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Robotic single site surgery (R-SSH) is a novel technique, which may be superior to multi site hysterectomy (R-MSH) in select patients regarding cosmesis and postoperative pain. A randomized trial is performed to compare R-SSH with R-MSH with regard to the postoperative rehabilitation, cosmesis, the operational cost, and the perioperative morbidity.
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The study is scheduled to start November 2018 and compares robotic single site to multi site hysterectomy. Procedures are performed on two locations, Herning and Herlev Hospitals, by experienced surgeons. Patients are randomized to either R-SSH (No.=62) or R-MSH (No.=62). Patient's satisfaction with body image and cosmesis is assessed at different time points pre- and postoperatively by means of validated cosmesis scales and Body Image Questionnaire and photo-evaluations.
Postoperative pain and split times spent at the operation theatre will be registered as secondary outcome parameters.
A follow-up at 1, 3 and 6 month include evaluation of the scar and registration of port-site hernias and vaginal dehiscence or other complications. Interviews and diaries will include time of return to home and work, daily activities including sexuality The R-SSH is performed using da Vinci, Xi robotic system. One single port, diameter 2 cm is applied. Applying an additional assistant port is defined conversion of procedure R-MSH is performed using standard equipment and 4 trocars, 5 mm each.
Sample size calculation was based a previous study on fast track hysterectomy, which showed a difference in return to work of 4 days. 62 women in each group is needed with standard deviation ±8 and a power of 80%. To include those not working, the calculation was performed with an expected visual analog pain score of 0.86 ±0.2 and 62 in each group and suggested that the sample was sufficient to detect of difference of 0.1 in visual analog pain score with a power of 80%. All calculation are based on two-sided testing with alpha of 0.05.
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0 participants in 2 patient groups
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Carsten Byrialsen; Finn F Lauszus, PhD
Data sourced from clinicaltrials.gov
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