James M. Peacock

2.5k total citations
49 papers, 2.0k citations indexed

About

James M. Peacock is a scholar working on Cardiology and Cardiovascular Medicine, Epidemiology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, James M. Peacock has authored 49 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Cardiology and Cardiovascular Medicine, 14 papers in Epidemiology and 14 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in James M. Peacock's work include Diabetes, Cardiovascular Risks, and Lipoproteins (11 papers), Adipokines, Inflammation, and Metabolic Diseases (8 papers) and Lipid metabolism and disorders (7 papers). James M. Peacock is often cited by papers focused on Diabetes, Cardiovascular Risks, and Lipoproteins (11 papers), Adipokines, Inflammation, and Metabolic Diseases (8 papers) and Lipid metabolism and disorders (7 papers). James M. Peacock collaborates with scholars based in United States, Spain and Switzerland. James M. Peacock's co-authors include Aaron R. Folsom, Donna K. Arnett, John H. Eckfeldt, José M. Ordovás, Michael Y. Tsai, Michael A. Province, Robert J. Straka, A.R. Folsom, Eric Boerwinkle and James E. Hixson and has published in prestigious journals such as Circulation, Diabetes Care and Stroke.

In The Last Decade

James M. Peacock

45 papers receiving 1.9k citations

Peers

James M. Peacock
Else‐Marie Bladbjerg Denmark
Johannes Pleiner Austria
James Ehrlich United States
Shunroku Baba Japan
Jennifer K. Pai United States
K. C. B. Tan Hong Kong
Daniel Gordin Finland
Chan‐Hee Jung South Korea
Erdinç Çakır Türkiye
Di̇lek Gogas Yavuz Türkiye
Else‐Marie Bladbjerg Denmark
James M. Peacock
Citations per year, relative to James M. Peacock James M. Peacock (= 1×) peers Else‐Marie Bladbjerg

Countries citing papers authored by James M. Peacock

Since Specialization
Citations

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

Fields of papers citing papers by James M. Peacock

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James M. Peacock. 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 James M. Peacock. The network helps show where James M. Peacock may publish in the future.

Co-authorship network of co-authors of James M. Peacock

This figure shows the co-authorship network connecting the top 25 collaborators of James M. Peacock. A scholar is included among the top collaborators of James M. Peacock 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 James M. Peacock. James M. Peacock 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.
Piccini, Jonathan P., Elaine M. Hylek, Rahul Kanwar, et al.. (2024). Performance of Atrial Fibrillation Burden Trends for Stroke Risk Stratification. Circulation Arrhythmia and Electrophysiology. 17(11). e012394–e012394. 2 indexed citations
2.
Peacock, James M., Lawrence C. Johnson, Elaine M. Hylek, et al.. (2024). Using Atrial Fibrillation Burden Trends and Machine Learning to Predict Near-Term Risk of Cardiovascular Hospitalization. Circulation Arrhythmia and Electrophysiology. 17(11). e012991–e012991. 2 indexed citations
3.
4.
Asaithambi, Ganesh, Xin Tong, Mary G. George, et al.. (2014). Acute Stroke Reperfusion Therapy Trends in the Expanded Treatment Window Era. Journal of Stroke and Cerebrovascular Diseases. 23(9). 2316–2321. 21 indexed citations
5.
Tekle, Wondwossen, Saqib Chaudhry, Ameer E Hassan, et al.. (2012). Utilization of Intravenous Thrombolysis in 3–4.5 Hours: Analysis of the Minnesota Stroke Registry. Cerebrovascular Diseases. 34(5-6). 400–405. 9 indexed citations
6.
Prizment, Anna E., Myron D. Gross, Laura J. Rasmussen‐Torvik, James M. Peacock, & Kristin E. Anderson. (2011). Genes Related to Diabetes May Be Associated With Pancreatic Cancer in a Population-Based Case-Control Study in Minnesota. Pancreas. 41(1). 50–53. 19 indexed citations
7.
Peacock, James M., Hong H. Keo, Sue Duval, et al.. (2011). The incidence and health economic burden of ischemic amputation in Minnesota, 2005-2008.. PubMed. 8(6). A141–A141. 62 indexed citations
8.
Steffen, Lyn M., Mary Cushman, James M. Peacock, et al.. (2009). Metabolic syndrome and risk of venous thromboembolism: Longitudinal Investigation of Thromboembolism Etiology. Journal of Thrombosis and Haemostasis. 7(5). 746–751. 97 indexed citations
9.
Warodomwichit, Daruneewan, Jian Shen, Donna K. Arnett, et al.. (2009). ADIPOQ Polymorphisms, Monounsaturated Fatty Acids, and Obesity Risk: The GOLDN Study. Obesity. 17(3). 510–517. 75 indexed citations
10.
Smith, Jennifer A., Donna K. Arnett, Reagan Kelly, et al.. (2008). The genetic architecture of fasting plasma triglyceride response to fenofibrate treatment. European Journal of Human Genetics. 16(5). 603–613. 29 indexed citations
11.
Shen, Jian, Donna K. Arnett, Pablo Pérez‐Martínez, et al.. (2008). The effect of IL6-174C/G polymorphism on postprandial triglyceride metabolism in the GOLDN study*. Journal of Lipid Research. 49(8). 1839–1845. 20 indexed citations
12.
Folsom, Aaron R., James M. Peacock, Ellen W. Demerath, & Eric Boerwinkle. (2008). Variation in ANGPTL4 and risk of coronary heart disease: the Atherosclerosis Risk in Communities Study. Metabolism. 57(11). 1591–1596. 56 indexed citations
13.
Folsom, Aaron R., James M. Peacock, & Eric Boerwinkle. (2008). Variation in PCSK9, low LDL cholesterol, and risk of peripheral arterial disease. Atherosclerosis. 202(1). 211–215. 33 indexed citations
14.
Shen, Jian, Donna K. Arnett, James M. Peacock, et al.. (2007). Interleukin1β Genetic Polymorphisms Interact with Polyunsaturated Fatty Acids to Modulate Risk of the Metabolic Syndrome , ,3. Journal of Nutrition. 137(8). 1846–1851. 51 indexed citations
15.
Folsom, Aaron R., James M. Peacock, & Eric Boerwinkle. (2007). Sequence Variation in Proprotein Convertase Subtilisin/Kexin Type 9 Serine Protease Gene, Low LDL Cholesterol, and Cancer Incidence. Cancer Epidemiology Biomarkers & Prevention. 16(11). 2455–2458. 25 indexed citations
16.
Tsai, Michael Y., Naomi Q. Hanson, Robert J. Straka, et al.. (2005). Effect of influenza vaccine on markers of inflammation and lipid profile. Journal of Laboratory and Clinical Medicine. 145(6). 323–327. 78 indexed citations
17.
Folsom, A.R., James S. Pankow, Russell P. Tracy, et al.. (2001). Association of C-reactive protein with markers of prevalent atherosclerotic disease. The American Journal of Cardiology. 88(2). 112–117. 201 indexed citations
18.
Peacock, James M., A.R. Folsom, David S. Knopman, et al.. (2000). Dietary antioxidant intake and cognitive performance in middle-aged adults. Public Health Nutrition. 3(3). 337–343. 32 indexed citations
19.
Peacock, James M., Aaron R. Folsom, David S. Knopman, et al.. (1999). Association of Nonsteroidal Anti-Inflammatory Drugs and Aspirinwith Cognitive Performance inMiddle-Aged Adults. Neuroepidemiology. 18(3). 134–143. 9 indexed citations
20.
Peacock, James M., Aaron R. Folsom, Donna K. Arnett, John H. Eckfeldt, & Moysés Szklo. (1999). Relationship of Serum and Dietary Magnesium to Incident Hypertension. Annals of Epidemiology. 9(3). 159–165. 91 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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