David A. Lomas

23.2k total citations · 9 hit papers
123 papers, 12.7k citations indexed

About

David A. Lomas is a scholar working on Pulmonary and Respiratory Medicine, Physiology and Emergency Medical Services. According to data from OpenAlex, David A. Lomas has authored 123 papers receiving a total of 12.7k indexed citations (citations by other indexed papers that have themselves been cited), including 112 papers in Pulmonary and Respiratory Medicine, 52 papers in Physiology and 15 papers in Emergency Medical Services. Recurrent topics in David A. Lomas's work include Chronic Obstructive Pulmonary Disease (COPD) Research (107 papers), Asthma and respiratory diseases (46 papers) and Respiratory Support and Mechanisms (37 papers). David A. Lomas is often cited by papers focused on Chronic Obstructive Pulmonary Disease (COPD) Research (107 papers), Asthma and respiratory diseases (46 papers) and Respiratory Support and Mechanisms (37 papers). David A. Lomas collaborates with scholars based in United Kingdom, United States and Denmark. David A. Lomas's co-authors include Ruth Tal‐Singer, Edwin K. Silverman, Bruce E. Miller, William MacNee, Àlvar Agustí, Jørgen Vestbo, Peter M.A. Calverley, Stephen I. Rennard, Lisa Edwards and Harvey O. Coxson and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Investigation and PLoS ONE.

In The Last Decade

David A. Lomas

123 papers receiving 12.5k citations

Hit Papers

Susceptibility to Exacerbation in Chronic Obstructive Pul... 2008 2026 2014 2020 2010 2010 2018 2011 2012 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David A. Lomas United Kingdom 53 10.6k 5.3k 1.5k 1.0k 909 123 12.7k
Borja G. Cosío Spain 57 5.5k 0.5× 3.3k 0.6× 1.7k 1.1× 590 0.6× 1.0k 1.1× 266 12.4k
Julie Yates United Kingdom 40 9.3k 0.9× 5.0k 1.0× 553 0.4× 522 0.5× 917 1.0× 94 10.7k
Nick H.T. ten Hacken Netherlands 47 5.2k 0.5× 3.1k 0.6× 978 0.6× 409 0.4× 466 0.5× 185 7.5k
Roland Buhl Germany 52 5.6k 0.5× 5.0k 1.0× 1.0k 0.7× 404 0.4× 819 0.9× 224 9.6k
Craig P. Hersh United States 44 4.4k 0.4× 2.1k 0.4× 1.3k 0.8× 620 0.6× 266 0.3× 185 6.1k
Claudia Côté United States 37 7.7k 0.7× 3.1k 0.6× 672 0.4× 291 0.3× 834 0.9× 63 9.6k
Henrik Watz Germany 41 5.9k 0.6× 3.3k 0.6× 593 0.4× 294 0.3× 444 0.5× 188 7.3k
Víctor Pinto-Plata United States 44 6.8k 0.6× 2.5k 0.5× 417 0.3× 370 0.4× 652 0.7× 106 7.9k
Sang‐Heon Cho South Korea 46 2.8k 0.3× 3.9k 0.7× 811 0.5× 640 0.6× 1.5k 1.7× 338 9.4k
Lisa Edwards United States 39 6.4k 0.6× 3.5k 0.7× 376 0.2× 408 0.4× 509 0.6× 113 7.5k

Countries citing papers authored by David A. Lomas

Since Specialization
Citations

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

Fields of papers citing papers by David A. Lomas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. Lomas. 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 David A. Lomas. The network helps show where David A. Lomas may publish in the future.

Co-authorship network of co-authors of David A. Lomas

This figure shows the co-authorship network connecting the top 25 collaborators of David A. Lomas. A scholar is included among the top collaborators of David A. Lomas 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 David A. Lomas. David A. Lomas 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.
Han, MeiLan K., Gerard J. Criner, Mark T. Dransfield, et al.. (2020). The Effect of Inhaled Corticosteroid Withdrawal and Baseline Inhaled Treatment on Exacerbations in the IMPACT Study. A Randomized, Double-Blind, Multicenter Clinical Trial. American Journal of Respiratory and Critical Care Medicine. 202(9). 1237–1243. 20 indexed citations
2.
Lipson, David A., Courtney Crim, Gerard J. Criner, et al.. (2020). Reduction in All-Cause Mortality with Fluticasone Furoate/Umeclidinium/Vilanterol in Patients with Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 201(12). 1508–1516. 146 indexed citations
3.
Pascoe, Steven, Neil Barnes, Guy Brusselle, et al.. (2019). Blood eosinophils and treatment response with triple and dual combination therapy in chronic obstructive pulmonary disease: analysis of the IMPACT trial. The Lancet Respiratory Medicine. 7(9). 745–756. 153 indexed citations
4.
Lipson, David A., Helen Barnacle, Ruby Birk, et al.. (2017). FULFIL Trial: Once-Daily Triple Therapy for Patients with Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 196(4). 438–446. 226 indexed citations
5.
Briggs, Andrew, Timothy Baker, Nancy Risebrough, et al.. (2016). Development of the Galaxy Chronic Obstructive Pulmonary Disease (COPD) Model Using Data from ECLIPSE: Internal Validation of a Linked-Equations Cohort Model. Medical Decision Making. 37(4). 469–480. 28 indexed citations
6.
Yonchuk, John, Edwin K. Silverman, Russell P. Bowler, et al.. (2015). Circulating Soluble Receptor for Advanced Glycation End Products (sRAGE) as a Biomarker of Emphysema and the RAGE Axis in the Lung. American Journal of Respiratory and Critical Care Medicine. 192(7). 785–792. 72 indexed citations
7.
Vestbo, Jørgen, Àlvar Agustí, Emiel F.�M. Wouters, et al.. (2014). Should We View Chronic Obstructive Pulmonary Disease Differently after ECLIPSE?. A Clinical Perspective from the Study Team. American Journal of Respiratory and Critical Care Medicine. 189(9). 1022–1030. 105 indexed citations
8.
Bafadhel, Mona, Susan McKenna, Sarah Terry, et al.. (2012). Blood Eosinophils to Direct Corticosteroid Treatment of Exacerbations of Chronic Obstructive Pulmonary Disease: A Randomized Placebo-Controlled Trial. American Journal of Respiratory and Critical Care Medicine. 186(1). 48–55. 422 indexed citations breakdown →
9.
Polkey, Michael I., Martijn A. Spruit, Lisa Edwards, et al.. (2012). Six-Minute-Walk Test in Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 187(4). 382–386. 239 indexed citations
10.
Celli, Bartolomé R., Nicholas Locantore, Julie Yates, et al.. (2012). Inflammatory Biomarkers Improve Clinical Prediction of Mortality in Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 185(10). 1065–1072. 313 indexed citations breakdown →
11.
Wan, Emily S., Weiliang Qiu, Andrea Baccarelli, et al.. (2012). Systemic Steroid Exposure Is Associated with Differential Methylation in Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 186(12). 1248–1255. 62 indexed citations
12.
Hersh, Craig P., Edwin K. Silverman, Soumyaroop Bhattacharya, et al.. (2011). SOX5 Is a Candidate Gene for Chronic Obstructive Pulmonary Disease Susceptibility and Is Necessary for Lung Development. American Journal of Respiratory and Critical Care Medicine. 183(11). 1482–1489. 53 indexed citations
13.
Sin, Don D., Bruce E. Miller, Annelyse Duvoix, et al.. (2011). Serum PARC/CCL-18 Concentrations and Health Outcomes in Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 183(9). 1187–1192. 84 indexed citations
14.
Qiu, Weiliang, Andrea Baccarelli, Vincent J. Carey, et al.. (2011). Variable DNA Methylation Is Associated with Chronic Obstructive Pulmonary Disease and Lung Function. American Journal of Respiratory and Critical Care Medicine. 185(4). 373–381. 174 indexed citations
15.
Castaldi, Peter J., Michael H. Cho, Augusto A. Litonjua, et al.. (2011). The Association of Genome-Wide Significant Spirometric Loci with Chronic Obstructive Pulmonary Disease Susceptibility. American Journal of Respiratory Cell and Molecular Biology. 45(6). 1147–1153. 66 indexed citations
16.
Pillai, Sreekumar, Xiangyang Kong, Lisa Edwards, et al.. (2010). Loci Identified by Genome-wide Association Studies Influence Different Disease-related Phenotypes in Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 182(12). 1498–1505. 111 indexed citations
17.
Kong, Xiangyang, Michael H. Cho, W. J. Anderson, et al.. (2010). Genome-wide Association Study Identifies BICD1 as a Susceptibility Gene for Emphysema. American Journal of Respiratory and Critical Care Medicine. 183(1). 43–49. 83 indexed citations
18.
Pillai, Sreekumar, Dongliang Ge, Guohua Zhu, et al.. (2009). A Genome-Wide Association Study in Chronic Obstructive Pulmonary Disease (COPD): Identification of Two Major Susceptibility Loci. PLoS Genetics. 5(3). e1000421–e1000421. 480 indexed citations breakdown →
19.
Zhu, Guohua, Liling Warren, Jennifer L. Aponte, et al.. (2007). The SERPINE2 Gene is Associated with Chronic Obstructive Pulmonary Disease in Two Large Populations. American Journal of Respiratory and Critical Care Medicine. 176(2). 167–173. 97 indexed citations
20.
Patel, Bipen D., et al.. (2001). Siblings of Patients With Severe Chronic Obstructive Pulmonary Disease Have a Significant Risk of Airflow Obstruction. American Journal of Respiratory and Critical Care Medicine. 164(8). 1419–1424. 121 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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