Tamás Szakmány

10.0k total citations · 1 hit paper
96 papers, 1.6k citations indexed

About

Tamás Szakmány is a scholar working on Epidemiology, Pulmonary and Respiratory Medicine and Critical Care and Intensive Care Medicine. According to data from OpenAlex, Tamás Szakmány has authored 96 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Epidemiology, 31 papers in Pulmonary and Respiratory Medicine and 26 papers in Critical Care and Intensive Care Medicine. Recurrent topics in Tamás Szakmány's work include Sepsis Diagnosis and Treatment (32 papers), Respiratory Support and Mechanisms (23 papers) and Intensive Care Unit Cognitive Disorders (17 papers). Tamás Szakmány is often cited by papers focused on Sepsis Diagnosis and Treatment (32 papers), Respiratory Support and Mechanisms (23 papers) and Intensive Care Unit Cognitive Disorders (17 papers). Tamás Szakmány collaborates with scholars based in United Kingdom, Hungary and United States. Tamás Szakmány's co-authors include Zsolt Molnár, A Mikor, Xavier Wittebole, Marc Léone, Jean‐Louis Vincent, Yasser Sakr, Tamás Leiner, Mary‐Nicoleta Lupu, Jeffrey Lipman and Ignacio Martín‐Loeches and has published in prestigious journals such as The Journal of Immunology, Scientific Reports and Cochrane Database of Systematic Reviews.

In The Last Decade

Tamás Szakmány

89 papers receiving 1.6k 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.

Sepsis in Intensive Care Unit Patients: Worldwide Data From the Intensive Care over Nations Audit

2018 306 citations Yasser Sakr, Ulrich Jaschinski et al. Open Forum Infectious Diseases profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tamás Szakmány United Kingdom	21	577	432	405	350	227	96	1.6k
Silvio A. Ñamendys‐Silva Mexico	18	950 1.6×	355 0.8×	475 1.2×	344 1.0×	217 1.0×	68	2.0k
Stefano Busani Italy	20	557 1.0×	473 1.1×	364 0.9×	334 1.0×	281 1.2×	65	1.7k
Fabián Jaimes Colombia	22	1.0k 1.8×	269 0.6×	351 0.9×	348 1.0×	219 1.0×	151	2.1k
Pierre‐François Dequin France	23	559 1.0×	350 0.8×	243 0.6×	423 1.2×	163 0.7×	76	1.5k
Iraklis Tsangaris Greece	27	1.1k 1.8×	613 1.4×	397 1.0×	238 0.7×	148 0.7×	84	2.3k
David J. Murphy United States	19	1.2k 2.1×	377 0.9×	656 1.6×	329 0.9×	322 1.4×	56	2.5k
John Pappachan United Kingdom	16	894 1.5×	422 1.0×	223 0.6×	278 0.8×	293 1.3×	57	1.7k
Dimitrios Velissaris Greece	20	719 1.2×	217 0.5×	254 0.6×	428 1.2×	120 0.5×	99	1.7k
Lee P. Skrupky United States	18	678 1.2×	310 0.7×	488 1.2×	186 0.5×	184 0.8×	43	1.4k
Pierre-François Laterre Belgium	18	575 1.0×	241 0.6×	275 0.7×	366 1.0×	116 0.5×	35	1.4k

Countries citing papers authored by Tamás Szakmány

Since Specialization

Citations

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

Fields of papers citing papers by Tamás Szakmány

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tamás Szakmány

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

All Works

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20 of 20 papers shown

Villar, Jesús, Jesús M. González‐Martín, Cristina Fernández, et al.. (2025). Early Prediction of ICU Mortality in Patients with Acute Hypoxemic Respiratory Failure Using Machine Learning: The MEMORIAL Study. Journal of Clinical Medicine. 14(5). 1711–1711.

Wu, Daniel, Amy Dzierba, Enyo Ablordeppey, et al.. (2025). The Definition of the Intensivist in the Era of Global Healthcare: 2024 Consensus Statement From the Society of Critical Care Medicine Defining Intensivist Task Force. Critical Care Medicine. 53(3). e548–e554. 1 indexed citations

Boyle, Andrew, Kiran Reddy, J. Michael Conlon, et al.. (2025). Evaluation of Plasma Biomarkers to Understand the Biology and Heterogeneity of Treatment Effect in Lower Tidal Volume Ventilation Facilitated by Extracorporeal CO2 Removal in Acute Hypoxemic Respiratory Failure: A Secondary Analysis of the REST Trial. Critical Care Explorations. 7(4). e1246–e1246. 1 indexed citations

Szakmány, Tamás, Harriet Garlant, Tony Whitehouse, et al.. (2024). The ‘analysis of gene expression and biomarkers for point-of-care decision support in Sepsis‘ study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS discrimination. Frontiers in Immunology. 14. 1308530–1308530. 7 indexed citations

Tume, Lyvonne N., Victoria Waugh, Brian Johnston, et al.. (2024). Nurses' decision‐making around gastric residual volume measurement in UK adult intensive care: A four‐centre survey. Nursing in Critical Care. 29(5). 916–922. 1 indexed citations

Cheema, Huzaifa Ahmad, Abia Shahid, Mohammad Ebad Ur Rehman, et al.. (2023). Efficacy and safety of corticosteroids for the treatment of community-acquired pneumonia: A systematic review and meta-analysis of randomized controlled trials. Journal of Critical Care. 80. 154507–154507. 13 indexed citations

Cheema, Huzaifa Ahmad, Abia Shahid, Mohammad Ebad Ur Rehman, et al.. (2023). Awake Prone Positioning for Non-Intubated COVID-19 Patients with Acute Respiratory Failure: A Meta-Analysis of Randomised Controlled Trials. Journal of Clinical Medicine. 12(3). 926–926. 3 indexed citations

Brown, Kate, et al.. (2023). Procalcitonin Values Fail to Track the Presence of Secondary Bacterial Infections in COVID-19 ICU Patients. Antibiotics. 12(4). 709–709. 4 indexed citations

Henley, Josie, Lucy Brookes‐Howell, Philip Pallmann, et al.. (2023). Developing a model for decision-making around antibiotic prescribing for patients with COVID-19 pneumonia in acute NHS hospitals during the first wave of the COVID-19 pandemic: qualitative results from the Procalcitonin Evaluation of Antibiotic use in COVID-19 Hospitalised patients (PEACH Study). BMJ Open. 13(12). e077117–e077117. 1 indexed citations

10.

Szakmány, Tamás, et al.. (2021). Differences in Inflammatory Marker Kinetics between the First and Second Wave of COVID-19 Patients Admitted to the ICU: A Retrospective, Single-Center Study. Journal of Clinical Medicine. 10(15). 3290–3290. 7 indexed citations

11.

Silversides, Jonathan A., Lydia M. Emerson, Ian Bradbury, et al.. (2021). Feasibility of conservative fluid administration and deresuscitation compared with usual care in critical illness: the Role of Active Deresuscitation After Resuscitation-2 (RADAR-2) randomised clinical trial. Intensive Care Medicine. 48(2). 190–200. 31 indexed citations

12.

Pugh, Richard, Rowena Bailey, Tamás Szakmány, et al.. (2021). Long‐term trends in critical care admissions in Wales* ^*. Anaesthesia. 76(10). 1316–1325. 9 indexed citations

13.

Montgomery, Hugh, Luigi Camporota, Michael P. W. Grocott, et al.. (2020). COVID-19: UK frontline intensivists' emerging learning. Journal of the Intensive Care Society. 22(3). 211–213. 2 indexed citations

14.

Sakr, Yasser, Ulrich Jaschinski, Xavier Wittebole, et al.. (2018). Sepsis in Intensive Care Unit Patients: Worldwide Data From the Intensive Care over Nations Audit. Open Forum Infectious Diseases. 5(12). ofy313–ofy313. 306 indexed citations breakdown →

15.

Szakmány, Tamás, James Ditai, М. Yu. Кirov, et al.. (2017). In-hospital clinical outcomes after upper gastrointestinal surgery: Data from an international observational study. European Journal of Surgical Oncology. 43(12). 2324–2332. 6 indexed citations

16.

Márton, Sándor, et al.. (2005). Does transthoracic compared to transhiatal resection alter the early postoperative course of oesophagectomy?. Diseases of the Esophagus. 18(3). 155–159. 6 indexed citations

17.

Szakmány, Tamás, Ildikó Y. Tóth, Zsolt Kovács, et al.. (2005). Effects of volumetric vs. pressure-guided fluid therapy on postoperative inflammatory response: a prospective, randomized clinical trial. Intensive Care Medicine. 31(5). 656–663. 22 indexed citations

18.

Szakmány, Tamás, A Mikor, Tamás Leiner, & Zsolt Molnár. (2004). Fluid resuscitation with colloids of different molecular weight in septic shock. Critical Care. 8(Suppl 1). P130–P130. 1 indexed citations

19.

Szakmány, Tamás, et al.. (2003). Oral Presentations 232 - 291. Intensive Care Medicine. 29(S1). S64–S78. 3 indexed citations

20.

Molnár, Zsolt, et al.. (2003). Microalbuminuria does not reflect increased systemic capillary permeability in septic shock. Intensive Care Medicine. 29(3). 391–395. 30 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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