N Sattar

1.1k total citations
23 papers, 806 citations indexed

About

N Sattar is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Epidemiology. According to data from OpenAlex, N Sattar has authored 23 papers receiving a total of 806 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Endocrinology, Diabetes and Metabolism, 5 papers in Surgery and 5 papers in Epidemiology. Recurrent topics in N Sattar's work include Lipoproteins and Cardiovascular Health (3 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers) and Ovarian function and disorders (2 papers). N Sattar is often cited by papers focused on Lipoproteins and Cardiovascular Health (3 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers) and Ovarian function and disorders (2 papers). N Sattar collaborates with scholars based in United Kingdom, United States and Germany. N Sattar's co-authors include Donald C. McMillan, Nita G. Forouhi, S. Goya Wannamethee, John R. Petrie, M. N. V. Ravi Kumar, K. Wilson, Gaurav Sharma, Christopher F. van der Walle, Graham Leese and John McKnight and has published in prestigious journals such as The Lancet, Circulation and European Heart Journal.

In The Last Decade

N Sattar

20 papers receiving 778 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
N Sattar United Kingdom 10 205 202 144 133 128 23 806
Daniele Sola Italy 14 254 1.2× 206 1.0× 110 0.8× 37 0.3× 84 0.7× 42 912
Yasuyuki Okuda Japan 21 717 3.5× 264 1.3× 59 0.4× 160 1.2× 87 0.7× 64 1.5k
Kausik Umanath United States 14 298 1.5× 301 1.5× 94 0.7× 95 0.7× 90 0.7× 27 1.4k
Charles A. Reasner United States 15 456 2.2× 248 1.2× 78 0.5× 31 0.2× 71 0.6× 36 852
Lihua Wang China 19 85 0.4× 233 1.2× 129 0.9× 73 0.5× 88 0.7× 70 983
James B. Moberly United States 20 224 1.1× 287 1.4× 71 0.5× 95 0.7× 75 0.6× 51 1.1k
Motoshi Ouchi Japan 18 264 1.3× 238 1.2× 85 0.6× 19 0.1× 124 1.0× 58 846
Kristoffer Hellsing Sweden 17 352 1.7× 219 1.1× 302 2.1× 78 0.6× 142 1.1× 46 1.1k

Countries citing papers authored by N Sattar

Since Specialization
Citations

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

Fields of papers citing papers by N Sattar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of N Sattar

This figure shows the co-authorship network connecting the top 25 collaborators of N Sattar. A scholar is included among the top collaborators of N Sattar 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 N Sattar. N Sattar 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.
Smolen, Josef S, Peter Nash, Kevin Winthrop, et al.. (2025). Safety of Janus kinase inhibitors in immune-mediated inflammatory diseases – a systematic literature review informing the 2024 update of an international expert consensus statement. Annals of the Rheumatic Diseases. 84(5). 697–715. 7 indexed citations
2.
Hartley, Adam, Somayeh Rostamian, Amit Kaura, et al.. (2025). The relationship of baseline high-sensitivity C-reactive protein with incident cardiovascular events and all-cause mortality over 20 years. EBioMedicine. 117. 105786–105786.
3.
Dennis, John, Andrew McGovern, Andrew Farmer, et al.. (2025). A five-drug class model using routinely available clinical features to optimise prescribing in type 2 diabetes: a prediction model development and validation study. The Lancet. 405(10480). 701–714. 10 indexed citations
4.
Smolen, Josef S, Peter Nash, Daniel Aletaha, et al.. (2025). Efficacy of Janus kinase inhibitors in immune-mediated inflammatory diseases a systematic literature review informing the 2024 update of an international consensus statement. Annals of the Rheumatic Diseases. 84(5). 680–696. 2 indexed citations
5.
Pétursson, Pétur, Aidin Rawshani, Jan Borén, et al.. (2025). End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images. Open Heart. 12(1). e002998–e002998. 2 indexed citations
6.
Prato, Stefano Del, Chinthanie Ramasundarahettige, Kelley R. Branch, et al.. (2024). Impact of baseline FIB-4 score on efpeglenatide benefits on cardiovascular outcomes in people with type 2 diabetes: a participant-level exploratory analysis of the AMPLITUDE-O trial. Cardiovascular Diabetology. 23(1). 352–352.
7.
8.
Sattar, N, Paul Valensi, David Preiss, et al.. (2016). Long-term efficacy of evolocumab in reducing lipids in EU subjects with and without type 2 diabetes: an analysis from the open-label extension OSLER studies. Diabetologia. 59. 1 indexed citations
9.
Sattar, N, et al.. (2016). Potential relevance of changes in haematocrit to changes in lipid parameters with empagliflozin in patients with type 2 diabetes. Diabetologie und Stoffwechsel. 11(S 01). 8 indexed citations
10.
Looker, Helen C., Stephen Nyangoma, John A. Olson, et al.. (2012). Diabetic retinopathy at diagnosis of type 2 diabetes in Scotland. Diabetologia. 55(9). 2335–2342. 81 indexed citations
11.
Colhoun, Helen M., Shona Livingstone, Helen C. Looker, et al.. (2012). Hospitalised hip fracture risk with rosiglitazone and pioglitazone use compared with other glucose-lowering drugs. Diabetologia. 55(11). 2929–2937. 118 indexed citations
12.
13.
Sever, Peter, Neil R Poulter, Aroon D. Hingorani, et al.. (2011). Evaluation of C-reactive protein prior to and on-treatment as a predictor of benefit from atorvastatin: observations from the Anglo-Scandinavian Cardiac Outcomes Trial. European Heart Journal. 33(4). 486–494. 41 indexed citations
14.
Sharma, Gaurav, K. Wilson, Christopher F. van der Walle, et al.. (2010). Microemulsions for oral delivery of insulin: Design, development and evaluation in streptozotocin induced diabetic rats. European Journal of Pharmaceutics and Biopharmaceutics. 76(2). 159–169. 113 indexed citations
15.
Sassarini, Jenifer, Henrik Fox, William R. Ferrell, N Sattar, & Mary Ann Lumsden. (2010). Vascular function and cardiovascular risk factors in women with severe flushing. Clinical Endocrinology. 74(1). 97–103. 23 indexed citations
16.
Hothersall, Eleanor J., Rekha Chaudhuri, Charles McSharry, et al.. (2008). Effects of atorvastatin added to inhaled corticosteroids on lung function and sputum cell counts in atopic asthma. Thorax. 63(12). 1070–1075. 83 indexed citations
17.
Sattar, N, S. Goya Wannamethee, & Nita G. Forouhi. (2008). Novel biochemical risk factors for type 2 diabetes: pathogenic insights or prediction possibilities?. Diabetologia. 51(6). 926–940. 109 indexed citations
18.
Sattar, N, et al.. (2003). Evidence for the use of metformin in women with polycystic ovary syndrome. 1 indexed citations
19.
Harborne, L, et al.. (2002). Metformin and weight loss in women with polycystic ovary syndrome (PCOS). 4. 1 indexed citations
20.
McMillan, Donald C., et al.. (2000). Effect of the inflammatory response on trace element and vitamin status. Annals of Clinical Biochemistry International Journal of Laboratory Medicine. 37(3). 289–297. 158 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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