Gaya Thanabalasingham

842 total citations
17 papers, 485 citations indexed

About

Gaya Thanabalasingham is a scholar working on Surgery, Endocrinology, Diabetes and Metabolism and Epidemiology. According to data from OpenAlex, Gaya Thanabalasingham has authored 17 papers receiving a total of 485 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Surgery, 8 papers in Endocrinology, Diabetes and Metabolism and 6 papers in Epidemiology. Recurrent topics in Gaya Thanabalasingham's work include Pancreatic function and diabetes (6 papers), Diabetes and associated disorders (5 papers) and Pituitary Gland Disorders and Treatments (3 papers). Gaya Thanabalasingham is often cited by papers focused on Pancreatic function and diabetes (6 papers), Diabetes and associated disorders (5 papers) and Pituitary Gland Disorders and Treatments (3 papers). Gaya Thanabalasingham collaborates with scholars based in United Kingdom, Poland and Denmark. Gaya Thanabalasingham's co-authors include Katharine R. Owen, Mark I. McCarthy, Andrew Farmer, Niki Karavitaki, John Wass, Helen Turner, Olaf Ansorge, Raluca Trifănescu, Sian Ellard and Polly J. Bingley and has published in prestigious journals such as PLoS ONE, Diabetes Care and Diabetes.

In The Last Decade

Gaya Thanabalasingham

15 papers receiving 466 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gaya Thanabalasingham United Kingdom 7 344 290 244 101 32 17 485
Subbiah Sridhar India 11 80 0.2× 115 0.4× 52 0.2× 45 0.4× 38 1.2× 35 302
Elisa Verrua Italy 15 158 0.5× 384 1.3× 102 0.4× 106 1.0× 5 0.2× 29 508
Anna Casteràs Spain 8 48 0.1× 219 0.8× 95 0.4× 144 1.4× 22 0.7× 21 380
Angelica Malinoc Germany 6 122 0.4× 98 0.3× 72 0.3× 63 0.6× 20 0.6× 8 240
Marina Pourafkari Canada 11 70 0.2× 100 0.3× 132 0.5× 98 1.0× 31 1.0× 25 326
Søren C. Tamer Denmark 7 246 0.7× 411 1.4× 124 0.5× 47 0.5× 5 0.2× 7 507
Karina Danilowicz Argentina 12 239 0.7× 448 1.5× 37 0.2× 57 0.6× 9 0.3× 43 608
Elvira De Martino Italy 10 264 0.8× 528 1.8× 46 0.2× 72 0.7× 10 0.3× 11 587
Qiao-Yi Chen United States 8 108 0.3× 155 0.5× 213 0.9× 43 0.4× 4 0.1× 14 375
Iulia Potorac Belgium 9 96 0.3× 162 0.6× 58 0.2× 36 0.4× 56 1.8× 19 303

Countries citing papers authored by Gaya Thanabalasingham

Since Specialization
Citations

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

Fields of papers citing papers by Gaya Thanabalasingham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gaya Thanabalasingham

This figure shows the co-authorship network connecting the top 25 collaborators of Gaya Thanabalasingham. A scholar is included among the top collaborators of Gaya Thanabalasingham 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 Gaya Thanabalasingham. Gaya Thanabalasingham is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
O’Callaghan, Christopher A., Jennifer J. Rayner, Gaya Thanabalasingham, et al.. (2025). Integrating and Defragmenting Multi-Specialty Care for People With Multiple Long-Term Conditions. British Journal of Hospital Medicine. 86(8). 1–11.
2.
Reschen, Michael E., Jennifer Rayner, Gaya Thanabalasingham, et al.. (2025). Development and evaluation of an integrated multispecialty clinic for people with multiple long-term conditions. Future Healthcare Journal. 12(2). 100235–100235.
3.
Diamond, Charlie, Nicole Eichert, Prashant Pandya, et al.. (2024). Quantitative Imaging Reveals Steatosis and Fibroinflammation in Multiple Organs in People With Type 2 Diabetes: A Real-World Study. Diabetes. 73(8). 1285–1299. 6 indexed citations
4.
Thanabalasingham, Gaya, et al.. (2024). Acceptability of and satisfaction with continuous glucose monitoring in pregnant women with type 2 diabetes mellitus: A service improvement project. Obstetric Medicine. 18(1). 12–17. 2 indexed citations
5.
Eichert, Nicole, Vashist Deelchand, Helena Thomaides‐Brears, et al.. (2022). High prevalence of multi-organ steatosis and fibroinflammation, identified by multi-parametric magnetic resonance imaging, in people with type 2 diabetes. Journal of Hepatology. 77. S433–S434. 1 indexed citations
6.
Rea, Rustam, Alistair Lumb, Garry D. Tan, et al.. (2020). Using data to improve the care of people with diabetes across Oxfordshire. Practical Diabetes. 37(1). 27–31. 2 indexed citations
7.
Thanabalasingham, Gaya, Brian Shine, Lai Mun Wang, et al.. (2014). Refractory hypercalcaemia secondary to parathyroid carcinoma: response to high-dose denosumab. European Journal of Endocrinology. 171(1). K1–K5. 35 indexed citations
8.
Thanabalasingham, Gaya & Katharine R. Owen. (2014). Type 2 diabetes in the young: why we should worry. Practical Diabetes. 31(6). 225–227. 3 indexed citations
9.
Thanabalasingham, Gaya, et al.. (2013). Acromegaly: Beyond surgery. Indian Journal of Endocrinology and Metabolism. 17(4). 563–563. 2 indexed citations
10.
McDonald, Timothy J., Jane McEneny, Ewan R. Pearson, et al.. (2012). Lipoprotein composition in HNF1A-MODY: Differentiating between HNF1A-MODY and Type 2 diabetes. Clinica Chimica Acta. 413(9-10). 927–932. 38 indexed citations
11.
Nowak, Natalia, Magdalena Szopa, Gaya Thanabalasingham, et al.. (2012). Cystatin C is not a good candidate biomarker for HNF1A-MODY. Acta Diabetologica. 50(5). 815–820. 10 indexed citations
12.
Gloyn, Anna L., Johan H. Faber, Daniel Malmodin, et al.. (2012). Metabolic Profiling in Maturity-Onset Diabetes of the Young (MODY) and Young Onset Type 2 Diabetes Fails to Detect Robust Urinary Biomarkers. PLoS ONE. 7(7). e40962–e40962. 16 indexed citations
13.
Thanabalasingham, Gaya, et al.. (2012). Biomarkers currently used for the diagnosis of maturity-onset diabetes of the young. Diabetes Management. 3(1). 71–80. 5 indexed citations
14.
Thanabalasingham, Gaya, Mary Selwood, Christina Dudley, et al.. (2012). Systematic Assessment of Etiology in Adults With a Clinical Diagnosis of Young-Onset Type 2 Diabetes Is a Successful Strategy for Identifying Maturity-Onset Diabetes of the Young. Diabetes Care. 35(6). 1206–1212. 136 indexed citations
15.
Owen, Katharine R., Gaya Thanabalasingham, T J James, et al.. (2010). Assessment of High-Sensitivity C-Reactive Protein Levels as Diagnostic Discriminator of Maturity-Onset Diabetes of the Young Due to HNF1A Mutations. Diabetes Care. 33(9). 1919–1924. 88 indexed citations
16.
Karavitaki, Niki, Gaya Thanabalasingham, Raluca Trifănescu, et al.. (2006). Do the limits of serum prolactin in disconnection hyperprolactinaemia need re‐definition? A study of 226 patients with histologically verified non‐functioning pituitary macroadenoma. Clinical Endocrinology. 65(4). 524–529. 139 indexed citations
17.
Thanabalasingham, Gaya, Niki Karavitaki, Simon Cudlip, & John Wass. (2005). Treatment of Pituitary Tumors: History. Endocrine. 28(1). 3–8. 2 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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