Tony Stanton

3.3k total citations · 1 hit paper
88 papers, 2.3k citations indexed

About

Tony Stanton is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Tony Stanton has authored 88 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Cardiology and Cardiovascular Medicine, 27 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Surgery. Recurrent topics in Tony Stanton's work include Cardiac Imaging and Diagnostics (26 papers), Cardiovascular Function and Risk Factors (26 papers) and Blood Pressure and Hypertension Studies (12 papers). Tony Stanton is often cited by papers focused on Cardiac Imaging and Diagnostics (26 papers), Cardiovascular Function and Risk Factors (26 papers) and Blood Pressure and Hypertension Studies (12 papers). Tony Stanton collaborates with scholars based in Australia, United Kingdom and United States. Tony Stanton's co-authors include Thomas H. Marwick, Rodel Leano, Nicole M. Isbel, Brian Haluska, Carmel M. Hawley, Rathika Krishnasamy, James Hare, David W. Johnson, Katrina L. Campbell and Elaine M. Pascoe and has published in prestigious journals such as Circulation, Journal of the American College of Cardiology and PLoS ONE.

In The Last Decade

Tony Stanton

80 papers receiving 2.3k citations

Hit Papers

Prediction of All-Cause Mortality From Global Longitudina... 2009 2026 2014 2020 2009 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tony Stanton Australia 25 1.7k 811 296 295 209 88 2.3k
Alfredo Bardajı́ Spain 28 1.5k 0.9× 400 0.5× 246 0.8× 435 1.5× 194 0.9× 179 2.4k
Markus Noveanu Switzerland 23 2.0k 1.2× 692 0.9× 171 0.6× 501 1.7× 179 0.9× 41 2.6k
Hack‐Lyoung Kim South Korea 24 1.6k 0.9× 538 0.7× 164 0.6× 663 2.2× 165 0.8× 204 2.4k
Ervin R. Fox United States 31 1.5k 0.9× 297 0.4× 228 0.8× 266 0.9× 299 1.4× 104 2.5k
Marcello Chinali Italy 30 2.6k 1.5× 621 0.8× 174 0.6× 398 1.3× 197 0.9× 108 3.2k
Normand Racine Canada 23 1.9k 1.1× 629 0.8× 110 0.4× 596 2.0× 140 0.7× 86 2.5k
R.B. Devereux United States 17 2.9k 1.7× 552 0.7× 213 0.7× 411 1.4× 90 0.4× 33 3.3k
Hong Euy Lim South Korea 32 2.8k 1.6× 474 0.6× 90 0.3× 655 2.2× 145 0.7× 224 3.5k
Víctor A. López United States 18 987 0.6× 633 0.8× 69 0.2× 309 1.0× 86 0.4× 39 1.9k
Rosario Rossi Italy 26 1.7k 1.0× 559 0.7× 135 0.5× 703 2.4× 142 0.7× 111 2.9k

Countries citing papers authored by Tony Stanton

Since Specialization
Citations

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

Fields of papers citing papers by Tony Stanton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tony Stanton. 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 Tony Stanton. The network helps show where Tony Stanton may publish in the future.

Co-authorship network of co-authors of Tony Stanton

This figure shows the co-authorship network connecting the top 25 collaborators of Tony Stanton. A scholar is included among the top collaborators of Tony Stanton 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 Tony Stanton. Tony Stanton 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.
Stanton, Tony, Christian Hamilton‐Craig, S. Wahi, et al.. (2025). Exercise blood pressure relative to fitness and cardiovascular outcomes: the EXERTION study. European Heart Journal.
3.
Schultz, Martin G., Petr Otáhal, Philip Roberts‐Thomson, et al.. (2023). A Hypertensive Response To Exercise Relative To Fitness In Type 2 Diabetes Is Associated With Increased Risk Of Cardiovascular Events And Mortality: Results From The Exercise Stress Test Collaboration (EXERTION).. Medicine & Science in Sports & Exercise. 55(9S). 298–298. 1 indexed citations
4.
Schultz, Martin G., Petr Otáhal, Philip Roberts‐Thomson, et al.. (2022). Type-2 Diabetes and the Clinical Importance of Exaggerated Exercise Blood Pressure. Hypertension. 79(10). 2346–2354. 4 indexed citations
5.
McFarlane, Catherine, Rathika Krishnasamy, Tony Stanton, et al.. (2021). Diet Quality and Protein-Bound Uraemic Toxins: Investigation of Novel Risk Factors and the Role of Microbiome in Chronic Kidney Disease. Journal of Renal Nutrition. 32(5). 542–551. 28 indexed citations
8.
Huynh, Quan, Kazuaki Negishi, Carmine G. De Pasquale, et al.. (2021). Cognitive impairment as a determinant of response to management plans after heart failure admission. European Journal of Heart Failure. 23(7). 1205–1214. 11 indexed citations
10.
Prasad, S., et al.. (2019). Relation of Left Atrial Volumes in Patients With Myocardial Infarction to Left Ventricular Filling Pressures and Outcomes. The American Journal of Cardiology. 124(3). 325–333. 27 indexed citations
11.
Anstey, Chris, Christopher J. Boos, Edward Carlton, et al.. (2017). Myocardial blood flow reserve is impaired in patients with aortic valve calcification and unobstructed epicardial coronary arteries. International Journal of Cardiology. 248. 427–432. 5 indexed citations
12.
Woo, E.Y., et al.. (2017). Flecainide overdose-induced Brugada electrocardiogram pattern. QJM. 110(9). 607–607. 2 indexed citations
13.
Haluska, Brian, et al.. (2014). A family history of premature cardiovascular disease is independently associated with increased carotid intima-media thickness. European Heart Journal. 35. 225–225. 1 indexed citations
14.
Krishnasamy, Rathika, Nicole M. Isbel, Carmel M. Hawley, et al.. (2014). The association between left ventricular global longitudinal strain, renal impairment and all-cause mortality. Nephrology Dialysis Transplantation. 29(6). 1218–1225. 57 indexed citations
15.
Mordi, Ify, Tony Stanton, David Carrick, et al.. (2014). Comprehensive Dobutamine Stress CMR Versus Echocardiography in LBBB and Suspected Coronary Artery Disease. JACC. Cardiovascular imaging. 7(5). 490–498. 23 indexed citations
16.
Jellis, Christine, Tony Stanton, Rodel Leano, Jennifer Martin, & Thomas H. Marwick. (2011). Usefulness of At Rest and Exercise Hemodynamics to Detect Subclinical Myocardial Disease in Type 2 Diabetes Mellitus. The American Journal of Cardiology. 107(4). 615–621. 25 indexed citations
17.
Jenkins, Carly, Tony Stanton, & Thomas H. Marwick. (2010). What is the best predictor of outcome: ejection fraction or global strain?. Queensland's institutional digital repository (The University of Queensland). 1 indexed citations
18.
Jellis, Christine, Tony Stanton, Carly Jenkins, & Thomas H. Marwick. (2009). Reduced pressure-volume response to exercise may reflect subclinical myocardial disease in type 2 diabetes. Circulation. 120(18). 2 indexed citations
19.
Stanton, Tony, Gordon C. Inglis, Sandosh Padmanabhan, et al.. (2002). Variation at the beta-1 adrenoceptor gene locus affects left ventricular mass in renal failure.. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 15(5). 512–8. 15 indexed citations
20.
Stanton, Tony & John L. Reid. (2002). Fixed dose combination therapy in the treatment of hypertension. Journal of Human Hypertension. 16(2). 75–78. 34 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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