New insights in robotic colorectal surgery: are we moving to the future or are we stuck in the progress?

Colorectal diseases represent a significant burden in modern medicine, with a severe impact on patients’ quality of life. This has driven the need for effective treatments and the refinement of currently available methods. Surgical intervention remains the gold standard for most colorectal conditions. However, because of the complexity of such surgeries, the steep learning curves for surgeons, operator-associated complications, and many other factors, the availability of highly specialized colorectal surgeons does not meet the growing demand. To optimize patient care, several strategies have been analyzed to address these obstacles, most of which focus on shifting from conventional surgical methods to more novel approaches. Robotic surgery (RS) has been a prominent topic since its introduction and has provided outstanding results in various clinical scenarios. Compared with traditional methods, robotic techniques offer distinct advantages. The enhanced dexterity and range of motion provided by robotic tools are invaluable in the surgical field. Moreover, the magnified view provides more clarity, enabling more precise maneuvers. As surgical practices continue to evolve, minimally invasive methods and robotic techniques are gaining relevance worldwide. In this review, we assess the suitability of robotic methods in colorectal surgeries by comparing their outcomes, associated costs, operator learning curves, intraoperative and postoperative complications, and conversion rates to open surgery in contrast to traditional methods.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-10
DOI
https://doi.org/10.5281/zenodo.14062393
Primary Topic
Colorectal Cancer Surgical Treatments
Type
article
Field-Weighted Citation Impact
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article

New insights in robotic colorectal surgery: are we moving to the future or are we stuck in the progress?

Zenodo (CERN European Organization for Nuclear Research)
Colorectal Cancer Surgical Treatments
article

New insights in robotic colorectal surgery: are we moving to the future or are we stuck in the progress?

article en

Abstract

Colorectal diseases represent a significant burden in modern medicine, with a severe impact on patients’ quality of life. This has driven the need for effective treatments and the refinement of currently available methods. Surgical intervention remains the gold standard for most colorectal conditions. However, because of the complexity of such surgeries, the steep learning curves for surgeons, operator-associated complications, and many other factors, the availability of highly specialized colorectal surgeons does not meet the growing demand. To optimize patient care, several strategies have been analyzed to address these obstacles, most of which focus on shifting from conventional surgical methods to more novel approaches. Robotic surgery (RS) has been a prominent topic since its introduction and has provided outstanding results in various clinical scenarios. Compared with traditional methods, robotic techniques offer distinct advantages. The enhanced dexterity and range of motion provided by robotic tools are invaluable in the surgical field. Moreover, the magnified view provides more clarity, enabling more precise maneuvers. As surgical practices continue to evolve, minimally invasive methods and robotic techniques are gaining relevance worldwide. In this review, we assess the suitability of robotic methods in colorectal surgeries by comparing their outcomes, associated costs, operator learning curves, intraoperative and postoperative complications, and conversion rates to open surgery in contrast to traditional methods.

Zenodo (CERN European Organization for Nuclear Research)
Pontificia Universidad Católica del Ecuador (EC), Sociedad Española de Cirugía Ortopédica y Traumatología (ES), Hospital de Especialidades (MX), Hospital Metropolitano (EC)
Openalex Percentile: Top 55%
Colorectal Cancer Surgical Treatments
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