Giovanni Pigna

586 total citations
9 papers, 333 citations indexed

About

Giovanni Pigna is a scholar working on Endocrinology, Diabetes and Metabolism, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Giovanni Pigna has authored 9 papers receiving a total of 333 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Endocrinology, Diabetes and Metabolism, 6 papers in Cardiology and Cardiovascular Medicine and 5 papers in Surgery. Recurrent topics in Giovanni Pigna's work include Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers), Lipid metabolism and disorders (5 papers) and Lipoproteins and Cardiovascular Health (5 papers). Giovanni Pigna is often cited by papers focused on Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers), Lipid metabolism and disorders (5 papers) and Lipoproteins and Cardiovascular Health (5 papers). Giovanni Pigna collaborates with scholars based in Italy, Germany and Finland. Giovanni Pigna's co-authors include Marcello Arca, Anna Montali, Ilenia Minicocci, Fabio Pannozzo, Matti Jauhiainen, Christian Ehnholm, Fabiana Quagliarini, Marius R. Robciuc, Giancarlo Labbadia and Dieter Lütjohann and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, The American Journal of Cardiology and Atherosclerosis.

In The Last Decade

Giovanni Pigna

9 papers receiving 325 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Giovanni Pigna Italy 8 165 165 145 73 57 9 333
M.J. Veerkamp Netherlands 7 184 1.1× 228 1.4× 225 1.6× 57 0.8× 84 1.5× 7 387
A. Asplund‐Carlson Sweden 8 177 1.1× 219 1.3× 146 1.0× 59 0.8× 72 1.3× 10 349
Mingde Fu China 13 141 0.9× 307 1.9× 235 1.6× 88 1.2× 65 1.1× 26 433
Edward Duran United States 6 112 0.7× 165 1.0× 190 1.3× 67 0.9× 56 1.0× 10 326
Tetsuo Machida Japan 13 190 1.2× 213 1.3× 77 0.5× 55 0.8× 67 1.2× 23 359
Graciela López Argentina 16 124 0.8× 156 0.9× 137 0.9× 53 0.7× 105 1.8× 39 426
Yasuhiro Endoh Japan 8 213 1.3× 143 0.9× 133 0.9× 31 0.4× 55 1.0× 16 395
Juying Ji Australia 9 126 0.8× 285 1.7× 232 1.6× 103 1.4× 104 1.8× 11 420
Mohmed Ashmaig United States 3 88 0.5× 234 1.4× 231 1.6× 44 0.6× 34 0.6× 7 327
Phillip Bukberg United States 7 81 0.5× 144 0.9× 124 0.9× 56 0.8× 33 0.6× 9 257

Countries citing papers authored by Giovanni Pigna

Since Specialization
Citations

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

Fields of papers citing papers by Giovanni Pigna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giovanni Pigna

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

All Works

9 of 9 papers shown
1.
D’Erasmo, Laura, Ilenia Minicocci, Alessia Di Costanzo, et al.. (2021). Clinical Implications of Monogenic Versus Polygenic Hypercholesterolemia: Long‐Term Response to Treatment, Coronary Atherosclerosis Burden, and Cardiovascular Events. Journal of the American Heart Association. 10(9). e018932–e018932. 24 indexed citations
2.
3.
Arca, Marcello, et al.. (2012). Mechanisms of Diabetic Dyslipidemia: Relevance for Atherogenesis. Current Vascular Pharmacology. 10(6). 684–686. 71 indexed citations
4.
Minicocci, Ilenia, Anna Montali, Marius R. Robciuc, et al.. (2012). Mutations in theANGPTL3Gene and Familial Combined Hypolipidemia: A Clinical and Biochemical Characterization. The Journal of Clinical Endocrinology & Metabolism. 97(7). E1266–E1275. 120 indexed citations
5.
Arca, Marcello, et al.. (2012). Management of statin-intolerant patient.. PubMed. 54(2). 105–18. 12 indexed citations
6.
Pigna, Giovanni, Alessandro Napoli, Fulvio Zaccagna, et al.. (2011). The relationship between metabolic syndrome, its components, and the whole-body atherosclerotic disease burden as measured by computed tomography angiography. Atherosclerosis. 215(2). 417–420. 9 indexed citations
7.
Arca, Marcello, Giovanni Pigna, Fulvio Zaccagna, et al.. (2010). P9 ATHEROSCLEROTIC BURDEN IN ASYMPTOMATIC PATIENTS WITH METABOLIC SYNDROME EVALUATED BY COMPUTED TOMOGRAPHY ANGIOGRAPHY. Atherosclerosis Supplements. 11(2). 18–18. 1 indexed citations
8.
Arca, Marcello, Anna Montali, Giovanni Pigna, et al.. (2007). Comparison of atorvastatin versus fenofibrate in reaching lipid targets and influencing biomarkers of endothelial damage in patients with familial combined hyperlipidemia. Metabolism. 56(11). 1534–1541. 18 indexed citations
9.
Arca, Marcello, Anna Montali, Filomena Campagna, et al.. (2007). Usefulness of Atherogenic Dyslipidemia for Predicting Cardiovascular Risk in Patients With Angiographically Defined Coronary Artery Disease. The American Journal of Cardiology. 100(10). 1511–1516. 61 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026