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Retrospective Analysis of Route Selection for Hysterectomy for Benign Indications at Ochsner Baptist Hospital
Background: Hysterectomy, the most common gynecologic procedure in the United States, can be performed in a number of ways. A shift in surgical practice toward cost-effective and minimally invasive approaches provides an impetus to maximize early training in vaginal surgery for resident physicians....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academic Division of Ochsner Clinic Foundation
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755548/ https://www.ncbi.nlm.nih.gov/pubmed/33408573 http://dx.doi.org/10.31486/toj.20.0017 |
Sumario: | Background: Hysterectomy, the most common gynecologic procedure in the United States, can be performed in a number of ways. A shift in surgical practice toward cost-effective and minimally invasive approaches provides an impetus to maximize early training in vaginal surgery for resident physicians. Methods: A total of 62 abdominal, 303 robotic, and 41 vaginal hysterectomies performed between January 1, 2015 and December 31, 2017 at Ochsner Baptist Hospital in New Orleans, LA, that met inclusion criteria were retrospectively reviewed with a previously published route selection algorithm. We applied the algorithm using preoperative and postoperative data collected via medical record review to determine if our practices favor minimally invasive approaches. Results: Analysis using preoperative variables identified 152 robotic cases that were vaginal hysterectomy candidates (50.2%). Postoperative analysis of the same cases identified 127 (41.9%) vaginal hysterectomy candidates. Among abdominal cases, 37 (59.7%) called for a less invasive approach by preoperative findings: 7 (11.3%) vaginal and 30 (48.4%) laparoscopic. The algorithm sorted only 25 of the 62 abdominal cases (40.3%) to the abdominal approach. Conclusion: Use of a hysterectomy route selection algorithm preoperatively improves identification of candidates for minimally invasive hysterectomy. |
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