Route Of Hysterectomy: Robotic

JOURNAL OF GYNECOLOGIC SURGERY(2021)

引用 0|浏览4
暂无评分
摘要
The annual percentage of hysterectomies performed with robotic-assisted laparoscopy has steadily increased since the U.S. Food and Drug Administration (FDA) approved the platform for gynecologic surgery in 2005. The rapid adoption and continued expansion of this technique are due to many factors, including 3-dimensional cameras with better visualization, instrumentation enabling precise movements with tremor control, and better ergonomics for surgeons. Residency training, with decreased numbers of minimally invasive techniques using vaginal and laparoscopic approaches, likely contributes to this trend as well. Despite these ever-increasing numbers, gynecologic societies have yet to determine and outline a standardized credentialing process. The robotic-assisted laparoscopic platform enables challenging cases, which previously would have been relegated to laparotomy, to be addressed in a minimally invasive platform. Obese patients and those with enlarged uteri or with significant adhesive disease have benefited from this unique technology. Hysterectomies performed with the robotic platform have consistently had lower surgical blood loss and shorter lengths of hospital stays. Complication rates between robotic-assisted laparoscopy and standard laparoscopy for hysterectomies appear to be similar; however, the robotic platform has longer operative times. This could be balanced by the demonstrated overall shorter hospital stay, compared to standard laparoscopic hysterectomy, and by a lower conversion rate to laparotomy. Advantages of the robotic platform appear to be magnified when surgeons have greater experience. Costs associated with purchase and use of robotic platforms continue to cause concern. It is hoped that competition with alternative robotic systems will decrease these costs. However, they must be viewed within the context of improved surgical and perioperative outcomes.
更多
查看译文
关键词
gynecology, hysterectomy, robotic, surgery
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要