Shin Ito

936 total citations
37 papers, 580 citations indexed

About

Shin Ito is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism and Molecular Biology. According to data from OpenAlex, Shin Ito has authored 37 papers receiving a total of 580 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cardiology and Cardiovascular Medicine, 10 papers in Endocrinology, Diabetes and Metabolism and 8 papers in Molecular Biology. Recurrent topics in Shin Ito's work include Heart Failure Treatment and Management (15 papers), Cardiovascular Function and Risk Factors (14 papers) and Diabetes Treatment and Management (7 papers). Shin Ito is often cited by papers focused on Heart Failure Treatment and Management (15 papers), Cardiovascular Function and Risk Factors (14 papers) and Diabetes Treatment and Management (7 papers). Shin Ito collaborates with scholars based in Japan, United States and China. Shin Ito's co-authors include Masafumi Kitakaze, Masanori Asakura, Hiroshi Asanuma, Tetsuo Minamino, Naoki Mochizuki, Shoji Sanada, Jiyoong Kim, Hiroyuki Takahama, Masakatsu Wakeno and H. Sasaki and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Shin Ito

33 papers receiving 570 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shin Ito Japan 11 250 233 144 123 90 37 580
Dajun Wang United States 11 275 1.1× 392 1.7× 107 0.7× 111 0.9× 79 0.9× 18 712
Loubina Fazal France 11 347 1.4× 244 1.0× 95 0.7× 102 0.8× 29 0.3× 17 650
Xiuren Gao China 15 232 0.9× 457 2.0× 108 0.8× 111 0.9× 64 0.7× 33 792
Thor Tejada United States 10 366 1.5× 154 0.7× 100 0.7× 219 1.8× 43 0.5× 14 725
Shin-ichi Gorogawa Japan 10 194 0.8× 106 0.5× 170 1.2× 206 1.7× 47 0.5× 11 582
Caroline Rudnicka Australia 10 184 0.7× 154 0.7× 310 2.2× 168 1.4× 54 0.6× 13 519
Xavier Hermant France 14 228 0.9× 250 1.1× 127 0.9× 188 1.5× 106 1.2× 19 699
Tsukasa Shimauchi Japan 14 235 0.9× 196 0.8× 41 0.3× 87 0.7× 99 1.1× 38 554
Sumit Kar United States 10 261 1.0× 241 1.0× 49 0.3× 80 0.7× 49 0.5× 18 601
Hodaka Yamada Japan 13 180 0.7× 116 0.5× 265 1.8× 196 1.6× 41 0.5× 42 581

Countries citing papers authored by Shin Ito

Since Specialization
Citations

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

Fields of papers citing papers by Shin Ito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shin Ito

This figure shows the co-authorship network connecting the top 25 collaborators of Shin Ito. A scholar is included among the top collaborators of Shin Ito 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 Shin Ito. Shin Ito 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.
Kobayashi, Masatake, Akira Yamashina, Kazuhiro Satomi, et al.. (2025). Eplerenone, diabetes, and chronic kidney disease in patients hospitalized for acute heart failure: findings from the EARLIER trial. Cardiovascular Diabetology. 24(1). 136–136. 1 indexed citations
2.
Tsukamoto, Osamu, Takuya Hasegawa, Ken Matsuoka, et al.. (2024). Relative B-Type Natriuretic Peptide Deficiency May Exist in Diastolic Dysfunction in Subclinical Population. Circulation Reports. 6(5). 151–160. 1 indexed citations
3.
Tsukamoto, Osamu, Takuya Hasegawa, Ken Matsuoka, et al.. (2024). Association Between B-Type Natriuretic Peptide Deficiency and Left Ventricular Concentric Hypertrophy in Subclinical Individuals. JACC Asia. 4(1). 87–88. 1 indexed citations
4.
5.
Kobayashi, Masatake, Akira Yamashina, Kazuhiro Satomi, et al.. (2024). Adverse events associated with early initiation of Eplerenone in patients hospitalized for acute heart failure. International Journal of Cardiology. 415. 132477–132477. 4 indexed citations
6.
Fukuda, Hiroki, Jiyoong Kim, Shin Ito, et al.. (2023). Metabolic syndrome is linked to the incidence of pancreatic cancer. EClinicalMedicine. 67. 102353–102353. 12 indexed citations
7.
Ito, Shin, Takashi Morimoto, & Masafumi Kitakaze. (2022). Daily self-monitoring of blood pressure decreases systolic and diastolic blood pressure in hypertensive participants. Heart and Vessels. 37(7). 1265–1270. 2 indexed citations
8.
Tsukamoto, Osamu, Takuya Hasegawa, Ken Matsuoka, et al.. (2022). Candidate Screening for Heart Failure With Preserved Ejection Fraction Clinic by Fib-4 Index From Subclinical Subjects. SHILAP Revista de lepidopterología. 2(2). 170–181. 4 indexed citations
9.
Tsukamoto, Osamu, Takuya Hasegawa, Ken Matsuoka, et al.. (2021). Lower B-Type Natriuretic Peptide Levels Predict Left Ventricular Concentric Remodelling and Insulin Resistance. ESC Heart Failure. 9(1). 636–647. 8 indexed citations
10.
Hisatome, Ichiro, Yasutaka Kurata, Yasutaka Yamamoto, et al.. (2021). α1-Adrenergic receptor mediates adipose-derived stem cell sheet-induced protection against chronic heart failure after myocardial infarction in rats. Hypertension Research. 45(2). 283–291. 4 indexed citations
11.
Min, Kyung‐Duk, Masanori Asakura, Manabu Shirai, et al.. (2021). ASB2 is a novel E3 ligase of SMAD9 required for cardiogenesis. Scientific Reports. 11(1). 23056–23056. 5 indexed citations
12.
Fukuda, Hiroki, et al.. (2020). Artificial Intelligence Uncovered Clinical Factors for Cardiovascular Events in Myocardial Infarction Patients with Glucose Intolerance. Cardiovascular Drugs and Therapy. 34(4). 535–545. 3 indexed citations
13.
Imazu, Miki, Hiroki Fukuda, Hideaki Kanzaki, et al.. (2020). Plasma indoxyl sulfate levels predict cardiovascular events in patients with mild chronic heart failure. Scientific Reports. 10(1). 16528–16528. 19 indexed citations
14.
Fukuda, Hiroki, et al.. (2020). Plasma BNP Levels and Diuretics Use as Predictors of Cardiovascular Events in Patients with Myocardial Infarction and Impaired Glucose Tolerance. Cardiovascular Drugs and Therapy. 34(1). 79–88. 5 indexed citations
15.
16.
Iwata, Yuko, Shin Ito, Shigeo Wakabayashi, & Masafumi Kitakaze. (2019). TRPV2 channel as a possible drug target for the treatment of heart failure. Laboratory Investigation. 100(2). 207–217. 25 indexed citations
17.
Fukuda, Hiroki, et al.. (2019). Heart rate determines the beneficial effects of beta-blockers on cardiovascular outcomes in patients with heart failure and atrial fibrillation. Hypertension Research. 42(11). 1716–1725. 5 indexed citations
18.
Fukuda, Hiroki, Tomomi Ide, Shintaro Kinugawa, et al.. (2018). Elucidation of the Strongest Predictors of Cardiovascular Events in Patients with Heart Failure. EBioMedicine. 33. 185–195. 8 indexed citations
19.
Fukuda, Hiroki, Jiyoong Kim, Tomomi Ide, et al.. (2018). The impact of creating mathematical formula to predict cardiovascular events in patients with heart failure. Scientific Reports. 8(1). 3986–3986. 5 indexed citations
20.
Ito, Shin, Koichi Akutsu, Yuiichi Tamori, et al.. (2007). Differences in Atherosclerotic Profiles Between Patients With Thoracic and Abdominal Aortic Aneurysms. The American Journal of Cardiology. 101(5). 696–699. 71 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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