Background. Patients on kidney replacement therapy comprise a vulnerable population and may be at increased risk of death from coronavirus disease 2019 (COVID-19). Currently, only limited data are available on outcomes in this patient population. Methods. We set up the ERACODA (European Renal Association COVID-19 Database) database, which is specifically designed to prospectively collect detailed data on kidney transplant and dialysis patients with COVID-19. For this analysis, patients were included who presented between 1 February and 1 May 2020 and had complete information available on the primary outcome parameter, 28-day mortality. Results. Of the 1073 patients enrolled, 305 (28%) were kidney transplant and 768 (72%) dialysis patients with a mean age of 60 ± 13 and 67 ± 14 years, respectively. The 28-day probability of death was 21.3% [95% confidence interval (95% CI) 14.3–30.2%] in kidney transplant and 25.0% (95% CI 20.2–30.0%) in dialysis patients. Mortality was primarily associated with advanced age in kidney transplant patients, and with age and frailty in dialysis patients. After adjusting for sex, age and frailty, in-hospital mortality did not significantly differ between transplant and dialysis patients [hazard ratio (HR) 0.81, 95% CI 0.59–1.10, P = 0.18]. In the subset of dialysis patients who were a candidate for transplantation (n = 148), 8 patients died within 28 days, as compared with 7 deaths in 23 patients who underwent a kidney transplantation <1 year before presentation (HR adjusted for sex, age and frailty 0.20, 95% CI 0.07–0.56, P < 0.01). Conclusions. The 28-day case-fatality rate is high in patients on kidney replacement therapy with COVID-19 and is primarily driven by the risk factors age and frailty. Furthermore, in the first year after kidney transplantation, patients may be at increased risk of COVID-19-related mortality as compared with dialysis patients on the waiting list for transplantation. This information is important in guiding clinical decision-making, and for informing the public and healthcare authorities on the COVID-19-related mortality risk in kidney transplant and dialysis patients.

Residual kidney function (RKF) contributes significant solute clearance in hemodialysis patients. Kidney Diseases Outcomes Quality Initiative (KDOQI) guidelines suggest that hemodialysis dose can be safely reduced in those with residual urea clearance (KRU) of 2 ml/min/1.73 m(2) or more. However, serial measurement of RKF is cumbersome and requires regular interdialytic urine collections. Simpler methods for assessing RKF are needed. β-trace protein (βTP) and β2-microglobulin (β2M) have been proposed as alternative markers of RKF. We derived predictive equations to estimate glomerular filtration rate (GFR) and KRU based on serum βTP and β2M from 191 hemodialysis patients based on standard measurements of KRU and GFR (mean of urea and creatinine clearances) using interdialytic urine collections. These modeled equations were tested in a separate validation cohort of 40 patients. A prediction equation for GFR that includes both βTP and β2M provided a better estimate than either alone and contained the terms 1/βTP, 1/β2M, 1/serum creatinine, and a factor for gender. The equation for KRU contained the terms 1/βTP, 1/β2M, and a factor for ethnicity. Mean bias between predicted and measured GFR was 0.63 ml/min and 0.50 ml/min for KRU. There was substantial agreement between predicted and measured KRU at a cut-off level of 2 ml/min/1.73 m(2). Thus, equations involving βTP and β2M provide reasonable estimates of RKF and could potentially be used to identify those with KRU of 2 ml/min/1.73 m(2) or more to follow the KDOQI incremental hemodialysis algorithm.

To determine the proportion of children receiving antibiotics for common illnesses and to understand the antibiotic prescription ptern and factors influencing it, a cross sectional study was done among the private practitioners in Chennai, India 403 prescriptions by 40 physicians from selected health facilities were analyzed 79.9% of children with ARI (Acute respiratory infection) and ADD (Acute watery diarrhea) were prescribed antibiotics. Penicillins (43.9%) were the commonest antibiotic prescribed. Factors like postgraduate qualification, experience of physician, source and method of updating knowledge, inpatient practice setting and presence of fever influenced the antibiotic prescription.