Home Nephro News Results from the ERA-EDTA Registry indicate a high mortality due to COVID-19 in dialysis patients and kidney transplant recipients across Europe.

Results from the ERA-EDTA Registry indicate a high mortality due to COVID-19 in dialysis patients and kidney transplant recipients across Europe.

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Results from the ERA-EDTA Registry indicate a high mortality due to COVID-19 in dialysis patients and kidney transplant recipients across Europe.

 Data collection and participants

The European Renal Association – European Dialysis and Transplant Association (ERA-EDTA) Registry collects data annually on patients starting KRT from national and regional renal registries in Europe. When the COVID-19 pandemic reached our continent, the registries providing individual level patient data on KRT patients were asked to provide additional data on all KRT patients with a diagnosis of COVID-19, either a clinical diagnosis or one proven by testing. Data items included patient and KRT treatment characteristics (month and year of birth, sex, primary renal disease (PRD), year of start of KRT, current treatment modality), supplemented with the date of COVID-19 diagnosis, and the date of death. Data from seven renal registries with at least 25 patients on dialysis or 25 patients living with a functioning kidney transplant with a COVID-19 diagnosis were included in this study (Austria, French-speaking, Belgium, France, Romania, Spain, Switzerland, and the Netherlands). The year of KRT start was not available for Spain; instead the year of start of the current treatment modality was provided. PRD was categorized in four groups: glomerulonephritis, diabetes mellitus, hypertension / renal vascular disease (RVD) and other PRDs. Patients with missing year of death (N=2) and treatment modality (N=8) were deleted from the analysis. Missing PRD (N=5) was included in the PRD category ‘other’. Sex and date of detection were complete for all patients. All national and regional renal registries contributing data for this study followed national legislation and European and national regulations for data protection.

 Study outcomes and statistical analysis

The endpoint studied was all-cause mortality within 28 days of diagnosis of COVID-19. Continuous variables were given as mean (standard deviation) or median (interquartile range [IQR]), and were compared between groups using the (paired) t-test or the Wilcoxon rank sums test. Categorical variables were presented as frequencies and percentages and were compared using Fisher’s exact test. The percentage of dialysis and transplant patients diagnosed with COVID-19 was estimated by dividing the number of cases by the number of prevalent patients at December 31, 2017 multiplied by 100.

To compare the probability of death between patients with COVID-19 and those without COVID-19 among dialysis and transplant patients, we selected historic controls from the ERA-EDTA Registry database who were alive and on dialysis or living with a functioning transplant on 15 March 2017. COVID-19 patients were matched to 10 non-COVID patients based on their estimated propensity score. This propensity score was calculated using logistic regression including COVID-19 as dependent variable, and the following independent variables: modality (either dialysis or transplantation, 100% match required), age, sex, PRD (4 groups), time since start KRT (since last treatment modality change for Spain), and country.

Survival analyses were used to calculate the probability of death. For patients with COVID-19 the date of diagnosis was taken as the starting point, and all-cause mortality was the event studied. Follow-up time was censored after 28 days of follow-up or on May 1, 2020, whichever occurred first. For dialysis and transplant patients without COVID-19 the follow-up started on March 15, 2017 and ended at death or at 28 days after March 15, 2017. The Kaplan-Meier method was used to calculate unadjusted probabilities of death for dialysis patients and transplant patients with COVID-19 and their matched historic controls without COVID-19, and allows for censored observations. The log-rank test was used to compare the distribution of time to death between groups. The COVID-19 attributable mortality was defined as the probability of death in the COVID patient population, minus the probability of death in the non-COVID patient population (i.e. historic controls). Attributable mortality measures the proportion of the probability of death in the COVID population that can be attributed to COVID.

The comparison of mortality in dialysis and transplant patients with COVID-19 also made use of propensity score matching as a method to control for confounding. Patients from these groups were matched 1 to 1, and propensity scores were based on age, sex, PRD (4 groups), time since start KRT (since last treatment modality change for Spain) and country. Patients who could not be matched were deleted from the analyses. Again, the Kaplan-Meier method was used to compare the probabilities of death for patients with COVID-19 on dialysis and their matched controls living on a functioning transplant. We performed a sensitivity analysis of the main results to ascertain the accuracy of the propensity score using multivariable Cox regression (adjusting for age, sex, year of start RRT, primary renal disease, and country). Results from this analysis did not differ meaningfully from the main results.

In dialysis and transplant patients with COVID-19 crude and adjusted probabilities of death were studied for age categories (<65 years, 65-74 years and ≥75 years), for men and women, by PRD category, by treatment modality (dialysis versus transplantation) and by country. We used Cox regression analysis to investigate the association of COVID-19 with the probability of death. In COVID-19 patients, we applied Cox regression to adjust for age, sex, PRD, year of start KRT or year of transplant, treatment modality, and country, where appropriate.

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