Neesh Pannu

61.0k total citations · 6 hit papers
185 papers, 41.8k citations indexed

About

Neesh Pannu is a scholar working on Nephrology, Molecular Biology and Surgery. According to data from OpenAlex, Neesh Pannu has authored 185 papers receiving a total of 41.8k indexed citations (citations by other indexed papers that have themselves been cited), including 112 papers in Nephrology, 31 papers in Molecular Biology and 30 papers in Surgery. Recurrent topics in Neesh Pannu's work include Acute Kidney Injury Research (79 papers), Chronic Kidney Disease and Diabetes (46 papers) and Dialysis and Renal Disease Management (43 papers). Neesh Pannu is often cited by papers focused on Acute Kidney Injury Research (79 papers), Chronic Kidney Disease and Diabetes (46 papers) and Dialysis and Renal Disease Management (43 papers). Neesh Pannu collaborates with scholars based in Canada, United States and Netherlands. Neesh Pannu's co-authors include Randy J. Read, Garib N. Murshudov, Alexei A. Vagin, Martyn Winn, Paul D. Adams, Axel T. Brünger, Ralf W. Grosse‐Kunstleve, Piet Gros, Michaël Nilges and Jiansheng Jiang and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and The Lancet.

In The Last Decade

Neesh Pannu

172 papers receiving 41.4k citations

Hit Papers

Crystallography & NMR System: A New Software Suite fo... 1998 2026 2007 2016 1998 2011 2011 2013 2012 4.0k 8.0k 12.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Neesh Pannu Canada 51 25.5k 8.9k 5.4k 3.9k 3.0k 185 41.8k
David S. Wishart Canada 112 48.3k 1.9× 4.9k 0.5× 644 0.1× 5.0k 1.3× 2.4k 0.8× 553 75.7k
Piet Gros Netherlands 75 19.8k 0.8× 4.5k 0.5× 595 0.1× 3.8k 1.0× 2.2k 0.7× 251 34.7k
Richard A. Lerner United States 95 22.2k 0.9× 1.9k 0.2× 411 0.1× 2.7k 0.7× 1.9k 0.6× 417 38.4k
Mark B. Pepys United Kingdom 79 12.8k 0.5× 946 0.1× 1.7k 0.3× 2.2k 0.6× 1.7k 0.6× 251 26.2k
Jeremy K. Nicholson United Kingdom 130 54.2k 2.1× 829 0.1× 831 0.2× 3.7k 0.9× 1.4k 0.5× 776 76.1k
Thomas E. Ferrin United States 43 35.6k 1.4× 5.5k 0.6× 159 0.0× 4.8k 1.2× 3.9k 1.3× 93 55.6k
Carl Nathan United States 115 23.9k 0.9× 1.4k 0.2× 747 0.1× 2.9k 0.8× 2.8k 0.9× 318 73.0k
Raymond A. Dwek United Kingdom 110 29.4k 1.2× 1.5k 0.2× 402 0.1× 1.2k 0.3× 4.7k 1.6× 564 46.1k
Conrad C. Huang United States 31 31.3k 1.2× 4.9k 0.5× 138 0.0× 4.4k 1.1× 3.6k 1.2× 48 49.3k
Michael Kuhn Germany 55 23.9k 0.9× 1.6k 0.2× 196 0.0× 2.9k 0.7× 1.6k 0.5× 153 39.2k

Countries citing papers authored by Neesh Pannu

Since Specialization
Citations

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

Fields of papers citing papers by Neesh Pannu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Neesh Pannu

This figure shows the co-authorship network connecting the top 25 collaborators of Neesh Pannu. A scholar is included among the top collaborators of Neesh Pannu 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 Neesh Pannu. Neesh Pannu 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.
MacRae, Jennifer M., Sandra M. Dumanski, Meghan J. Elliott, et al.. (2024). Sex and gender differences in health-related quality of life in individuals treated with incremental and conventional hemodialysis. Clinical Kidney Journal. 17(10). sfae273–sfae273. 4 indexed citations
5.
Acharya, Dilaram, Tyrone G. Harrison, Nusrat Shommu, et al.. (2024). Nephroprotective Effects of Cilastatin in People at Risk of Acute Kidney Injury: A Systematic Review and Meta-analysis. Kidney Medicine. 6(12). 100913–100913. 1 indexed citations
6.
Klarenbach, Scott, David Collister, Natasha Wiebe, et al.. (2024). Association of Glomerular Filtration Rate Decline With Clinical Outcomes in a Population With Type 2 Diabetes. Canadian Journal of Kidney Health and Disease. 11. 1045210981–1045210981.
7.
James, Matthew T., Elijah Dixon, Indraneel Datta, et al.. (2024). Stepped-Wedge Trial of Decision Support for Acute Kidney Injury on Surgical Units. Kidney International Reports. 9(10). 2996–3005.
8.
Watson, Kaitlyn E., Maoliosa Donald, Matthew T. James, et al.. (2023). Managing ‘sick days’ in patients with chronic conditions: An exploration of patient and healthcare provider experiences. Health Expectations. 26(4). 1746–1756. 4 indexed citations
9.
Ravani, Pietro, et al.. (2023). Variations in Incidence and Prognosis of Stage 4 CKD Among Adults Identified Using Different Algorithms: A Population-Based Cohort Study. American Journal of Kidney Diseases. 83(5). 578–587.e1.
10.
Willemse, Joost, Patrick Voskamp, Xinmeng Li, et al.. (2021). Ectopic positioning of the cell division plane is associated with single amino acid substitutions in the FtsZ-recruiting SsgB in Streptomyces. Open Biology. 11(2). 200409–200409. 6 indexed citations
11.
James, Matthew T., Bryan Har, Peter Faris, et al.. (2019). Clinical Decision Support to Reduce Contrast-Induced Kidney Injury During Cardiac Catheterization: Design of a Randomized Stepped-Wedge Trial. Canadian Journal of Cardiology. 35(9). 1124–1133. 12 indexed citations
12.
Afanasyev, Pavel, Raimond B. G. Ravelli, Rishi Matadeen, et al.. (2017). Single-particle cryo-EM using alignment by classification (ABC): the structure ofLumbricus terrestrishaemoglobin. IUCrJ. 4(5). 678–694. 21 indexed citations
13.
Perkovic, Vlado, Jonathan C. Craig, Worawon Chailimpamontree, et al.. (2017). Action plan for optimizing the design of clinical trials in chronic kidney disease. Kidney International Supplements. 7(2). 138–144. 15 indexed citations
14.
Pannu, Neesh, Michelle M. Graham, Scott Klarenbach, et al.. (2016). A new model to predict acute kidney injury requiring renal replacement therapy after cardiac surgery. Canadian Medical Association Journal. 188(15). 1076–1083. 35 indexed citations
15.
James, Matthew T., Josée Bouchard, Julie Ho, et al.. (2013). Canadian Society of Nephrology Commentary on the 2012 KDIGO Clinical Practice Guideline for Acute Kidney Injury. American Journal of Kidney Diseases. 61(5). 673–685. 107 indexed citations
16.
Ravani, Pietro, Suetonia C. Palmer, Matthew J. Oliver, et al.. (2013). Associations between Hemodialysis Access Type and Clinical Outcomes. Journal of the American Society of Nephrology. 24(3). 465–473. 497 indexed citations breakdown →
18.
James, Matthew T., William A. Ghali, Merril L. Knudtson, et al.. (2011). Associations Between Acute Kidney Injury and Cardiovascular and Renal Outcomes After Coronary Angiography. Circulation. 123(4). 409–416. 280 indexed citations
19.
Tonelli, Marcello, Neesh Pannu, & Braden Manns. (2010). Oral Phosphate Binders in Patients with Kidney Failure. New England Journal of Medicine. 362(14). 1312–1324. 249 indexed citations
20.
Lameire, Norbert, Paul W. Eggers, Neesh Pannu, et al.. (2008). Epidemiology of Acute Kidney Injury. Clinical Journal of the American Society of Nephrology. 3(3). 881–886. 205 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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