame (2 years), despite not accounting for competing events. Models predicting over a longer time frame (5 years) overestimated risk because of the competing risk of death. The Grams model, which accounts for the latter, is suitable for longer-term predictions (4 years)