Tom Abbott

14.6k total citations · 1 hit paper
64 papers, 1.8k citations indexed

About

Tom Abbott is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Tom Abbott has authored 64 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Cardiology and Cardiovascular Medicine, 27 papers in Surgery and 10 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Tom Abbott's work include Cardiac, Anesthesia and Surgical Outcomes (38 papers), Hemodynamic Monitoring and Therapy (15 papers) and Blood Pressure and Hypertension Studies (7 papers). Tom Abbott is often cited by papers focused on Cardiac, Anesthesia and Surgical Outcomes (38 papers), Hemodynamic Monitoring and Therapy (15 papers) and Blood Pressure and Hypertension Studies (7 papers). Tom Abbott collaborates with scholars based in United Kingdom, Canada and United States. Tom Abbott's co-authors include Rupert M. Pearse, Alexander J. Fowler, John R. Prowle, Gareth L. Ackland, Gil Mor, Kathryn L. Stone, Baolin Wu, David A. Fishman, Kenneth R. Williams and Hongyu Zhao and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Tom Abbott

58 papers receiving 1.7k citations

Hit Papers

Age of patients undergoing surgery 2019 2026 2021 2023 2019 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Abbott United Kingdom 22 750 667 281 177 167 64 1.8k
Peng Jin China 23 462 0.6× 741 1.1× 258 0.9× 198 1.1× 242 1.4× 113 1.9k
Warren S. Sandberg United States 34 1.1k 1.5× 1.3k 2.0× 489 1.7× 326 1.8× 336 2.0× 118 3.2k
Alexander Thompson United Kingdom 19 672 0.9× 1.0k 1.5× 275 1.0× 57 0.3× 177 1.1× 51 2.6k
Mark de Groot Netherlands 24 263 0.4× 350 0.5× 245 0.9× 121 0.7× 236 1.4× 81 1.6k
Sarah Clarke United Kingdom 20 553 0.7× 581 0.9× 956 3.4× 275 1.6× 249 1.5× 47 2.6k
Jonathan Benn United Kingdom 26 226 0.3× 445 0.7× 318 1.1× 114 0.6× 68 0.4× 83 2.8k
Quinn S. Wells United States 31 1.7k 2.2× 527 0.8× 522 1.9× 133 0.8× 661 4.0× 126 3.1k
Matthew W. Segar United States 21 755 1.0× 138 0.2× 376 1.3× 65 0.4× 119 0.7× 68 1.6k
Stefan Gräber Germany 29 565 0.8× 655 1.0× 286 1.0× 31 0.2× 525 3.1× 74 2.6k
Mei Wang China 30 1.3k 1.7× 555 0.8× 187 0.7× 29 0.2× 482 2.9× 138 3.1k

Countries citing papers authored by Tom Abbott

Since Specialization
Citations

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

Fields of papers citing papers by Tom Abbott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Abbott

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Abbott. A scholar is included among the top collaborators of Tom Abbott 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 Abbott. Tom Abbott 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
3.
Ackland, Gareth L., Stuart Miller, Ana Gutierrez del Arroyo, et al.. (2025). Non-invasive vagus nerve stimulation and exercise capacity in healthy volunteers: a randomized trial. European Heart Journal. 46(17). 1634–1644. 4 indexed citations
4.
Abbott, Tom, Salma Begum, Priyanthi Dias, et al.. (2025). Platform trials—an emerging methodology for perioperative medicine: a narrative review. Perioperative Medicine. 14(1). 67–67.
5.
Fowler, Alexander J., Priyanthi Dias, Bruce Biccard, et al.. (2024). The lifetime risk of surgery in England: a nationwide observational cohort study. British Journal of Anaesthesia. 133(4). 768–775. 3 indexed citations
6.
Fowler, Alexander J., et al.. (2024). Environmental impact of commonly used anaesthetic agents: systematic literature review with narrative synthesis. SHILAP Revista de lepidopterología. 13. 100362–100362. 1 indexed citations
8.
Fowler, Alexander J., et al.. (2021). Routine postoperative noninvasive respiratory support and pneumonia after elective surgery: a systematic review and meta-analysis of randomised trials. British Journal of Anaesthesia. 128(2). 363–374. 13 indexed citations
9.
Abbott, Tom, Alexander J. Fowler, Thomas D. Dobbs, et al.. (2021). Mortality after surgery with SARS-CoV-2 infection in England: a population-wide epidemiological study. British Journal of Anaesthesia. 127(2). 205–214. 22 indexed citations
10.
Dobbs, Thomas D., John Gibson, Alexander J. Fowler, et al.. (2021). Surgical activity in England and Wales during the COVID-19 pandemic: a nationwide observational cohort study. British Journal of Anaesthesia. 127(2). 196–204. 46 indexed citations
11.
Fowler, Alexander J., Thomas D. Dobbs, Yize I. Wan, et al.. (2020). Resource requirements for reintroducing elective surgery during the COVID-19 pandemic: modelling study. British journal of surgery. 108(1). 97–103. 30 indexed citations
12.
Abbott, Tom, Shaun M. May, Brian H. Cuthbertson, et al.. (2019). Perioperative plasma cortisol levels and myocardial injury after non-cardiac surgery. British Journal of Anaesthesia. 122(3). e45–e46. 1 indexed citations
13.
May, Shaun M., Tom Abbott, Ana Gutierrez del Arroyo, et al.. (2019). Serum microRNAs and perioperative myocardial injury. British Journal of Anaesthesia. 122(3). e45–e45. 1 indexed citations
14.
Fowler, Alexander J., Tahania Ahmad, Tom Abbott, et al.. (2018). Association of preoperative anaemia with postoperative morbidity and mortality: an observational cohort study in low-, middle-, and high-income countries. British Journal of Anaesthesia. 121(6). 1227–1235. 46 indexed citations
15.
Abbott, Tom, Rupert M. Pearse, Brian H. Cuthbertson, Duminda N. Wijeysundera, & Gareth L. Ackland. (2018). Cardiac vagal dysfunction and myocardial injury after non-cardiac surgery: a planned secondary analysis of the measurement of Exercise Tolerance before surgery study. British Journal of Anaesthesia. 122(2). 188–197. 20 indexed citations
16.
Torrance, Hew D.T., Tom Abbott, Gareth L. Ackland, et al.. (2018). Post-operative immune suppression is mediated via reversible, Interleukin-10 dependent pathways in circulating monocytes following major abdominal surgery. PLoS ONE. 13(9). e0203795–e0203795. 25 indexed citations
17.
Abbott, Tom, Alexander J. Fowler, Thomas D. Dobbs, et al.. (2017). Frequency of surgical treatment and related hospital procedures in the UK: a national ecological study using hospital episode statistics. British Journal of Anaesthesia. 119(2). 249–257. 148 indexed citations
18.
Abbott, Tom, et al.. (2017). Elevated preoperative heart rate is associated with cardiopulmonary and autonomic impairment in high-risk surgical patients. British Journal of Anaesthesia. 119(1). 87–94. 21 indexed citations
19.
Pandit, Jaideep J., et al.. (2012). Is ‘starting on time’ useful (or useless) as a surrogate measure for ‘surgical theatre efficiency’?*. Anaesthesia. 67(8). 823–832. 34 indexed citations
20.
Wu, Baolin, Tom Abbott, David A. Fishman, et al.. (2003). Comparison of statistical methods for classification of ovarian cancer using mass spectrometry data. Bioinformatics. 19(13). 1636–1643. 348 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026