This study evaluated intraoperative complications and postoperative outcomes of gynecologic oncology patients undergoing robotic-assisted (RA) laparoscopic procedures in a university setting. A retrospective chart review evaluated all gynecologic oncology patients at the University of Alabama at Birmingham who underwent attempted RA procedures between August 2006 and October 2011. Patient demographics, medical/surgical history, intraoperative complications, postoperative outcomes, conversion rates, readmission rates, and length of stay were examined. Total complication rates were assessed over time for each surgeon. 681 patients underwent planned RA procedures by seven gynecologic oncologists. The mean body mass index was 33.5 kg/m(2) (range 16.6-71.0 kg/m(2)). 61.4 % were diagnosed with malignancy. The most common procedure was RA hysterectomy with unilateral/bilateral salpingo-oophorectomy (37.2 %). Robotic staging was performed in 291 patients (45.1 %). Mean estimated blood loss was 75 ml (range 5-700 ml). 36 patients (5.3 %) were converted to laparotomy. The most common reason for conversion was adhesions (30.1 %), followed by uterine size (22.2 %). In 107 cases, a surgical modification was required for specimen removal including mini-laparotomy (24), extension of accessory port (36), morcellation (9), and difficult vaginal delivery (38). 3.7 % had intraoperative complications; 6 patients had a cystotomy and 5 had a vascular injury. Postoperatively, 20 patients had a febrile episode, 9 had wound complications, and 3 had a vaginal cuff dehiscence. 27 (4.2 %) patients were readmitted within 30 days. Complication rates and conversion rates were similar per surgeon. Total complication rates for evaluable surgeons were similar between the first 10 cases and subsequent 50 cases. Although patients undergoing RA procedures in a university setting are high risk, the conversion rate to laparotomy is low and intraoperative and postoperative complications are acceptable. Total complication rates for each surgeon were not impacted by the number of cases performed.
Keywords: Learning curve; Robotic hysterectomy; Robotic hysterectomy complications.