Paul S. García

3.6k total citations · 1 hit paper
94 papers, 2.4k citations indexed

About

Paul S. García is a scholar working on Anesthesiology and Pain Medicine, Critical Care and Intensive Care Medicine and Cognitive Neuroscience. According to data from OpenAlex, Paul S. García has authored 94 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Anesthesiology and Pain Medicine, 36 papers in Critical Care and Intensive Care Medicine and 34 papers in Cognitive Neuroscience. Recurrent topics in Paul S. García's work include Anesthesia and Sedative Agents (52 papers), Intensive Care Unit Cognitive Disorders (36 papers) and Anesthesia and Neurotoxicity Research (31 papers). Paul S. García is often cited by papers focused on Anesthesia and Sedative Agents (52 papers), Intensive Care Unit Cognitive Disorders (36 papers) and Anesthesia and Neurotoxicity Research (31 papers). Paul S. García collaborates with scholars based in United States, Germany and New Zealand. Paul S. García's co-authors include Matthias Kreuzer, Andrew Jenkins, Darren Hight, Jamie Sleigh, Gerhard Schneider, Anna Woodbury, Vivek K. Moitra, Robert A. Whittington, Yuanjia Wang and Chen Chen and has published in prestigious journals such as PLoS ONE, NeuroImage and Journal of Neurophysiology.

In The Last Decade

Paul S. García

87 papers receiving 2.4k citations

Hit Papers

Association of Delirium With Long-term Cognitive Decline 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul S. García United States 27 960 914 711 612 406 94 2.4k
Kazuyoshi Hirota Japan 28 659 0.7× 339 0.4× 340 0.5× 532 0.9× 544 1.3× 294 3.2k
Mu‐Huo Ji China 35 384 0.4× 1.1k 1.3× 1.0k 1.4× 169 0.3× 390 1.0× 141 3.5k
Joseph F. Antognini United States 32 1.4k 1.4× 323 0.4× 782 1.1× 519 0.8× 945 2.3× 133 3.2k
Peter A. Goldstein United States 34 354 0.4× 346 0.4× 754 1.1× 662 1.1× 1.8k 4.3× 80 4.2k
Luc J. Teppema Netherlands 35 1.1k 1.2× 227 0.2× 170 0.2× 550 0.9× 498 1.2× 81 4.1k
Paul J. Manberg United States 26 2.8k 3.0× 1.1k 1.2× 1.4k 2.0× 498 0.8× 1.0k 2.5× 52 4.8k
E. Tassonyi Switzerland 26 1.2k 1.2× 411 0.4× 542 0.8× 110 0.2× 189 0.5× 94 2.0k
Malin Jonsson Fagerlund Sweden 24 611 0.6× 548 0.6× 438 0.6× 76 0.1× 127 0.3× 82 2.0k
Benno Rehberg Germany 22 630 0.7× 147 0.2× 248 0.3× 314 0.5× 298 0.7× 72 1.4k
Diederik Nieuwenhuijs Netherlands 16 560 0.6× 197 0.2× 152 0.2× 220 0.4× 158 0.4× 23 1.4k

Countries citing papers authored by Paul S. García

Since Specialization
Citations

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

Fields of papers citing papers by Paul S. García

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul S. García. 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 Paul S. García. The network helps show where Paul S. García may publish in the future.

Co-authorship network of co-authors of Paul S. García

This figure shows the co-authorship network connecting the top 25 collaborators of Paul S. García. A scholar is included among the top collaborators of Paul S. García 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 Paul S. García. Paul S. García 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.
Chaikittisilpa, Nophanan, Indranil Chakraborty, Tumul Chowdhury, et al.. (2025). Perspectives on Analgesia for Craniotomy: A Survey of Anesthetic Practices. Journal of Neurosurgical Anesthesiology. 37(3). 319–324.
4.
Kreuzer, Matthias, Mercé Agustí, Sebastián Jaramillo, et al.. (2025). Cortical, subcortical, brainstem and autonomic responses to nociception under total intravenous anesthesia. Journal of Clinical Anesthesia. 103. 111825–111825.
6.
García, Paul S., et al.. (2024). Intraoperative Burst Suppression by Analysis of Raw Electroencephalogram Postoperative Delirium in Older Adults Undergoing Spine Surgery: A Retrospective Cohort Study. Journal of Neurosurgical Anesthesiology. 38(1). 68–75. 4 indexed citations
7.
Zinn, Sebastian, Laurent M. Willems, Sebastian Harder, et al.. (2024). Parametrization of the dying brain: A case report from ICU bed-side EEG monitoring. NeuroImage. 305. 120980–120980. 1 indexed citations
8.
9.
Zinn, Sebastian, Stefanie Pilge, Paul S. García, et al.. (2024). Aperiodic component of the electroencephalogram power spectrum reflects the hypnotic level of anaesthesia. British Journal of Anaesthesia. 134(2). 392–401. 1 indexed citations
10.
Rajan, Shobana, et al.. (2024). Alternate Electrode Placements to Facilitate Frontal Electroencephalography Monitoring in Anesthetized and Critically Ill Patients. Journal of Neurosurgical Anesthesiology. 37(1). 47–54. 1 indexed citations
11.
Schneider, Gerhard, et al.. (2023). Predictors of Low Risk for Delirium during Anesthesia Emergence. Anesthesiology. 139(6). 757–768. 10 indexed citations
12.
García, Paul S., Matthias Kreuzer, Darren Hight, & James W. Sleigh. (2021). Effects of noxious stimulation on the electroencephalogram during general anaesthesia: a narrative review and approach to analgesic titration. British Journal of Anaesthesia. 126(2). 445–457. 59 indexed citations
13.
Chan, Matthew T.V., Traci L. Hedrick, Talmage D. Egan, et al.. (2019). American Society for Enhanced Recovery and Perioperative Quality Initiative Joint Consensus Statement on the Role of Neuromonitoring in Perioperative Outcomes: Electroencephalography. Anesthesia & Analgesia. 130(5). 1278–1291. 77 indexed citations
14.
Bichler, Edyta K., et al.. (2017). The Influence of Regional Distribution and Pharmacologic Specificity of GABAAR Subtype Expression on Anesthesia and Emergence. Frontiers in Systems Neuroscience. 11. 58–58. 18 indexed citations
15.
Hight, Darren, Logan J. Voss, Paul S. García, & Jamie Sleigh. (2017). Changes in Alpha Frequency and Power of the Electroencephalogram during Volatile-Based General Anesthesia. Frontiers in Systems Neuroscience. 11. 36–36. 37 indexed citations
16.
Kreuzer, Matthias, et al.. (2017). Anesthetic Management of a Patient With Multiple Previous Episodes of Postanesthesia Care Unit Delirium. A & A Case Reports. 8(12). 311–315. 12 indexed citations
17.
Safavynia, Seyed A., Glenda L. Keating, Jonathan A. Fidler, et al.. (2016). Effects of γ-Aminobutyric Acid Type A Receptor Modulation by Flumazenil on Emergence from General Anesthesia. Anesthesiology. 125(1). 147–158. 36 indexed citations
18.
Woodbury, Anna, et al.. (2015). Complementary and alternative medicine therapies for the anesthesiologist and pain practitioner: a narrative review. Canadian Journal of Anesthesia/Journal canadien d anesthésie. 63(1). 69–85. 8 indexed citations
19.
Rye, David B., Donald L. Bliwise, Kathy P. Parker, et al.. (2012). Modulation of Vigilance in the Primary Hypersomnias by Endogenous Enhancement of GABA A Receptors. Science Translational Medicine. 4(161). 161ra151–161ra151. 120 indexed citations
20.
García, Paul S., Amitabh Gulati, & Jerrold H. Levy. (2010). The role of thrombin and protease-activated receptors in pain mechanisms. Thrombosis and Haemostasis. 103(6). 1145–1151. 26 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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