Stephan Eckert
Papers
1
Total Citations
7
H-Index
1
About
Dr. Stephan Eckert is a colorectal surgeon whose research focuses on optimizing surgical outcomes in minimally invasive oncology, particularly during the challenging initiation phase of robotic programs. His most-cited work, a 2020 study with 7 citations, provides critical insights into how patient comorbidity—measured by the ASA score—and the surgeon’s learning curve independently influence early postoperative results in robotic colorectal cancer resections. By analyzing 43 consecutive cases, Eckert demonstrated that while the learning curve affects operative efficiency, the ASA score remains a robust predictor of complications and mortality, offering a practical framework for patient selection and risk stratification in new robotic programs. This contribution is especially valuable for institutions adopting robotic surgery, as it helps balance patient safety with technical skill development. Eckert’s work underscores the importance of integrating patient-specific factors into surgical planning, advancing the evidence base for safe implementation of advanced technologies in colorectal oncology. His research continues to inform best practices for surgeons transitioning to robotic platforms.
Research Focus
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Top Papers
- 1