Female Pelvic Medicine and Reconstructive Surgery, Allina Health, St. Paul, and the Department of Obstetrics and Gynecology, the Division of Biomedical Statistics and Informatics, and the Division of Health Care Policy and Research, Mayo Clinic, Rochester, Minnesota.
Obstet Gynecol. 2020 Apr;135(4):761-769. doi: 10.1097/AOG.0000000000003725.
To evaluate the rate of vaginal hysterectomy and outcomes after initiation of a prospective decision-tree algorithm to determine the optimal surgical route of hysterectomy.
A prospective algorithm to determine optimal route of hysterectomy was developed, which uses the following factors: history of laparotomy, uterine size, and vaginal access. The algorithm was implemented at our institution from November 24, 2015, to December 31, 2017, for patients requiring hysterectomy for benign indications. Expected route of hysterectomy was assigned by the algorithm and was compared with the actual route performed to identify compliance compared with deviation. Surgical outcomes were analyzed.
Of 365 patients who met inclusion criteria, 202 (55.3%) were expected to have a total vaginal hysterectomy, 57 (15.6%) were expected to have an examination under anesthesia followed by total vaginal hysterectomy, 52 (14.2%) were expected to have an examination under anesthesia followed by robotic-assisted total laparoscopic hysterectomy, and 54 (14.8%) were expected to have an abdominal or robotic-laparoscopic route of hysterectomy. Forty-six procedures (12.6%) deviated from the algorithm to a more invasive route (44 robotic, two abdominal). Seven patients had total vaginal hysterectomy when robotic-assisted total laparoscopic hysterectomy or abdominal hysterectomy was expected by the algorithm. Overall, 71% of patients were expected to have a vaginal route of hysterectomy per the algorithm, of whom 81.5% had a total vaginal hysterectomy performed; more than 99% of the total vaginal hysterectomies attempted were successfully completed.
Vaginal surgery is feasible, carries a low complication rate with excellent outcomes, and should have a place in gynecologic surgery. National use of this prospective algorithm may increase the rate of total vaginal hysterectomy and decrease health care costs.
评估在启动前瞻性决策树算法以确定子宫切除术最佳手术路径后行阴道子宫切除术的比例和结局。
我们开发了一种用于确定子宫切除术最佳路径的前瞻性算法，该算法使用以下因素：剖腹手术史、子宫大小和阴道通道。该算法于 2015 年 11 月 24 日至 2017 年 12 月 31 日在我院用于因良性指征需行子宫切除术的患者。算法预期的子宫切除术路径与实际进行的路径进行比较，以确定符合率和偏差率。分析手术结局。
符合纳入标准的 365 例患者中，202 例（55.3%）预计行全阴道子宫切除术，57 例（15.6%）预计在全身麻醉下检查后行全阴道子宫切除术，52 例（14.2%）预计在全身麻醉下检查后行机器人辅助全腹腔镜子宫切除术，54 例（14.8%）预计行腹部或机器人腹腔镜子宫切除术。46 例（12.6%）手术路径偏离算法，采用更具侵袭性的路径（44 例机器人辅助手术，2 例开腹手术）。有 7 例患者预计行机器人辅助全腹腔镜子宫切除术或开腹子宫切除术，但行全阴道子宫切除术。总体而言，根据算法，71%的患者预计采用阴道途径行子宫切除术，其中 81.5%的患者行全阴道子宫切除术；尝试的全阴道子宫切除术 99%以上均成功完成。
阴道手术可行，并发症发生率低，结局良好，应在妇科手术中占有一席之地。全国范围内使用这种前瞻性算法可能会增加全阴道子宫切除术的比例，并降低医疗保健成本。
