Shelby Kutty

13.7k total citations · 1 hit paper
345 papers, 7.6k citations indexed

About

Shelby Kutty is a scholar working on Cardiology and Cardiovascular Medicine, Epidemiology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Shelby Kutty has authored 345 papers receiving a total of 7.6k indexed citations (citations by other indexed papers that have themselves been cited), including 233 papers in Cardiology and Cardiovascular Medicine, 170 papers in Epidemiology and 93 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Shelby Kutty's work include Congenital Heart Disease Studies (163 papers), Cardiovascular Function and Risk Factors (131 papers) and Cardiac Valve Diseases and Treatments (65 papers). Shelby Kutty is often cited by papers focused on Congenital Heart Disease Studies (163 papers), Cardiovascular Function and Risk Factors (131 papers) and Cardiac Valve Diseases and Treatments (65 papers). Shelby Kutty collaborates with scholars based in United States, Germany and United Kingdom. Shelby Kutty's co-authors include Andreas Schuster, David A. Danford, Johannes T. Kowallick, Philipp Beerbaum, Gerd Hasenfuß, Joachim Lotz, Eike Nagel, Geraint Morton, Roy Jogiya and Massimiliano Cantinotti and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and Journal of the American College of Cardiology.

In The Last Decade

Shelby Kutty

330 papers receiving 7.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Cardiovascular Magnetic Resonance Myocardial Feature Tracking

2016 272 citations Andreas Schuster, Johannes T. Kowallick et al. Circulation Cardiovascular Imaging profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shelby Kutty United States	43	4.8k	2.5k	2.2k	2.0k	1.7k	345	7.6k
Erwan Donal France	43	6.7k 1.4×	1.2k 0.5×	2.1k 1.0×	957 0.5×	1.5k 0.9×	282	7.8k
Giovanni Di Salvo Italy	42	4.5k 0.9×	1.8k 0.7×	1.4k 0.6×	1.3k 0.6×	1.1k 0.7×	334	6.5k
Mario J. García United States	55	9.7k 2.0×	1.6k 0.6×	4.5k 2.1×	1.7k 0.8×	2.4k 1.4×	331	12.0k
Mark Monaghan United Kingdom	37	4.3k 0.9×	1.6k 0.6×	1.7k 0.8×	939 0.5×	1.1k 0.6×	210	5.9k
Sabino Iliceto Italy	67	12.0k 2.5×	2.1k 0.8×	3.8k 1.8×	2.4k 1.2×	3.7k 2.1×	521	16.2k
Gad Keren Israel	47	5.7k 1.2×	1.6k 0.6×	1.5k 0.7×	1.5k 0.7×	2.1k 1.2×	372	10.6k
Krishnaswamy Chandrasekaran United States	35	8.0k 1.7×	2.6k 1.0×	1.7k 0.8×	4.6k 2.3×	2.9k 1.7×	207	11.1k
Hisham Dokainish United States	32	8.4k 1.7×	1.1k 0.4×	2.9k 1.3×	1.2k 0.6×	1.4k 0.8×	87	9.8k
Bernard Cosyns Belgium	37	3.6k 0.7×	1.3k 0.5×	1.7k 0.8×	830 0.4×	1.4k 0.8×	208	5.5k
Stamatios Lerakis United States	41	4.1k 0.8×	2.4k 0.9×	1.3k 0.6×	1.2k 0.6×	1.3k 0.7×	255	5.7k

Countries citing papers authored by Shelby Kutty

Since Specialization

Citations

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

Fields of papers citing papers by Shelby Kutty

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shelby Kutty

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

All Works

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20 of 20 papers shown

Backhaus, Sören J., Alexander Schulz, Johannes T. Kowallick, et al.. (2025). Evaluating pulmonary stenosis and regurgitation impact on cardiac strain and strain rate in a porcine model via magnetic resonance feature tracking. The International Journal of Cardiovascular Imaging. 41(2). 257–268.

Zhu, J., et al.. (2025). The prediction value of serum anion gap for short-term mortality in pulmonary hypertension patients with sepsis: a retrospective cohort study. Frontiers in Medicine. 11. 1499677–1499677. 2 indexed citations

Eynde, Jef Van den, Xander Jacquemyn, David A. Danford, et al.. (2024). Optimal Shunt Type for Norwood Procedure: Predicted Adverse Impact of Discordant Surgical Approach. The Annals of Thoracic Surgery. 119(3). 602–615.

Jacquemyn, Xander, Jordan B. Strom, Geoff Strange, et al.. (2024). Moderate Aortic Valve Stenosis Is Associated With Increased Mortality Rate and Lifetime Loss: Systematic Review and Meta‐Analysis of Reconstructed Time‐to‐Event Data of 409 680 Patients. Journal of the American Heart Association. 13(9). e033872–e033872. 11 indexed citations

Vervoort, Dominique, et al.. (2024). Unmet Needs in Pediatric and Congenital Heart Surgery: A Review. Congenital Heart Disease. 19(5). 499–511.

Cantinotti, Massimiliano, Vivek Jani, Shelby Kutty, et al.. (2024). Neonates and Infants with Left Heart Obstruction and Borderline Left Ventricle Undergoing Biventricular Repair: What Do We Know about Long-Term Outcomes? A Critical Review. Healthcare. 12(3). 348–348.

Jacquemyn, Xander, Shelby Kutty, & Cedric Manlhiot. (2023). The Lifelong Impact of Artificial Intelligence and Clinical Prediction Models on Patients With Tetralogy of Fallot. PubMed. 2(6). 440–452. 3 indexed citations

Cantinotti, Massimiliano, Colin J. McMahon, Marco Scalese, et al.. (2023). Echocardiographic Parameters for Risk Prediction in Borderline Right Ventricle: Review with Special Emphasis on Pulmonary Atresia with Intact Ventricular Septum and Critical Pulmonary Stenosis. Journal of Clinical Medicine. 12(14). 4599–4599. 3 indexed citations

Shen, Christine, James C. Perry, Amr F. Barakat, et al.. (2023). Convolution Neural Network Algorithm for Shockable Arrhythmia Classification Within a Digitally Connected Automated External Defibrillator. Journal of the American Heart Association. 12(8). e026974–e026974. 13 indexed citations

10.

Barnes, Benjamin, et al.. (2022). Right ventricular longitudinal function is linked to left ventricular filling pressure in patients with repaired tetralogy of fallot. The International Journal of Cardiovascular Imaging. 39(2). 401–409. 2 indexed citations

11.

Eynde, Jef Van den, Mark Lachmann, Karl‐Ludwig Laugwitz, Cedric Manlhiot, & Shelby Kutty. (2022). Successfully implemented artificial intelligence and machine learning applications in cardiology: State-of-the-art review. Trends in Cardiovascular Medicine. 33(5). 265–271. 25 indexed citations

12.

Choudhary, Preeti, W. Strugnell, Rajesh Puranik, et al.. (2021). LV non-compaction in patients with coarctation of the aorta: prevalence and effects on cardiac function. Cardiology in the Young. 31(9). 1445–1450. 1 indexed citations

13.

Loomba, Rohit, et al.. (2021). Persistent Right Venous Valve: Insights From Multimodality Imaging. Circulation Cardiovascular Imaging. 14(5). e010977–e010977. 7 indexed citations

14.

Cantinotti, Massimiliano, Raffaele Giordano, Nadia Assanta, et al.. (2021). Echocardiographic Screening of Anomalous Origin of Coronary Arteries in Athletes with a Focus on High Take-Off. Healthcare. 9(2). 231–231. 12 indexed citations

15.

Eynde, Jef Van den, et al.. (2021). Risk factors for acute kidney injury after pediatric cardiac surgery: a meta-analysis. Pediatric Nephrology. 37(3). 509–519. 29 indexed citations

16.

Choudhury, Songita A., et al.. (2018). Selective infarct zone imaging with intravenous acoustically activated droplets. PLoS ONE. 13(12). e0207486–e0207486. 12 indexed citations

17.

Cantinotti, Massimiliano, Raffaele Giordano, Marco Scalese, et al.. (2015). Nomograms for mitral inflow Doppler and tissue Doppler velocities in Caucasian children. Journal of Cardiology. 68(4). 288–299. 25 indexed citations

18.

Zhang, Ming, David A. Danford, Rimsha Hasan, et al.. (2015). Hepatic stiffness in the bidirectional cavopulmonary circulation: The Liver Adult-Pediatric-Congenital-Heart-Disease Dysfunction Study group. Journal of Thoracic and Cardiovascular Surgery. 151(3). 678–684. 22 indexed citations

19.

Peng, Qinghai, David A. Danford, Scott E. Fletcher, et al.. (2013). Increased hepatic stiffness as consequence of high hepatic afterload in the fontan circulation: A vascular doppler and elastography study. Hepatology. 59(1). 251–260. 109 indexed citations

20.

Kutty, Shelby, et al.. (2008). Pulmonary Valve Replacement Improves But Does Not Normalize Right Ventricular Mechanics in Repaired Congenital Heart Disease: A Comparative Assessment Using Velocity Vector Imaging. Journal of the American Society of Echocardiography. 21(11). 1216–1221. 26 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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