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Institute
Background
This article summarizes the 2012 European Renal Association—European Dialysis and Transplant Association Registry Annual Report (available at www.era-edta-reg.org) with a specific focus on older patients (defined as ≥65 years).
Methods
Data provided by 45 national or regional renal registries in 30 countries in Europe and bordering the Mediterranean Sea were used. Individual patient level data were received from 31 renal registries, whereas 14 renal registries contributed data in an aggregated form. The incidence, prevalence and survival probabilities of patients with end-stage renal disease (ESRD) receiving renal replacement therapy (RRT) and renal transplantation rates for 2012 are presented.
Results
In 2012, the overall unadjusted incidence rate of patients with ESRD receiving RRT was 109.6 per million population (pmp) (n = 69 035), ranging from 219.9 pmp in Portugal to 24.2 pmp in Montenegro. The proportion of incident patients ≥75 years varied from 15 to 44% between countries. The overall unadjusted prevalence on 31 December 2012 was 716.7 pmp (n = 451 270), ranging from 1670.2 pmp in Portugal to 146.7 pmp in the Ukraine. The proportion of prevalent patients ≥75 years varied from 11 to 32% between countries. The overall renal transplantation rate in 2012 was 28.3 pmp (n = 15 673), with the highest rate seen in the Spanish region of Catalonia. The proportion of patients ≥65 years receiving a transplant ranged from 0 to 35%. Five-year adjusted survival for all RRT patients was 59.7% (95% confidence interval, CI: 59.3–60.0) which fell to 39.3% (95% CI: 38.7–39.9) in patients 65–74 years and 21.3% (95% CI: 20.8–21.9) in patients ≥75 years.
Motivation
The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.
Main types of variables included
The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.
Spatial location and grain
BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).
Time period and grain
BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.
Major taxa and level of measurement
BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
Software format
.csv and .SQL.
Cover contact graphs
(2012)
We study problems that arise in the context of covering certain geometric objects called seeds (e.g., points or disks) by a set of other geometric objects called cover (e.g., a set of disks or homothetic triangles). We insist that the interiors of the seeds and the cover elements are pairwise disjoint, respectively, but they can touch. We call the contact graph of a cover a cover contact graph (CCG). We are interested in three types of tasks, both in the general case and in the special case of seeds on a line: (a) deciding whether a given seed set has a connected CCG, (b) deciding whether a given graph has a realization as a CCG on a given seed set, and (c) bounding the sizes of certain classes of CCG’s. Concerning (a) we give efficient algorithms for the case that seeds are points and show that the problem becomes hard if seeds and covers are disks. Concerning (b) we show that this problem is hard even for point seeds and disk covers (given a fixed correspondence between graph vertices and seeds). Concerning (c) we obtain upper and lower bounds on the number of CCG’s for point seeds.