13 research outputs found

    Surgery-related Complications of Robot-assisted Radical Cystectomy With Intracorporeal Urinary Diversion

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    OBJECTIVES To assess the surgery-related complications at robot-assisted radical cystectomy with total intracorporeal urinary diversion during our learning curve in treating 45 patients with bladder cancer. METHODS A total of 45 patients were pooled in 3 consecutive groups of 15 cases each to evaluate the complications according to the Clavien classification. As a surrogate for our learning curve, the following parameters were assessed: operative time, blood loss, urinary diversion type, lymph node yield, surgical margin status, and length of hospital stay. RESULTS Early surgery-related complications were noted in 40% of the patients and late complications in 30%. The early Clavien grade III complications remained significant (27%) and did not decline with time. Overall, fewer complications were observed between the groups over time, with a significant decrease in late versus early complications (P = .005 and P = .058). The mean operative times declined from the first group to the second and third groups (P = .005) and the hospital stays shortened (P = .006). No significant difference was observed between groups regarding the lymph node yield at cystectomy (P = .108), with a mean of 22.5 nodes (range 10-52) removed. More patients received an orthotopic bladder substitute (Studer) in each of the latter 2 groups than in the first. CONCLUSIONS Although robot-assisted radical cystectomy with total intracorporeal urinary diversion is a complex procedure, we observed decreased surgery-related complications and improved outcomes over time in the present series. Our results need to be confirmed by others before robot-assisted radical cystectomy with totally intracorporeal urinary diversion can be accepted as a treatment option for patients with bladder cancer. UROLOGY 77: 871-877, 2011. (c) 2011 Elsevier Inc

    Development of a patient and institutional-based model for estimation of operative times for robot-assisted radical cystectomy:Results from the International Robotic Cystectomy Consortium

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    OBJECTIVES: To design a methodology to predict operative times for robot-assisted radical cystectomy (RARC) based on variation in institutional, patient, and disease characteristics to help in operating room scheduling and quality control. PATIENTS AND METHODS: The model included preoperative variables and therefore can be used for prediction of surgical times: institutional volume, age, gender, body mass index, American Society of Anesthesiologists score, history of prior surgery and radiation, clinical stage, neoadjuvant chemotherapy, type, technique of diversion, and the extent of lymph node dissection. A conditional inference tree method was used to fit a binary decision tree predicting operative time. Permutation tests were performed to determine the variables having the strongest association with surgical time. The data were split at the value of this variable resulting in the largest difference in means for the surgical time across the split. This process was repeated recursively on the resultant data sets until the permutation tests showed no significant association with operative time. RESULTS: In all, 2 134 procedures were included. The variable most strongly associated with surgical time was type of diversion, with ileal conduits being 70 min shorter (P \u3c 0.001). Amongst patients who received neobladders, the type of lymph node dissection was also strongly associated with surgical time. Amongst ileal conduit patients, institutional surgeon volume (\u3e66 RARCs) was important, with those with a higher volume being 55 min shorter (P \u3c 0.001). The regression tree output was in the form of box plots that show the median and ranges of surgical times according to the patient, disease, and institutional characteristics. CONCLUSION: We developed a method to estimate operative times for RARC based on patient, disease, and institutional metrics that can help operating room scheduling for RARC
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