Tom Johnson

7.7k total citations · 2 hit papers
180 papers, 2.9k citations indexed

About

Tom Johnson is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Tom Johnson has authored 180 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Surgery, 91 papers in Cardiology and Cardiovascular Medicine and 58 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Tom Johnson's work include Coronary Interventions and Diagnostics (76 papers), Cardiac Imaging and Diagnostics (50 papers) and Acute Myocardial Infarction Research (45 papers). Tom Johnson is often cited by papers focused on Coronary Interventions and Diagnostics (76 papers), Cardiac Imaging and Diagnostics (50 papers) and Acute Myocardial Infarction Research (45 papers). Tom Johnson collaborates with scholars based in United Kingdom, United States and Netherlands. Tom Johnson's co-authors include Stephen J. White, Andrew C. Newby, Andreas Baumbach, David Adlam, Julian Strange, Abtehale Al-Hussaini, Fernándo Alfonso, Adrian Banning, Chiara Bucciarelli‐Ducci and Héctor Bueno and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and Journal of the American College of Cardiology.

In The Last Decade

Tom Johnson

167 papers receiving 2.8k citations

Hit Papers

align trajectories

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.

European Society of Cardiology, acute cardiovascular care association, SCAD study group: a position paper on spontaneous coronary artery dissection

2018 350 citations Tom Johnson et al. profile →
Percutaneous coronary intervention for bifurcation coronary lesions: the 15<sup>th</sup> consensus document from the European Bifurcation Club

2021 126 citations Tom Johnson et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tom Johnson United Kingdom	26	1.3k	1.3k	678	581	382	180	2.9k
Mitsuru Murata Japan	41	891 0.7×	1.3k 1.0×	230 0.3×	768 1.3×	817 2.1×	219	5.9k
M Takahashi Japan	35	1.1k 0.8×	1.1k 0.8×	643 0.9×	663 1.1×	361 0.9×	180	3.8k
Hein J. Verberne Netherlands	43	1.6k 1.2×	2.8k 2.1×	2.6k 3.8×	703 1.2×	536 1.4×	197	6.5k
Regent Lee United Kingdom	30	805 0.6×	943 0.7×	281 0.4×	471 0.8×	519 1.4×	86	2.8k
Mrinal K. Dewanjee United States	30	1.4k 1.1×	1.1k 0.8×	598 0.9×	774 1.3×	428 1.1×	139	3.4k
Shuichiro Kaji Japan	31	1.4k 1.1×	2.1k 1.6×	920 1.4×	1.1k 1.9×	467 1.2×	105	3.5k
Gerhard Mall Germany	31	534 0.4×	1.7k 1.3×	448 0.7×	735 1.3×	759 2.0×	79	4.8k
Robert Jan van Suylen Netherlands	34	712 0.5×	602 0.5×	602 0.9×	1.3k 2.2×	401 1.0×	75	3.1k
Hendrikus H. Boersma Netherlands	29	469 0.4×	614 0.5×	746 1.1×	517 0.9×	823 2.2×	95	2.6k
Yoko Ito Japan	29	703 0.5×	358 0.3×	715 1.1×	1.5k 2.6×	559 1.5×	105	3.9k

Countries citing papers authored by Tom Johnson

Since Specialization

Citations

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

Fields of papers citing papers by Tom Johnson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Johnson

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Lee, Oh‐Hyun, Seok‐Jae Heo, Tom Johnson, et al.. (2024). Intervención coronaria percutánea guiada por tomografía de coherencia óptica frente a guiada por ecografía intravascular en pacientes con infarto agudo de miocardio. Revista Española de Cardiología. 77(8). 607–617. 2 indexed citations

Chamié, Daniel, Mauro Echavarría‐Pinto, Ecaterina Cristea, et al.. (2024). Can Contrast Injections Cause or Propagate Coronary Injuries? Insights From Vessel and Guiding Catheter Hemodynamics. Journal of the Society for Cardiovascular Angiography & Interventions. 3(12). 102396–102396.

Hinton, Jonathan, et al.. (2024). Artificial Intelligence for the Interventional Cardiologist: Powering and Enabling OCT Image Interpretation. Interventional Cardiology Reviews Research Resources. 19. e03–e03. 8 indexed citations

Johnson, Tom, Olga Selioutski, Mark Marinescu, et al.. (2024). Wavelet and time-based cerebral autoregulation analysis using diffuse correlation spectroscopy on adults undergoing extracorporeal membrane oxygenation therapy. PLoS ONE. 19(10). e0299752–e0299752.

Bisaccia, Giandomenico, Isabella Leo, Matthew Williams, et al.. (2023). CMR reclassifies the majority of patients with suspected MINOCA and non MINOCA. European Heart Journal - Cardiovascular Imaging. 25(1). 8–15. 6 indexed citations

Haake, Steve, et al.. (2023). Parkrun as self-managed cardiac rehabilitation: secondary analysis of a cross-sectional survey of parkrun in the UK. Open Heart. 10(2). e002355–e002355. 1 indexed citations

Pareek, Nilesh, C. Frohmaier, M. Smith, et al.. (2023). A machine learning algorithm to predict a culprit lesion after out of hospital cardiac arrest. Catheterization and Cardiovascular Interventions. 102(1). 80–90. 2 indexed citations

Harris, Jessica, Koen B. Pouwels, Tom Johnson, et al.. (2023). Bleeding risk in patients prescribed dual antiplatelet therapy and triple therapy after coronary interventions: the ADAPTT retrospective population-based cohort studies. Health Technology Assessment. 27(8). 1–257. 6 indexed citations

Pareek, Nilesh, Antonio Cannatà, Peter Kordis, et al.. (2022). MIRACLE2 Score and SCAI Grade to Identify Patients With Out-of-Hospital Cardiac Arrest for Immediate Coronary Angiography. JACC: Cardiovascular Interventions. 15(10). 1074–1084. 13 indexed citations

10.

Pareek, Nilesh, Paul Rees, Tom Quinn, et al.. (2022). British Cardiovascular Interventional Society Consensus Position Statement on Out-of-Hospital Cardiac Arrest 1: Pathway of Care. Interventional Cardiology Reviews Research Resources. 17. e18–e18. 5 indexed citations

11.

Mion, Marco, Tom Johnson, Valentino Oriolo, et al.. (2022). British Cardiovascular Intervention Society Consensus Position Statement on Out-of-hospital Cardiac Arrest 2: Post-discharge Rehabilitation. Interventional Cardiology Reviews Research Resources. 17. e19–e19. 8 indexed citations

12.

Pufulete, Maria, Tom Johnson, Sabi Redwood, et al.. (2022). Confounders and co-interventions identified in non-randomized studies of interventions. Journal of Clinical Epidemiology. 148. 115–123. 1 indexed citations

13.

Williams, Matthew, Estefania De Gárate, Amardeep Ghosh Dastidar, et al.. (2022). Peak Troponin and CMR to Guide Management in Suspected ACS and Nonobstructive Coronary Arteries. JACC. Cardiovascular imaging. 15(9). 1578–1587. 25 indexed citations

14.

Mohamed, Mohamed O., Tim Kinnaird, Harindra C. Wijeysundera, et al.. (2022). Impact of Intracoronary Imaging‐Guided Percutaneous Coronary Intervention on Procedural Outcomes Among Complex Patient Groups. Journal of the American Heart Association. 11(19). e026500–e026500. 7 indexed citations

15.

Johnson, Tom, et al.. (2022). Intracoronary optical coherence tomography—An introduction. Catheterization and Cardiovascular Interventions. 100(S1). 1 indexed citations

16.

Johnson, Tom, Sarah Baos, James L. Hutchinson, et al.. (2020). Pharmacodynamic Comparison of Ticagrelor Monotherapy Versus Ticagrelor and Aspirin in Patients After Percutaneous Coronary Intervention: The TEMPLATE (Ticagrelor Monotherapy and Platelet Reactivity) Randomized Controlled Trial. Journal of the American Heart Association. 9(24). e016495–e016495. 13 indexed citations

17.

Erickson, Benjamin P., et al.. (2020). The Superficial Temporal Artery as ‘Biologic Jones Tube’: A Cadaveric Proof of Concept. Investigative Ophthalmology & Visual Science. 61(7). 401–401. 2 indexed citations

18.

Kim, Yongcheol, Tom Johnson, Min Chul Kim, et al.. (2019). Optical Coherence Tomography Findings of Non-ST Elevation Myocardial Infarction with Multivessel Disease. Korean Circulation Journal. 50(1). 88–88. 1 indexed citations

19.

Baos, Sarah, Lucy Culliford, Barnaby C Reeves, et al.. (2017). Platelet inhibition during ticagrelor monotherapy versus ticagrelor plus aspirin in patients with coronary artery disease (TEMPLATE study): study protocol for a randomised controlled trial. Trials. 18(1). 529–529. 6 indexed citations

20.

Vlodaver, Zeev, Tom Johnson, James N. Karnegis, Jesse E. Edwards, & Aldo R. Castañeda. (1973). Clinical pathologic conference. American Heart Journal. 85(5). 689–694. 1 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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