Marije M. Vis

9.6k total citations · 3 hit papers
153 papers, 6.1k citations indexed

About

Marije M. Vis is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Marije M. Vis has authored 153 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 122 papers in Cardiology and Cardiovascular Medicine, 85 papers in Surgery and 42 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Marije M. Vis's work include Acute Myocardial Infarction Research (62 papers), Coronary Interventions and Diagnostics (60 papers) and Cardiac Valve Diseases and Treatments (47 papers). Marije M. Vis is often cited by papers focused on Acute Myocardial Infarction Research (62 papers), Coronary Interventions and Diagnostics (60 papers) and Cardiac Valve Diseases and Treatments (47 papers). Marije M. Vis collaborates with scholars based in Netherlands, United States and United Kingdom. Marije M. Vis's co-authors include Jan J. Piek, José P.S. Henriques, Robbert J. de Winter, Karel T. Koch, Jan Baan, Jan G.P. Tijssen, René J. van der Schaaf, Krischan D. Sjauw, Jan G.P. Tijssen and Joanna J. Wykrzykowska and has published in prestigious journals such as New England Journal of Medicine, The Lancet and Circulation.

In The Last Decade

Marije M. Vis

151 papers receiving 6.0k citations

Hit Papers

Use of clopidogrel with o... 2013 2026 2017 2021 2013 2016 2017 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marije M. Vis Netherlands 38 4.4k 3.4k 1.6k 1.3k 1.0k 153 6.1k
Christian Juhl Terkelsen Denmark 42 4.1k 0.9× 2.3k 0.7× 692 0.4× 1.9k 1.4× 1.8k 1.8× 213 6.4k
Simon Dixon United States 40 3.2k 0.7× 3.5k 1.0× 2.1k 1.3× 1.6k 1.2× 1.6k 1.6× 184 6.2k
Hyeon‐Cheol Gwon South Korea 38 3.2k 0.7× 3.5k 1.0× 1.0k 0.6× 2.3k 1.7× 981 0.9× 300 5.5k
Joo‐Yong Hahn South Korea 38 3.1k 0.7× 3.8k 1.1× 1.3k 0.8× 2.5k 1.8× 1.2k 1.1× 296 5.7k
Young Bin Song South Korea 36 2.6k 0.6× 2.7k 0.8× 796 0.5× 1.8k 1.4× 712 0.7× 253 4.3k
Olivier Varenne France 33 2.3k 0.5× 1.6k 0.5× 522 0.3× 773 0.6× 1.1k 1.1× 132 4.1k
David M. Shavelle United States 34 3.7k 0.8× 1.4k 0.4× 694 0.4× 1.2k 0.9× 448 0.4× 177 5.2k
Howard Cohen United States 32 2.1k 0.5× 2.2k 0.6× 685 0.4× 922 0.7× 417 0.4× 78 3.5k
Gregory S. Couper United States 41 4.7k 1.1× 3.7k 1.1× 1.1k 0.7× 323 0.2× 419 0.4× 171 6.2k
Anne Kaltoft Denmark 33 3.0k 0.7× 2.9k 0.8× 526 0.3× 2.4k 1.8× 573 0.5× 99 4.8k

Countries citing papers authored by Marije M. Vis

Since Specialization
Citations

This map shows the geographic impact of Marije M. Vis'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 Marije M. Vis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marije M. Vis more than expected).

Fields of papers citing papers by Marije M. Vis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marije M. Vis. 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 Marije M. Vis. The network helps show where Marije M. Vis may publish in the future.

Co-authorship network of co-authors of Marije M. Vis

This figure shows the co-authorship network connecting the top 25 collaborators of Marije M. Vis. A scholar is included among the top collaborators of Marije M. Vis 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 Marije M. Vis. Marije M. Vis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Moeskops, Pim, Josje D. Schoufour, Peter J.M. Weijs, et al.. (2024). Low muscle quality on a procedural computed tomography scan assessed with deep learning as a practical useful predictor of mortality in patients with severe aortic valve stenosis. Clinical Nutrition ESPEN. 63. 142–147. 4 indexed citations
2.
Ravelli, Anita C.J., Saba Amiri, Marije M. Vis, et al.. (2024). Performance of federated learning-based models in the Dutch TAVI population was comparable to central strategies and outperformed local strategies. Frontiers in Cardiovascular Medicine. 11. 1399138–1399138. 1 indexed citations
3.
Beijk, Marcel A.M., Robbert J. de Winter, Jan Baan, et al.. (2023). Higher Edmonton Frail Scale prior to transcatheter Aortic Valve Implantation is related to longer hospital stay and mortality. International Journal of Cardiology. 399. 131637–131637. 2 indexed citations
4.
Fuentes, Federico, Héctor M. García‐García, Ronak Delewi, et al.. (2023). First-in-Human Drug-Eluting Balloon Treatment of Vulnerable Lipid-Rich Plaques: Rationale and Design of the DEBuT-LRP Study. Journal of Clinical Medicine. 12(18). 5807–5807. 5 indexed citations
5.
Abu‐Hanna, Ameen, Bas A.J.M. de Mol, Saskia Houterman, et al.. (2020). External validation of existing prediction models of 30-day mortality after Transcatheter Aortic Valve Implantation (TAVI) in the Netherlands Heart Registration. International Journal of Cardiology. 317. 25–32. 11 indexed citations
6.
Mourik, Martijn S. van, Ramón Rodríguez‐Olivares, Alexander H. Maass, et al.. (2020). Late onset of new conduction disturbances requiring permanent pacemaker implantation following TAVI. Heart. 106(16). 1244–1251. 13 indexed citations
7.
Karami, Mina, Krischan D. Sjauw, Annemarie E. Engström, et al.. (2020). Pre-PCI versus immediate post-PCI Impella initiation in acute myocardial infarction complicated by cardiogenic shock. PLoS ONE. 15(7). e0235762–e0235762. 13 indexed citations
8.
Vendrik, Jeroen, Martijn S. van Mourik, Saskia Houterman, Marije M. Vis, & Jan Baan. (2019). Transkatheter aortaklepvervanging (TAVI). Nederlandsch tijdschrift voor geneeskunde/Nederlands tijdschrift voor geneeskunde/NTvG-databank. 163(44). 1 indexed citations
9.
Mourik, Martijn S. van, Lucas A. Ramos, Jan Baan, et al.. (2019). Value of machine learning in predicting TAVI outcomes. Netherlands Heart Journal. 27(9). 443–450. 31 indexed citations
10.
Mourik, Martijn S. van, Jeroen Vendrik, Mohammad Abdelghani, et al.. (2018). Guideline-defined futility or patient-reported outcomes to assess treatment success after TAVI: what to use? Results from a prospective cohort study with long-term follow-up. Open Heart. 5(2). e000879–e000879. 22 indexed citations
11.
Ouweneel, Dagmar M., Justin de Brabander, Mina Karami, et al.. (2018). Real-life use of left ventricular circulatory support with Impella in cardiogenic shock after acute myocardial infarction: 12 years AMC experience. European Heart Journal Acute Cardiovascular Care. 8(4). 338–349. 57 indexed citations
12.
Kesteren, Floortje van, Martijn S. van Mourik, Esther Wiegerinck, et al.. (2018). Trends in patient characteristics and clinical outcome over 8 years of transcatheter aortic valve implantation. Netherlands Heart Journal. 26(9). 445–453. 9 indexed citations
13.
Koch, Karel T., Marije M. Vis, José P.S. Henriques, et al.. (2017). TCT-695 Elixhauser comorbidity score is the best risk score in predicting survival after MitraClip implantation. Journal of the American College of Cardiology. 70(18). B258–B259. 1 indexed citations
14.
Kikkert, Wouter J., Peter Damman, Bimmer E. Claessen, et al.. (2015). Influence of chronic kidney disease on anticoagulation levels and bleeding after primary percutaneous coronary intervention in patients treated with unfractionated heparin. Journal of Thrombosis and Thrombolysis. 41(3). 441–451. 6 indexed citations
15.
Kikkert, Wouter J., Mariëlla E.C.J. Hassell, Ronak Delewi, et al.. (2015). Predictors and prognostic consequence of gastrointestinal bleeding in patients with ST-segment elevation myocardial infarction. International Journal of Cardiology. 184. 128–134. 16 indexed citations
16.
Kikkert, Wouter J., Loes P. Hoebers, Peter Damman, et al.. (2013). Recurrent Myocardial Infarction After Primary Percutaneous Coronary Intervention for ST-Segment Elevation Myocardial Infarction. The American Journal of Cardiology. 113(2). 229–235. 22 indexed citations
17.
Hoebers, Loes P., Marije M. Vis, Bimmer E. Claessen, et al.. (2012). The impact of Multivessel Disease with and Without a Co-Existing Chronic Total Occlusion on Short- and Long-Term Mortality in ST-Elevation Myocardial Infarction Patients with and without Cardiogenic Shock. European Journal of Heart Failure. 15(4). 425–432. 75 indexed citations
18.
Beijk, Marcel A.M., Margo Klomp, Nan van Geloven, et al.. (2011). Two‐year follow‐up of the genous™ endothelial progenitor cell capturing stent versus the taxus liberté stent in patients with De Novo coronary artery lesions with a high‐risk of restenosis. Catheterization and Cardiovascular Interventions. 78(2). 189–195. 33 indexed citations
19.
Damman, Peter, Marcel A.M. Beijk, Wichert J. Kuijt, et al.. (2010). Multiple Biomarkers at Admission Significantly Improve the Prediction of Mortality in Patients Undergoing Primary Percutaneous Coronary Intervention for Acute ST-Segment Elevation Myocardial Infarction. Journal of the American College of Cardiology. 57(1). 29–36. 73 indexed citations
20.
Engström, Annemarie E., Marije M. Vis, Berto J. Bouma, et al.. (2010). Right Ventricular Dysfunction is an Independent Predictor for Mortality in ST-Elevation Myocardial Infarction Patients Presenting with Cardiogenic Shock on Admission. European Journal of Heart Failure. 12(3). 276–282. 56 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026