Matthew Lumley

1.3k total citations
31 papers, 860 citations indexed

About

Matthew Lumley is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Matthew Lumley has authored 31 papers receiving a total of 860 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Cardiology and Cardiovascular Medicine, 11 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Surgery. Recurrent topics in Matthew Lumley's work include Cardiac Imaging and Diagnostics (11 papers), Cardiovascular Function and Risk Factors (5 papers) and Cardiac pacing and defibrillation studies (4 papers). Matthew Lumley is often cited by papers focused on Cardiac Imaging and Diagnostics (11 papers), Cardiovascular Function and Risk Factors (5 papers) and Cardiac pacing and defibrillation studies (4 papers). Matthew Lumley collaborates with scholars based in United Kingdom, Netherlands and Germany. Matthew Lumley's co-authors include Divaka Perera, Simon Redwood, Kalpa De Silva, Michael Marber, Brian Clapp, Natalia Briceno, Howard Ellis, Rod Stables, Tim Clayton and Martyn Thomas and has published in prestigious journals such as The Lancet, Circulation and Journal of the American College of Cardiology.

In The Last Decade

Matthew Lumley

29 papers receiving 845 citations

Peers

Matthew Lumley
Matthew Lumley
Citations per year, relative to Matthew Lumley Matthew Lumley (= 1×) peers Germán Cediel

Countries citing papers authored by Matthew Lumley

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Lumley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Lumley

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Lumley. A scholar is included among the top collaborators of Matthew Lumley 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 Matthew Lumley. Matthew Lumley 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.
Attarwala, Husain, et al.. (2022). Translational Pharmacokinetic/Pharmacodynamic Model for mRNA-3927, an Investigational Therapeutic for the Treatment of Propionic Acidemia. Nucleic Acid Therapeutics. 33(2). 141–147. 27 indexed citations
2.
Gordon, Jason, Oliver Darlington, Phil McEwan, et al.. (2020). Estimating the Value of New Antimicrobials in the Context of Antimicrobial Resistance: Development and Application of a Dynamic Disease Transmission Model. PharmacoEconomics. 38(8). 857–869. 23 indexed citations
3.
Hill, Nathan R., Daniel Ayoubkhani, Phil McEwan, et al.. (2019). Predicting atrial fibrillation in primary care using machine learning. PLoS ONE. 14(11). e0224582–e0224582. 90 indexed citations
4.
Brownrigg, Jack, Massimiliano Lorenzini, Matthew Lumley, & Perry Elliott. (2019). Diagnostic Performance of Imaging Investigations in Detecting and Differentiating Cardiac Amyloidosis: A Systematic Review and Meta-Analysis. ESC Heart Failure. 6(5). 1041–1051. 73 indexed citations
5.
Ayoubkhani, Daniel, Matthew Lumley, Steven Lister, et al.. (2018). Machine Learning to Detect and Diagnose Atrial Fibrillation and Atrial Flutter (AF/F) Using Routine Clinical Data. Value in Health. 21. S213–S213. 1 indexed citations
6.
Williams, Rupert, Kaleab Asrress, Matthew Lumley, et al.. (2018). Deleterious Effects of Cold Air Inhalation on Coronary Physiological Indices in Patients With Obstructive Coronary Artery Disease. Journal of the American Heart Association. 7(14). e008837–e008837. 5 indexed citations
7.
Lumley, Matthew, Laura McDonald, Sreeram V Ramagopalan, et al.. (2017). Evolving landscape of stroke prevention in atrial fibrillation within the UK between 2012 and 2016: a cross-sectional analysis study using CPRD. BMJ Open. 7(9). e015363–e015363. 30 indexed citations
8.
Williams, Rupert, Guus A. de Waard, Kalpa De Silva, et al.. (2017). Doppler Versus Thermodilution-Derived Coronary Microvascular Resistance to Predict Coronary Microvascular Dysfunction in Patients With Acute Myocardial Infarction or Stable Angina Pectoris. The American Journal of Cardiology. 121(1). 1–8. 72 indexed citations
9.
Arri, Satpal, Rupert Williams, Kaleab Asrress, et al.. (2017). UNRAVELLING THE MECHANISMS OF MENTAL STRESS INDUCED MYOCARDIAL ISCHAEMIA: NOVEL INSIGHTS FROM INTRACORONARY MEASUREMENTS DURING CARDIAC CATHETERISATION. Journal of the American College of Cardiology. 69(11). 13–13. 1 indexed citations
10.
Lumley, Matthew, Rupert Williams, Kaleab Asrress, et al.. (2016). Coronary Physiology During Exercise and Vasodilation in the Healthy Heart and in Severe Aortic Stenosis. Journal of the American College of Cardiology. 68(7). 688–697. 56 indexed citations
12.
Briceno, Natalia, Andreas Schuster, Matthew Lumley, & Divaka Perera. (2016). Ischaemic cardiomyopathy: pathophysiology, assessment and the role of revascularisation. Heart. 102(5). 397–406. 61 indexed citations
13.
Williams, Rupert, Kalpa De Silva, Matthew Lumley, et al.. (2015). DOPPLER INDICES OF RESISTANCE ARE SUPERIOR TO THERMODILUTION INDICES AT PREDICTING CORONARY MICROVASCULAR DYSFUNCTION. Journal of the American College of Cardiology. 65(10). A1843–A1843. 1 indexed citations
14.
Silva, Kalpa De, Matthew Lumley, Jordi Alastruey, et al.. (2014). Coronary and Microvascular Physiology During Intra-Aortic Balloon Counterpulsation. JACC: Cardiovascular Interventions. 7(6). 631–640. 48 indexed citations
15.
Asrress, Kaleab, Rupert Williams, Amedeo Chiribiri, et al.. (2014). A Unravelling the Mechanisms of Exercise Induced Ischaemia, its Optimal Assessment, and Alleviation with Nitroglycerine. Heart. 100(Suppl 3). A124.2–A125. 2 indexed citations
16.
Rolandi, Marco, Kalpa De Silva, Matthew Lumley, et al.. (2014). Wave speed in human coronary arteries is not influenced by microvascular vasodilation: implications for wave intensity analysis. Basic Research in Cardiology. 109(2). 18 indexed citations
17.
Sharma, Sumeet K., Matthew Lumley, & Divaka Perera. (2013). Intraaortic balloon pump use in high-risk percutaneous coronary intervention. Current Opinion in Cardiology. 28(6). 671–675. 6 indexed citations
18.
Lumley, Matthew, et al.. (2013). Inadvertent left internal mammary artery (LIMA): great cardiac vein anastomosis. BMJ Case Reports. 2013. bcr–2012.
19.
Perera, Divaka, Matthew Lumley, Nico H.J. Pijls, & Manesh R. Patel. (2013). Intra-aortic Balloon Pump Trials. Circulation Cardiovascular Interventions. 6(3). 317–321. 13 indexed citations
20.
Palmer, Julia E., et al.. (2002). Acquired factor VIII inhibitors as a cause of primary post-partum haemorrhage. European Journal of Obstetrics & Gynecology and Reproductive Biology. 103(1). 97–98. 15 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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