Steve Baín

1.8k total citations
51 papers, 1.1k citations indexed

About

Steve Baín is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Molecular Biology. According to data from OpenAlex, Steve Baín has authored 51 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Endocrinology, Diabetes and Metabolism, 19 papers in Surgery and 8 papers in Molecular Biology. Recurrent topics in Steve Baín's work include Diabetes Treatment and Management (15 papers), Diabetes Management and Research (13 papers) and Pancreatic function and diabetes (12 papers). Steve Baín is often cited by papers focused on Diabetes Treatment and Management (15 papers), Diabetes Management and Research (13 papers) and Pancreatic function and diabetes (12 papers). Steve Baín collaborates with scholars based in United Kingdom, United States and Denmark. Steve Baín's co-authors include Jeffrey W. Stephens, Jiten Vora, Anthony Barnett, Sarah L. Prior, Torsten Christensen, John A. Todd, A. DeHennis, A H Barnett, L E Pritchard and Thomas Först and has published in prestigious journals such as Nature Genetics, SHILAP Revista de lepidopterología and Diabetes Care.

In The Last Decade

Steve Baín

49 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Steve Baín United Kingdom 20 548 374 341 294 115 51 1.1k
Moufida Ben Nasr United States 19 479 0.9× 369 1.0× 485 1.4× 293 1.0× 105 0.9× 38 1.2k
Shinsuke Noso Japan 20 437 0.8× 501 1.3× 433 1.3× 309 1.1× 104 0.9× 66 1.2k
Hasan Altunbaş Türkiye 20 525 1.0× 114 0.3× 349 1.0× 201 0.7× 113 1.0× 49 1.1k
Vadim V. Klimontov Russia 15 388 0.7× 181 0.5× 220 0.6× 170 0.6× 67 0.6× 101 799
Pierre-Jean Guillausseau France 19 669 1.2× 270 0.7× 362 1.1× 284 1.0× 149 1.3× 49 1.3k
Leonid Katz United States 12 550 1.0× 169 0.5× 413 1.2× 773 2.6× 60 0.5× 18 1.7k
Mitsutoshi Oguri Japan 21 166 0.3× 269 0.7× 204 0.6× 436 1.5× 139 1.2× 93 1.2k
M. Rema India 22 765 1.4× 185 0.5× 121 0.4× 168 0.6× 154 1.3× 30 1.9k
Dong Jun Lim South Korea 22 853 1.6× 109 0.3× 501 1.5× 222 0.8× 73 0.6× 67 1.4k
Wenjia Yang China 18 642 1.2× 67 0.2× 240 0.7× 310 1.1× 137 1.2× 59 1.1k

Countries citing papers authored by Steve Baín

Since Specialization
Citations

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

Fields of papers citing papers by Steve Baín

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Steve Baín

This figure shows the co-authorship network connecting the top 25 collaborators of Steve Baín. A scholar is included among the top collaborators of Steve Baín 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 Steve Baín. Steve Baín 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.
2.
Connolly, Derek, et al.. (2023). Assessing opinion on lower LDL-cholesterol lowering, and the role of newer lipid-reducing treatment options. British Journal of Cardiology. 30(2). 14–14. 1 indexed citations
3.
4.
Yamada, T., Nobuhiro Shojima, Toshimasa Yamauchi, et al.. (2019). Clinical care and other categories posters: Incretin therapies. Diabetic Medicine. 36(S1). 134–135. 1 indexed citations
5.
Baín, Steve, Debbie Hicks, Dipesh Patel, et al.. (2019). SGLT2 Inhibitors: Cardiovascular Benefits Beyond HbA1c—Translating Evidence into Practice. Diabetes Therapy. 10(5). 1595–1622. 37 indexed citations
6.
Davies, Melanie J., Steve Baín, G. Charpentier, et al.. (2019). A Randomized Controlled, Treat-to-Target Study Evaluating the Efficacy and Safety of Insulin Glargine 300 U/mL (Gla-300) Administered Using Either Device-Supported or Routine Titration in People With Type 2 Diabetes. Journal of Diabetes Science and Technology. 13(5). 881–889. 23 indexed citations
7.
Baín, Steve, Michael Feher, David Russell‐Jones, & Kamlesh Khunti. (2016). Management of type 2 diabetes: t he current situation and key opportunities to improve care in the UK. Diabetes Obesity and Metabolism. 18(12). 1157–1166. 21 indexed citations
8.
Vora, Jiten, et al.. (2014). Insulin Degludec Versus Insulin Glargine in Type 1 and Type 2 Diabetes Mellitus: A Meta-Analysis of Endpoints in Phase 3a Trials. Diabetes Therapy. 5(2). 435–446. 76 indexed citations
9.
Gordon, Jason, Marc Evans, Phil McEwan, Steve Baín, & Jiten Vora. (2013). Evaluation of Insulin Use and Value for Money in Type 2 Diabetes in the United Kingdom. Diabetes Therapy. 4(1). 51–66. 7 indexed citations
10.
Birkeland, K. I., Itamar Raz, S Gough, et al.. (2011). Insulin degludec in a flexible daily dosing regimen provides similar glycaemic control without increasing rates of hypoglycaemia compared to dosing the same time daily in type 2 diabetes. Diabetologia. 54. 6 indexed citations
11.
Atkin, Stephen L., Steve Baín, S Gough, et al.. (2011). Insulin degludec does not compromise efficacy or safety when given in a flexible once-daily dosing regimen compared to insulin glargine once daily at the same time each day in type 2 diabetes. Diabetologia. 54. 8 indexed citations
12.
Jones, D. A., Sarah L. Prior, Tricia S. Tang, et al.. (2010). Association between the rs4880 superoxide dismutase 2 (C>T) gene variant and coronary heart disease in diabetes mellitus. Diabetes Research and Clinical Practice. 90(2). 196–201. 35 indexed citations
13.
Bracken, Richard M., Daniel J. West, Jeffrey W. Stephens, et al.. (2010). Impact of pre‐exercise rapid‐acting insulin reductions on ketogenesis following running in Type 1 diabetes. Diabetic Medicine. 28(2). 218–222. 26 indexed citations
14.
Stephens, Jeffrey W., et al.. (2010). The incretin system in the management of type 2 diabetes mellitus. Clinical Medicine. 10(5). 491–495. 1 indexed citations
15.
Price, David E., et al.. (2009). Clinical experience with exenatide in a routine secondary care diabetes clinic. Primary care diabetes. 4(1). 57–60. 1 indexed citations
16.
Roudier, Martine P., et al.. (2005). Evaluation of pain in breast and prostate cancer bone metastasis rat models. Cancer Research. 65. 684–684. 1 indexed citations
17.
Patel, Ashok, William R. Scott, Penny Lympany, et al.. (2004). The TGF‐β1 gene codon 10 polymorphism contributes to the genetic predisposition to nephropathy in Type 1 diabetes. Diabetic Medicine. 22(1). 69–73. 31 indexed citations
18.
Patel, Ashok, et al.. (2003). Nitric oxide synthase gene polymorphisms and diabetic nephropathy. Diabetologia. 46(3). 426–428. 44 indexed citations
19.
Davies, June, James Copeman, Heather J. Cordell, et al.. (1995). LINKAGE MAPPING OF TYPE-1 DIABETES. The American Journal of Human Genetics. 57. 1–1. 72 indexed citations
20.
Baín, Steve, Jan‐Bas Prins, Catherine M. Hearne, et al.. (1992). Insulin gene region–encoded susceptibility to type 1 diabetes is not restricted to HLA–DR4–positive individuals. Nature Genetics. 2(3). 212–215. 103 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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