Screening for chronic kidney disease is recommended in people at high risk, but data on the independent and combined associations of estimated glomerular filtration rate (eGFR) and albuminuria with all-cause and cardiovascular mortality are limited. To clarify this, we performed a collaborative meta-analysis of 10 cohorts with 266,975 patients selected because of increased risk for chronic kidney disease, defined as a history of hypertension, diabetes, or cardiovascular disease. Risk for all-cause mortality was not associated with eGFR between 60–105 ml/min per 1.73 m², but increased at lower levels. Hazard ratios at eGFRs of 60, 45, and 15 ml/min per 1.73 m² were 1.03, 1.38 and 3.11, respectively, compared to an eGFR of 95, after adjustment for albuminuria and cardiovascular risk factors. Log albuminuria was linearly associated with log risk for all-cause mortality without thresholds. Adjusted hazard ratios at albumin-to-creatinine ratios of 10, 30 and 300 mg/g were 1.08, 1.38, and 2.16, respectively compared to a ratio of five. Albuminuria and eGFR were multiplicatively associated with all-cause mortality, without evidence for interaction. Similar associations were observed for cardiovascular mortality. Findings in cohorts with dipstick data were generally comparable to those in cohorts measuring albumin-to-creatinine ratios. Thus, lower eGFR and higher albuminuria are risk factors for all-cause and cardiovascular mortality in high-risk populations, independent of each other and of cardiovascular risk factors.

Both a low estimated glomerular filtration rate (eGFR) and albuminuria are known risk factors for end-stage renal disease (ESRD). To determine their joint contribution to ESRD and other kidney outcomes, we performed a meta-analysis of nine general population cohorts with 845,125 participants and an additional eight cohorts with 173,892 patients, the latter selected because of their high risk for chronic kidney disease (CKD). In the general population, the risk for ESRD was unrelated to eGFR at values between 75 and 105 ml/min per 1.73 m² but increased exponentially at lower levels. Hazard ratios for eGFRs averaging 60, 45, and 15 were 4, 29, and 454, respectively, compared with an eGFR of 95, after adjustment for albuminuria and cardiovascular risk factors. Log albuminuria was linearly associated with log ESRD risk without thresholds. Adjusted hazard ratios at albumin-to-creatinine ratios of 30, 300, and 1000 mg/g were 5, 13, and 28, respectively, compared with an albumin-to-creatinine ratio of 5. Albuminuria and eGFR were associated with ESRD, without evidence for multiplicative interaction. Similar associations were found for acute kidney injury and progressive CKD. In high-risk cohorts, the findings were generally comparable. Thus, lower eGFR and higher albuminuria are risk factors for ESRD, acute kidney injury and progressive CKD in both general and high-risk populations, independent of each other and of cardiovascular risk factors.

In order to investigate the applicability of routine 10s electrocardiogram (ECG) recordings for time-domain heart rate variability (HRV) calculation we explored to what extent these (ultra-)short recordings capture the “actual” HRV. The standard deviation of normal-to-normal intervals (SDNN) and the root mean square of successive differences (RMSSD) were measured in 3,387 adults. SDNN and RMSSD were assessed from (ultra)short recordings of 10s(3x), 30s, and 120s and compared to 240s–300s (gold standard) measurements. Pearson’s correlation coefficients (r), Bland-Altman 95% limits of agreement and Cohen’s d statistics were used as agreement analysis techniques. Agreement between the separate 10s recordings and the 240s-300s recording was already substantial (r = 0.758–0.764/Bias = 0.398–0.416/d = 0.855–0.894 for SDNN; r = 0.853–0.862/Bias = 0.079–0.096/d = 0.150–0.171 for RMSSD), and improved further when three 10s periods were averaged (r = 0.863/Bias = 0.406/d = 0.874 for SDNN; r = 0.941/Bias = 0.088/d = 0.167 for RMSSD). Agreement increased with recording length and reached near perfect agreement at 120s (r = 0.956/Bias = 0.064/d = 0.137 for SDNN; r = 0.986/Bias = 0.014/d = 0.027 for RMSSD). For all recording lengths and agreement measures, RMSSD outperformed SDNN. Our results confirm that it is unnecessary to use recordings longer than 120s to obtain accurate measures of RMSSD and SDNN in the time domain. Even a single 10s (standard ECG) recording yields a valid RMSSD measurement, although an average over multiple 10s ECGs is preferable. For SDNN we would recommend either 30s or multiple 10s ECGs. Future research projects using time-domain HRV parameters, e.g. genetic epidemiological studies, could calculate HRV from (ultra-)short ECGs enabling such projects to be performed at a large scale.

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.

Recently, the European Medicines Agency approved the use of the vasopressin V2 receptor antagonist tolvaptan to slow the progression of cyst development and renal insufficiency of autosomal dominant polycystic kidney disease (ADPKD) in adult patients with chronic kidney disease stages 1–3 at initiation of treatment with evidence of rapidly progressing disease. In this paper, on behalf of the ERA-EDTA Working Groups of Inherited Kidney Disorders and European Renal Best Practice, we aim to provide guidance for making the decision as to which ADPKD patients to treat with tolvaptan. The present position statement includes a series of recommendations resulting in a hierarchical decision algorithm that encompasses a sequence of risk-factor assessments in a descending order of reliability. By examining the best-validated markers first, we aim to identify ADPKD patients who have documented rapid disease progression or are likely to have rapid disease progression. We believe that this procedure offers the best opportunity to select patients who are most likely to benefit from tolvaptan, thus improving the benefit-to-risk ratio and cost-effectiveness of this treatment. It is important to emphasize that the decision to initiate treatment requires the consideration of many factors besides eligibility, such as contraindications, potential adverse events, as well as patient motivation and lifestyle factors, and requires shared decision-making with the patient.