Sven Thomas Niepmann

738 total citations · 1 hit paper
18 papers, 463 citations indexed

About

Sven Thomas Niepmann is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Epidemiology. According to data from OpenAlex, Sven Thomas Niepmann has authored 18 papers receiving a total of 463 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cardiology and Cardiovascular Medicine, 7 papers in Molecular Biology and 6 papers in Epidemiology. Recurrent topics in Sven Thomas Niepmann's work include Cardiac Valve Diseases and Treatments (12 papers), Infective Endocarditis Diagnosis and Management (5 papers) and Atherosclerosis and Cardiovascular Diseases (3 papers). Sven Thomas Niepmann is often cited by papers focused on Cardiac Valve Diseases and Treatments (12 papers), Infective Endocarditis Diagnosis and Management (5 papers) and Atherosclerosis and Cardiovascular Diseases (3 papers). Sven Thomas Niepmann collaborates with scholars based in Germany, Australia and United States. Sven Thomas Niepmann's co-authors include Georg Nickenig, Sebastian Zimmer, Andreas Zietzer, Felix Jansen, Franz Bauernfeind, Percy A. Knolle, Veit Hornung, Philip Roger Goody, Mohammed Rabiul Hosen and Matti Adam and has published in prestigious journals such as Circulation, The Journal of Immunology and PLoS ONE.

In The Last Decade

Sven Thomas Niepmann

17 papers receiving 458 citations

Hit Papers

Aortic Valve Stenosis 2020 2026 2022 2024 2020 50 100 150

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sven Thomas Niepmann Germany 9 228 182 113 100 91 18 463
Anke C. Fender Germany 14 225 1.0× 216 1.2× 64 0.6× 60 0.6× 44 0.5× 31 557
Sara Rattik Sweden 13 164 0.7× 159 0.9× 313 2.8× 77 0.8× 57 0.6× 25 560
Xiao Xiang Yan China 12 117 0.5× 129 0.7× 76 0.7× 73 0.7× 34 0.4× 16 463
А. В. Потехина Russia 10 143 0.6× 94 0.5× 108 1.0× 45 0.5× 51 0.6× 49 357
Americo Simonini United States 6 227 1.0× 146 0.8× 104 0.9× 49 0.5× 44 0.5× 6 472
Shunsuke Netsu Japan 11 222 1.0× 125 0.7× 70 0.6× 32 0.3× 63 0.7× 19 413
Aline Roth Switzerland 14 89 0.4× 171 0.9× 180 1.6× 64 0.6× 63 0.7× 30 483
Keeran Vickneson United Kingdom 6 167 0.7× 174 1.0× 65 0.6× 26 0.3× 81 0.9× 10 479
Gerrit M. Große Germany 12 102 0.4× 68 0.4× 68 0.6× 105 1.1× 71 0.8× 42 342
И. В. Кологривова Russia 8 203 0.9× 112 0.6× 92 0.8× 70 0.7× 16 0.2× 42 378

Countries citing papers authored by Sven Thomas Niepmann

Since Specialization
Citations

This map shows the geographic impact of Sven Thomas Niepmann's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sven Thomas Niepmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sven Thomas Niepmann more than expected).

Fields of papers citing papers by Sven Thomas Niepmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sven Thomas Niepmann. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sven Thomas Niepmann. The network helps show where Sven Thomas Niepmann may publish in the future.

Co-authorship network of co-authors of Sven Thomas Niepmann

This figure shows the co-authorship network connecting the top 25 collaborators of Sven Thomas Niepmann. A scholar is included among the top collaborators of Sven Thomas Niepmann based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sven Thomas Niepmann. Sven Thomas Niepmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Düsing, Philip, Patrick Giavalisco, Frederik Dethloff, et al.. (2025). The role of uremic toxin indoxyl sulfate in the pathophysiology of aortic valve stenosis. Cardiovascular Research. 121(11). 1734–1749. 1 indexed citations
2.
Schmitt, Johanna, Christoph Bourauel, Frank A. Schildberg, et al.. (2025). Aortic valve stenosis and osteoporosis: insights from a mouse model. BMC Cardiovascular Disorders. 25(1). 562–562. 1 indexed citations
3.
Al‐Kassou, Baravan, Dieter Lütjohann, Jasmin Shamekhi, et al.. (2024). Cholesterol Crystal Dissolution Rate of Serum Predicts Outcomes in Patients With Aortic Stenosis Undergoing Transcatheter Aortic Valve Replacement. Journal of the American Heart Association. 13(3). e031997–e031997. 1 indexed citations
4.
Niepmann, Sven Thomas, Philip Düsing, Thomas Beiert, et al.. (2024). Loss of ceramide synthase 5 inhibits the development of experimentally induced aortic valve stenosis. Acta Physiologica. 240(5). e14140–e14140. 2 indexed citations
5.
Niepmann, Sven Thomas, Philip Roger Goody, Andreas Zietzer, et al.. (2023). Toll-like receptor-3 contributes to the development of aortic valve stenosis. Basic Research in Cardiology. 118(1). 6–6. 8 indexed citations
6.
Quast, Christine, Frank Kober, K Becker, et al.. (2022). Multiparametric MRI identifies subtle adaptations for demarcation of disease transition in murine aortic valve stenosis. Basic Research in Cardiology. 117(1). 29–29. 6 indexed citations
8.
Weisheit, Christina, Sven Thomas Niepmann, Sebastian Zimmer, et al.. (2021). CX3CR1 is a prerequisite for the development of cardiac hypertrophy and left ventricular dysfunction in mice upon transverse aortic constriction. PLoS ONE. 16(1). e0243788–e0243788. 11 indexed citations
9.
Niepmann, Sven Thomas, et al.. (2021). Abstract 14271: TLR3 as a Potential Target to Prevent Aortic Valve Stenosis. Circulation. 144(Suppl_1). 1 indexed citations
10.
Niepmann, Sven Thomas, Andreas Zietzer, Nikos Werner, et al.. (2020). Murine sca1/flk1-positive cells are not endothelial progenitor cells, but B2 lymphocytes. Basic Research in Cardiology. 115(2). 18–18. 7 indexed citations
11.
Lüsebrink, Enzo, Philip Roger Goody, Catharina Lahrmann, et al.. (2020). AIM2 Stimulation Impairs Reendothelialization and Promotes the Development of Atherosclerosis in Mice. Frontiers in Cardiovascular Medicine. 7. 582482–582482. 23 indexed citations
12.
Niepmann, Sven Thomas, et al.. (2020). Dissolving cholesterol crystals reduces aortic valve stenosis development in mice. European Heart Journal. 41(Supplement_2). 1 indexed citations
13.
Zietzer, Andreas, Sven Thomas Niepmann, Philip Düsing, et al.. (2020). MicroRNA-mediated vascular intercellular communication is altered in chronic kidney disease. Cardiovascular Research. 118(1). 316–333. 24 indexed citations
14.
Goody, Philip Roger, Mohammed Rabiul Hosen, D Christmann, et al.. (2020). Aortic Valve Stenosis. Arteriosclerosis Thrombosis and Vascular Biology. 40(4). 885–900. 195 indexed citations breakdown →
15.
Zietzer, Andreas, Sven Thomas Niepmann, Felix Jansen, et al.. (2019). Sodium thiocyanate treatment attenuates atherosclerotic plaque formation and improves endothelial regeneration in mice. PLoS ONE. 14(4). e0214476–e0214476. 20 indexed citations
16.
Niepmann, Sven Thomas, Andreas Zietzer, Matti Adam, et al.. (2019). Graded murine wire-induced aortic valve stenosis model mimics human functional and morphological disease phenotype. Clinical Research in Cardiology. 108(8). 847–856. 23 indexed citations
17.
Quast, Christine, Sebastian Zimmer, Christoph Jacoby, et al.. (2019). P5993Comprehensive characterization of experimental aortic valve stenosis by multiparametric MRI. European Heart Journal. 40(Supplement_1). 1 indexed citations
18.
Bauernfeind, Franz, Sven Thomas Niepmann, Percy A. Knolle, & Veit Hornung. (2016). Aging-Associated TNF Production Primes Inflammasome Activation and NLRP3-Related Metabolic Disturbances. The Journal of Immunology. 197(7). 2900–2908. 103 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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