A
Annika Hoyer
Researcher at Ludwig Maximilian University of Munich
Publications - 90
Citations - 1194
Annika Hoyer is an academic researcher from Ludwig Maximilian University of Munich. The author has contributed to research in topics: Population & Type 2 diabetes. The author has an hindex of 14, co-authored 76 publications receiving 841 citations. Previous affiliations of Annika Hoyer include University of Düsseldorf & Martin Luther University of Halle-Wittenberg.
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Journal ArticleDOI
The Prevalence and Incidence of Diabetes in Germany.
TL;DR: The database of the German Institute of Medical Documentation and Information makes it possible for the first time to compute statistics on diabetes for all insurees of the statutory health insurance scheme in Germany, estimating that 5.8 million persons with type 2 diabetes are living in Germany today.
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Performance of Antinuclear Antibodies for Classifying Systemic Lupus Erythematosus: A Systematic Literature Review and Meta-Regression of Diagnostic Data
Nicolai Leuchten,Annika Hoyer,Ralph Brinks,Monika Schoels,Matthias Schneider,Josef S Smolen,Sindhu R. Johnson,David I. Daikh,Thomas Dörner,Martin Aringer,George Bertsias +10 more
TL;DR: To review the published literature on the performance of indirect immunofluorescence (IIF)–HEp‐2 antinuclear antibody (ANA) testing for classification of systemic lupus erythematosus (SLE), a large number of cases of SLE are reported.
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Projected number of people with diagnosed Type 2 diabetes in Germany in 2040
Thaddäus Tönnies,S Röckl,Annika Hoyer,Christin Heidemann,Jens Baumert,Yong Du,Christa Scheidt-Nave,Ralph Brinks +7 more
TL;DR: To project the number of people with Type 2 diabetes in Germany between 2015 and 2040, a database of more than 1.3 million people diagnosed with the disease over a 25-year period is used.
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Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas.
TL;DR: A new statistical model is proposed for the meta‐analysis for diagnostic accuracy studies that uses beta‐binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution.
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Healthcare costs of Type 2 diabetes in Germany.
TL;DR: To describe for the first time the direct costs of Type 2 diabetes treatment by analysing nationwide routine data from statutory health insurance in Germany.