Don Johns

2.8k total citations · 1 hit paper
26 papers, 2.2k citations indexed

About

Don Johns is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Surgery. According to data from OpenAlex, Don Johns has authored 26 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Endocrinology, Diabetes and Metabolism, 7 papers in Molecular Biology and 5 papers in Surgery. Recurrent topics in Don Johns's work include Diabetes Treatment and Management (17 papers), Diabetes Management and Research (12 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (7 papers). Don Johns is often cited by papers focused on Diabetes Treatment and Management (17 papers), Diabetes Management and Research (12 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (7 papers). Don Johns collaborates with scholars based in United States, United Kingdom and Austria. Don Johns's co-authors include Robert G. Brodows, Meng H. Tan, Mario Widel, Luc F. Van Gaal, Michael J. Mihm, Robert J. Heine, Michael Trautmann, Justin Northrup, Andreas Festa and N. Bradly Glazer and has published in prestigious journals such as Blood, Annals of Internal Medicine and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Don Johns

25 papers receiving 2.1k citations

Hit Papers

Exenatide versus Insulin Glargine in Patients with Subopt... 2005 2026 2012 2019 2005 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Don Johns United States 18 1.9k 1.0k 711 350 165 26 2.2k
Freddy G. Eliaschewitz Brazil 17 1.6k 0.8× 735 0.7× 640 0.9× 386 1.1× 174 1.1× 43 2.1k
Marcus Hompesch United States 27 1.6k 0.9× 627 0.6× 966 1.4× 241 0.7× 223 1.4× 82 2.3k
Mark O’Neill United Kingdom 9 2.0k 1.0× 1.3k 1.3× 807 1.1× 228 0.7× 300 1.8× 13 2.6k
Helle Linnebjerg United States 24 1.3k 0.7× 425 0.4× 859 1.2× 196 0.6× 123 0.7× 60 1.7k
Caterina Lamanna Italy 19 1.4k 0.7× 870 0.9× 413 0.6× 196 0.6× 134 0.8× 29 1.9k
Søren S. Lund Germany 22 1.5k 0.8× 659 0.7× 635 0.9× 172 0.5× 245 1.5× 50 1.9k
Gregory T. Golm United States 26 2.3k 1.2× 1.0k 1.0× 800 1.1× 367 1.0× 108 0.7× 52 2.5k
Rita Patwardhan United States 12 1.3k 0.7× 1.2k 1.2× 264 0.4× 184 0.5× 224 1.4× 14 2.0k
Thomas Meinicke Germany 22 2.5k 1.3× 1.0k 1.0× 971 1.4× 382 1.1× 147 0.9× 35 2.8k
Ross Bray United States 11 1.5k 0.8× 668 0.7× 446 0.6× 526 1.5× 473 2.9× 21 1.9k

Countries citing papers authored by Don Johns

Since Specialization
Citations

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

Fields of papers citing papers by Don Johns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Don Johns

This figure shows the co-authorship network connecting the top 25 collaborators of Don Johns. A scholar is included among the top collaborators of Don Johns 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 Don Johns. Don Johns 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.
Mader, Julia K., Leslie C. Lilly, Felix Aberer, et al.. (2018). Improved glycaemic control and treatment satisfaction with a simple wearable 3‐day insulin delivery device among people with Type 2 diabetes. Diabetic Medicine. 35(10). 1448–1456. 17 indexed citations
2.
Johns, Don. (2017). The efficacy of combination therapy with varenicline and bupropion for smoking cessation. Annals of Oncology. 28. ii6–ii7. 3 indexed citations
3.
McCall, Anthony L., Daniel J. Cox, Robert G. Brodows, et al.. (2009). Reduced Daily Risk of Glycemic Variability: Comparison of Exenatide with Insulin Glargine. Diabetes Technology & Therapeutics. 11(6). 339–344. 37 indexed citations
4.
Gao, Yan, Kun‐Ho Yoon, Lee‐Ming Chuang, et al.. (2008). Efficacy and safety of exenatide in patients of Asian descent with type 2 diabetes inadequately controlled with metformin or metformin and a sulphonylurea. Diabetes Research and Clinical Practice. 83(1). 69–76. 75 indexed citations
7.
Charbonnel, B, Michael Roden, Richard Urquhart, et al.. (2005). Pioglitazone elicits long-term improvements in insulin sensitivity in patients with type 2 diabetes: comparisons with gliclazide-based regimens. Diabetologia. 48(3). 553–560. 20 indexed citations
8.
Roden, Michael, Markku Laakso, Don Johns, et al.. (2005). Long‐term effects of pioglitazone and metformin on insulin sensitivity in patients with Type 2 diabetes mellitus. Diabetic Medicine. 22(8). 1101–1106. 17 indexed citations
10.
Heine, Robert J., Luc F. Van Gaal, Don Johns, et al.. (2005). Exenatide versus Insulin Glargine in Patients with Suboptimally Controlled Type 2 Diabetes. Annals of Internal Medicine. 143(8). 559–569. 637 indexed citations breakdown →
11.
Tan, Meng H., et al.. (2004). Pioglitazone as monotherapy or in combination with sulfonylurea or metformin enhances insulin sensitivity (HOMA-S or QUICKI) in patients with type 2 diabetes. Current Medical Research and Opinion. 20(5). 723–728. 22 indexed citations
12.
Tan, Meng H., Don Johns, Guillermo González-Gálvez, et al.. (2004). Effects of pioglitazone and glimepiride on glycemic control and insulin sensitivity in Mexican patients with type 2 diabetes mellitus: A multicenter, randomized, double-blind, parallel-group trial. Clinical Therapeutics. 26(5). 680–693. 51 indexed citations
13.
Tan, Meng H., Don Johns, Jorma Strand, et al.. (2004). Sustained effects of pioglitazone vs. glibenclamide on insulin sensitivity, glycaemic control, and lipid profiles in patients with Type 2 diabetes. Diabetic Medicine. 21(8). 859–866. 58 indexed citations
14.
Pávó, Imre, György Jermendy, Tamás Várkonyi, et al.. (2003). Effect of Pioglitazone Compared with Metformin on Glycemic Control and Indicators of Insulin Sensitivity in Recently Diagnosed Patients with Type 2 Diabetes. The Journal of Clinical Endocrinology & Metabolism. 88(4). 1637–1645. 135 indexed citations
16.
Wasilewski, Margaret, Don Johns, & Gregory D. Sides. (1999). Five-day dirithromycin therapy is as effective as seven-day erythromycin therapy for acute exacerbations of chronic bronchitis. Journal of Antimicrobial Chemotherapy. 43(4). 541–548. 13 indexed citations
17.
Gooch, W M, et al.. (1999). Loracarbef versus clarithromyin in children with acute otitis media with effusion. Clinical Therapeutics. 21(4). 711–722. 7 indexed citations
18.
Bandak, Stephen I., et al.. (1999). Cefaclor advanced formulation 750 mg twice daily versus clarithromycin 500 mg twice daily in the treatment of acute maxillary sinusitis. Current Therapeutic Research. 60(4). 185–194. 1 indexed citations
19.
20.
Watkins, Michael L., et al.. (1997). Double-masked, randomized, parallel-group comparison of cefaclor af and cefaclor in the treatment of acute bacterial sinusitis. Current Therapeutic Research. 58(4). 227–239. 1 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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