Stephen T. Vernon

2.0k total citations · 1 hit paper
41 papers, 1.1k citations indexed

About

Stephen T. Vernon is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Stephen T. Vernon has authored 41 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cardiology and Cardiovascular Medicine, 10 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Molecular Biology. Recurrent topics in Stephen T. Vernon's work include Acute Myocardial Infarction Research (13 papers), Cardiac Imaging and Diagnostics (9 papers) and Atherosclerosis and Cardiovascular Diseases (7 papers). Stephen T. Vernon is often cited by papers focused on Acute Myocardial Infarction Research (13 papers), Cardiac Imaging and Diagnostics (9 papers) and Atherosclerosis and Cardiovascular Diseases (7 papers). Stephen T. Vernon collaborates with scholars based in Australia, New Zealand and Sweden. Stephen T. Vernon's co-authors include Gemma A. Figtree, Emil Hagström, Clara K Chow, Jean Yang, Sean Coffey, Stuart M. Grieve, Nermin Hadziosmanovic, John O’Sullivan, Margrét Leósdóttir and Johan Sundström and has published in prestigious journals such as The Lancet, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Stephen T. Vernon

39 papers receiving 1.1k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Mortality in STEMI patients without standard modifiable risk factors: a sex-disaggregated analysis of SWEDEHEART registry data

2021 179 citations Gemma A. Figtree, Stephen T. Vernon et al. The Lancet profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Stephen T. Vernon Australia	17	609	223	199	152	86	41	1.1k
Max M. He United States	18	926 1.5×	227 1.0×	199 1.0×	163 1.1×	80 0.9×	31	1.5k
Yaohua He United States	17	230 0.4×	622 2.8×	69 0.3×	192 1.3×	23 0.3×	41	1.3k
Hesong Zeng China	20	696 1.1×	303 1.4×	242 1.2×	201 1.3×	87 1.0×	81	1.5k
Kerstin Weitmann Germany	19	922 1.5×	148 0.7×	403 2.0×	208 1.4×	76 0.9×	58	1.6k
Kristian Hindberg Norway	16	203 0.3×	88 0.4×	33 0.2×	119 0.8×	64 0.7×	53	869
Eliot Schechter United States	20	752 1.2×	348 1.6×	277 1.4×	105 0.7×	27 0.3×	46	1.2k
Katsuki Okada Japan	14	483 0.8×	364 1.6×	206 1.0×	154 1.0×	30 0.3×	68	887
Κωνσταντίνος Λαμπρόπουλος Greece	14	356 0.6×	161 0.7×	36 0.2×	74 0.5×	65 0.8×	79	771
Aaron Peace United Kingdom	23	678 1.1×	477 2.1×	260 1.3×	66 0.4×	46 0.5×	82	1.2k

Countries citing papers authored by Stephen T. Vernon

Since Specialization

Citations

This map shows the geographic impact of Stephen T. Vernon'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 Stephen T. Vernon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen T. Vernon more than expected).

Fields of papers citing papers by Stephen T. Vernon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen T. Vernon. 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 Stephen T. Vernon. The network helps show where Stephen T. Vernon may publish in the future.

Co-authorship network of co-authors of Stephen T. Vernon

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

All Works

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20 of 20 papers shown

Gray, Michael P., David S. Celermajer, Helen M. McGuire, et al.. (2024). Vascular Cytokines and Atherosclerosis: Differential Serum Levels of TRAIL, IL-18, and OPG in Obstructive Coronary Artery Disease. Biomolecules. 14(9). 1119–1119. 2 indexed citations

Vernon, Stephen T., et al.. (2024). Expression of Myeloperoxidase in Patient-Derived Endothelial Colony-Forming Cells—Associations with Coronary Artery Disease and Mitochondrial Function. Biomolecules. 14(10). 1308–1308. 2 indexed citations

Vernon, Stephen T., Stuart J. Brentnall, Michael P. Gray, et al.. (2024). Health economic analysis of polygenic risk score use in primary prevention of coronary artery disease – A system dynamics model. SHILAP Revista de lepidopterología. 18. 100672–100672. 7 indexed citations

Kott, Kayleen S., Stephen T. Vernon, Ellis Patrick, et al.. (2023). Acute exposure to PM2.5 promotes arterial stiffening by down-regulating serine and trans-4-hydroxyproline dependent pathways - results from an Asutralian cohort metabolomic study. European Heart Journal. 44(Supplement_2).

Besnier, Marie, Owen Tang, Katharine A. Kott, et al.. (2023). High-Throughput Measure of Mitochondrial Superoxide Levels as a Marker of Coronary Artery Disease to Accelerate Drug Translation in Patient-Derived Endothelial Cells Using Opera Phenix® Technology. International Journal of Molecular Sciences. 25(1). 22–22. 4 indexed citations

Kott, Katharine A., Michael P. Gray, Peter Riis Hansen, et al.. (2023). Serum Soluble Lectin-like Oxidized Low-Density Lipoprotein Receptor-1 (sLOX-1) Is Associated with Atherosclerosis Severity in Coronary Artery Disease. Biomolecules. 13(8). 1187–1187. 4 indexed citations

Vernon, Stephen T., Owen Tang, Gemma A. Figtree, et al.. (2023). Overcoming cohort heterogeneity for the prediction of subclinical cardiovascular disease risk. iScience. 26(5). 106633–106633. 2 indexed citations

Coorey, Genevieve, Gemma A. Figtree, David F. Fletcher, et al.. (2022). The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field. npj Digital Medicine. 5(1). 126–126. 167 indexed citations

Mazhar, J., Rebecca Kozor, Stuart M. Grieve, et al.. (2022). Cardiovascular magnetic resonance characteristics and clinical outcomes of patients with ST-elevation myocardial infarction and no standard modifiable risk factors–A DANAMI-3 substudy. Frontiers in Cardiovascular Medicine. 9. 945815–945815. 6 indexed citations

10.

Kott, Katharine A., M. D. Bishop, Louise Cullen, et al.. (2022). Biomarker Development in Cardiology: Reviewing the Past to Inform the Future. Cells. 11(3). 588–588. 10 indexed citations

11.

Vernon, Stephen T., Owen Tang, Tai-Yun Kim, et al.. (2021). Metabolic Signatures in Coronary Artery Disease: Results from the BioHEART-CT Study. Cells. 10(5). 980–980. 17 indexed citations

12.

Besnier, Marie, Christine Yu, Katharine A. Kott, et al.. (2021). Patient Endothelial Colony-Forming Cells to Model Coronary Artery Disease Susceptibility and Unravel the Role of Dysregulated Mitochondrial Redox Signalling. Antioxidants. 10(10). 1547–1547. 10 indexed citations

13.

Kim, Tai-Yun, Owen Tang, Stephen T. Vernon, et al.. (2021). A hierarchical approach to removal of unwanted variation for large-scale metabolomics data. Nature Communications. 12(1). 4992–4992. 28 indexed citations

14.

Figtree, Gemma A., Stephen T. Vernon, Nermin Hadziosmanovic, et al.. (2021). Mortality in STEMI patients without standard modifiable risk factors: a sex-disaggregated analysis of SWEDEHEART registry data. The Lancet. 397(10279). 1085–1094. 179 indexed citations breakdown →

15.

Figtree, Gemma A., et al.. (2021). Mortality in STEMI Patients Without Standard Modifiable Risk Factors: A Sex-Disaggregated Analysis of SWEDEHEART Registry Data. Journal of Emergency Medicine. 61(1). 117–118. 1 indexed citations

16.

Tam, Charmaine S., Janice Gullick, Stephen T. Vernon, et al.. (2021). Combining structured and unstructured data in EMRs to create clinically-defined EMR-derived cohorts. BMC Medical Informatics and Decision Making. 21(1). 91–91. 11 indexed citations

17.

Kott, Katharine A., Marie‐Christine Morel‐Kopp, Stephen T. Vernon, et al.. (2021). Association of Global Coagulation Profiles With Cardiovascular Risk Factors and Atherosclerosis: A Sex Disaggregated Analysis From the BioHEART‐CT Study. Journal of the American Heart Association. 10(20). e020604–e020604. 8 indexed citations

18.

Vernon, Stephen T., Katharine A. Kott, Thomas Hansen, Sheryl van Nunen, & Gemma A. Figtree. (2020). 446 Association of Mammalian Oligosaccharide Galactose-α-1,3-galactose (α-Gal) With Atherosclerotic Coronary Artery Disease. Heart Lung and Circulation. 29. S237–S238. 1 indexed citations

19.

Figtree, Gemma A., Stephen T. Vernon, & Stephen J. Nicholls. (2020). Taking the next steps to implement polygenic risk scoring for improved risk stratification and primary prevention of coronary artery disease. European Journal of Preventive Cardiology. 29(4). 580–587. 15 indexed citations

20.

Kott, Katharine A., Stephen T. Vernon, Thomas Hansen, et al.. (2019). Biobanking for discovery of novel cardiovascular biomarkers using imaging-quantified disease burden: protocol for the longitudinal, prospective, BioHEART-CT cohort study. BMJ Open. 9(9). e028649–e028649. 38 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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