G. Cavera

701 citations
19 papers · 480 · h-index 12

Impact in

Papers in

G. Cavera

19 papers receiving 453 citations

Peers

G. Cavera
Comparison fields: 5 of 76
  • Transplantation 16
  • Endocrinology, Diabetes and Metabolism 87
  • Cardiology and Cardiovascular Medicine 76
  • Genetics 90
  • Aging 5
Replace G Lloveras with:
G Lloveras Spain
Daniela Liccardo Italy
Jieling Xiao Singapore
Ivan Jakopčić Croatia
Patricia Botas Spain
Farid Ljuca Bosnia and Herzegovina
Raúl Fernández-Prado Spain
Daniel S. Donovan United States
D.E. van Diermen Netherlands
Linlin Mai China
G. Cavera relative to G Lloveras Spain G Lloveras's profile →
Citations per field
00.5×5.3×
G Lloveras · 1×
Citations per year

Countries citing papers authored by G. Cavera

Since Specialization
Citations

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

Fields of papers citing papers by G. Cavera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside G. Cavera, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with G. Cavera Line = papers co-authored together G. Cavera links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 1998103
2 200150
3 200743
4 201342
5 200541
6 199935
7 200226
8 200224
9 199723
10 199820
11 199919
12
Riskard 2005. New tools for prediction of cardiovascular disease risk derived from Italian population studies. Nutr Metab Cardiovasc Dis. 2005 Dec;15(6):426-40. Epub 2005 Nov 16
200511
13 199210
14 20119
15 20089
16 20165
17
Apo-lipoprotein profile in subjects with extracranial carotid atherosclerosis.
19944
18
Lipoprotein(A) levels and apoprotein(a) phenotypes in a Sicilian population.
19993
19 20133

About G. Cavera

G. Cavera is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism, Pulmonary and Respiratory Medicine, Surgery and Rheumatology, having authored 19 papers that have together received 480 indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Cancer, Lipids, and Metabolism (2 papers), Heart Failure Treatment and Management (2 papers), Diabetes Management and Research (1 paper), Blood properties and coagulation (1 paper), Digestive system and related health (1 paper), Cardiovascular Health and Disease Prevention (1 paper) and Gallbladder and Bile Duct Disorders (1 paper). The work is most often cited by research in Transplantation (16 citations), Endocrinology, Diabetes and Metabolism (87 citations), Cardiology and Cardiovascular Medicine (76 citations), Genetics (90 citations) and Aging (5 citations). G. Cavera has collaborated with scholars based in Italy and United States. Frequent co-authors include Maurizio Averna, A Notarbartoló, Davide Noto, Giuseppe Montalto, Carlo M. Barbagallo, Antonio Carroccio, Angelo B. Cefalù, Michele Pagano, Manfredi Rizzo and Rosalia Caldarella. Their work appears in journals such as Nutrition Metabolism and Cardiovascular Diseases, Journal of the American College of Nutrition, Thrombosis and Haemostasis, BMC Pharmacology and Toxicology and Age and Ageing.

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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