John G. Kingma

2.0k total citations
70 papers, 1.5k citations indexed

About

John G. Kingma is a scholar working on Cardiology and Cardiovascular Medicine, Pathology and Forensic Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, John G. Kingma has authored 70 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Cardiology and Cardiovascular Medicine, 31 papers in Pathology and Forensic Medicine and 16 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in John G. Kingma's work include Cardiac Ischemia and Reperfusion (31 papers), Cardiac electrophysiology and arrhythmias (19 papers) and Cardiac Imaging and Diagnostics (16 papers). John G. Kingma is often cited by papers focused on Cardiac Ischemia and Reperfusion (31 papers), Cardiac electrophysiology and arrhythmias (19 papers) and Cardiac Imaging and Diagnostics (16 papers). John G. Kingma collaborates with scholars based in Canada, United Kingdom and Netherlands. John G. Kingma's co-authors include R. William Currie, Jacques R. Rouleau, Jean G. Dumesnil, George Honos, Pascal Daleau, Jeffrey L. Ardell, J. Andrew Armour, Gerrit Eggink, Roland G. Lageveen and Derek M. Yellon and has published in prestigious journals such as Circulation, Journal of the American College of Cardiology and PLoS ONE.

In The Last Decade

John G. Kingma

70 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John G. Kingma Canada 19 701 454 326 173 171 70 1.5k
Ricardo J. Gelpi Argentina 24 726 1.0× 460 1.0× 642 2.0× 202 1.2× 137 0.8× 138 1.9k
Robert M. Lust United States 26 615 0.9× 505 1.1× 249 0.8× 580 3.4× 54 0.3× 86 2.2k
Boris Z. Simkhovich United States 23 340 0.5× 436 1.0× 556 1.7× 164 0.9× 65 0.4× 51 1.6k
Georg Daniel Duerr Germany 21 711 1.0× 448 1.0× 172 0.5× 298 1.7× 80 0.5× 63 1.5k
Matthias L. Riess United States 29 639 0.9× 883 1.9× 1.4k 4.2× 371 2.1× 165 1.0× 108 2.6k
José Nascimento Brazil 26 818 1.2× 389 0.9× 198 0.6× 122 0.7× 154 0.9× 109 1.8k
Detlef Obal United States 20 321 0.5× 238 0.5× 741 2.3× 185 1.1× 45 0.3× 43 1.4k
Monique C. de Waard Netherlands 25 497 0.7× 569 1.3× 132 0.4× 219 1.3× 54 0.3× 41 1.9k
Constantinos Pantos Greece 31 699 1.0× 1.1k 2.5× 429 1.3× 319 1.8× 157 0.9× 113 2.5k
Guy Berkenboom Belgium 21 595 0.8× 276 0.6× 158 0.5× 314 1.8× 157 0.9× 107 1.4k

Countries citing papers authored by John G. Kingma

Since Specialization
Citations

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

Fields of papers citing papers by John G. Kingma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John G. Kingma. 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 John G. Kingma. The network helps show where John G. Kingma may publish in the future.

Co-authorship network of co-authors of John G. Kingma

This figure shows the co-authorship network connecting the top 25 collaborators of John G. Kingma. A scholar is included among the top collaborators of John G. Kingma 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 John G. Kingma. John G. Kingma 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.
Kingma, John G.. (2021). Ischemic Conditioning-Mediated Myocardial Protection in Relation to Duration of Coronary Occlusion. World Journal of Cardiovascular Diseases. 11(3). 210–222. 1 indexed citations
2.
Kingma, John G.. (2018). Myocardial Infarction: An Overview of STEMI and NSTEMI Physiopathology and Treatment. World Journal of Cardiovascular Diseases. 8(11). 498–517. 16 indexed citations
3.
4.
Kingma, John G., et al.. (2014). Impact of Chronic Kidney Disease on Myocardial Blood Flow Regulation in Dogs. Nephron Experimental Nephrology. 126(4). 175–182. 5 indexed citations
5.
Kingma, John G., et al.. (2014). Nitric oxide bioavailability affects cardiovascular regulation dependent on cardiac nerve status. Autonomic Neuroscience. 187. 70–75. 2 indexed citations
6.
Kingma, John G.. (2014). Conditioning Strategies Limit Cellular Injury?. World Journal of Cardiovascular Diseases. 4(11). 539–547. 4 indexed citations
7.
Kingma, John G.. (2013). The myocardial microcirculation: A key target for salvaging ischemic myocardium?. World Journal of Cardiovascular Diseases. 3(5). 8–16. 1 indexed citations
8.
Kingma, John G., et al.. (2011). Modulation of nitric oxide affects myocardial perfusion-contraction matching in anaesthetized dogs with recurrent no-flow ischaemia. Experimental Physiology. 96(12). 1293–1301. 3 indexed citations
9.
Picichè, Marco, John G. Kingma, Élie Fadel, et al.. (2009). Enhancement of noncoronary collateral circulation: The hypothesis of an alternative treatment for ischemic heart disease. Medical Hypotheses. 74(1). 21–23. 8 indexed citations
10.
Sarrazin, J., Pascal Daleau, John G. Kingma, et al.. (2007). Reduced Incidence of Vagally Induced Atrial Fibrillation and Expression Levels of Connexins by n-3 Polyunsaturated Fatty Acids in Dogs. Journal of the American College of Cardiology. 50(15). 1505–1512. 83 indexed citations
11.
Kingma, John G., et al.. (2006). Influence of Acute Renal Failure on Coronary Vasoregulation in Dogs. Journal of the American Society of Nephrology. 17(5). 1316–1324. 35 indexed citations
12.
Kingma, John G., et al.. (2005). Comparison of Neutron Activated and Radiolabeled Microsphere Methods for Measurement of Transmural Myocardial Blood Flow in Dogs. Journal of Thrombosis and Thrombolysis. 19(3). 201–208. 9 indexed citations
13.
Armour, J. Andrew, Bengt Linderoth, Rakesh C. Arora, et al.. (2002). Long-term modulation of the intrinsic cardiac nervous system by spinal cord neurons in normal and ischaemic hearts. Autonomic Neuroscience. 95(1-2). 71–79. 64 indexed citations
14.
Rouleau, Jacques R., et al.. (2002). Myocardial blood flow after chronic cardiac decentralization in anesthetized dogs: effects of ACE-inhibition. Autonomic Neuroscience. 97(1). 12–18. 9 indexed citations
15.
Kingma, John G., Sylvain Planté, & Peter Bogaty. (2000). Platelet GPIIb/IIIa receptor blockade reduces infarct size in a canine model of ischemia-reperfusion. Journal of the American College of Cardiology. 36(7). 2317–2324. 24 indexed citations
16.
Kingma, John G.. (1999). Cardiac Adaptation to Ischemia‐Reperfusion Injurya. Annals of the New York Academy of Sciences. 874(1). 83–99. 17 indexed citations
17.
Kingma, John G., et al.. (1994). Timely administration of AICA riboside reduces reperfusion injury in rabbits. Cardiovascular Research. 28(7). 1003–1007. 25 indexed citations
18.
Kingma, John G. & Derek M. Yellon. (1992). Inability of dimethylthiourea to limit tissue necrosis during acute myocardial infarction in rabbits. Free Radical Biology and Medicine. 12(4). 263–270. 4 indexed citations
19.
20.
Kingma, John G., et al.. (1991). Reperfusion-induced arrhythmias are not prevented by uric acid in the isolated rat heart. Free Radical Biology and Medicine. 11(3). 319–326. 2 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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