About

Amit Iyengar is a leading cardiovascular surgeon-scientist whose research focuses on robotic cardiac surgery, surgical outcomes, and the learning curves associated with advanced minimally invasive techniques. His work has been instrumental in defining the minimum case requirements for training in robotically assisted coronary artery bypass grafting (RA-CABG), using data from the STS database to move beyond expert opinion toward evidence-based benchmarks. His landmark 2021 study on the learning curve of RA-CABG has garnered 33 citations, shaping training protocols and patient safety standards. Iyengar has also investigated the impact of surgical approach and hospital volume on cardiovascular complications after pulmonary lobectomy (19 citations), highlighting the importance of institutional experience in complex thoracic procedures. More recently, he has contributed to the strategic implementation of new robotic mitral repair programs, sharing early outcomes to guide program development. Through his rigorous analyses of large clinical databases, Iyengar provides actionable insights that help surgeons and hospitals optimize robotic cardiac surgery programs, ultimately improving patient outcomes and advancing the field of minimally invasive cardiac care.

Research Focus

Key Achievements

2
H-Index
3
Papers
53
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
The learning curve of robotic coronary arterial bypass surgery: A report from the STS database
33 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 26
🏛 Institutions: University of Pennsylvania, University of California, Los Angeles, Hospital of the University of Pennsylvania

Top Papers

  1. 1
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago