Study Objective
To determine the factors that allow for a safe outpatient robotic-assisted minimally invasive gynecologic oncology surgery procedure.
Design
Retrospective chart review (Canadian Task Force classification II-1).
Setting
University hospital.
Patients
All patients (140) undergoing robotic-assisted minimally invasive surgery with the gynecologic oncology service from January 1, 2013, to December 31, 2013.
Interventions
Risk factors for unsuccessful discharge within 23 hours of surgery and same-day discharge were assessed using logistic regression models.
Measurements and Main Results
All patients were initially scheduled for same-day discharge. The outpatient surgery group was defined by discharge within 23 hours of the surgery end time, and a same-day surgery subgroup was defined by discharge before midnight on the day of surgery. One hundred fifteen (82.1%) were successfully discharged within 23 hours of surgery, and 90 (64.3%) were discharged the same day. The median hospital stay was 5.3 hours (range, 1–48 hours). Unsuccessful discharge within 23 hours was associated with a preoperative diagnosis of lung disease and intraoperative complications; unsuccessful same-day discharge was associated with older age and later surgery end time. Only 2 patients (1.4%) were readmitted to the hospital within 30 days of surgery.
Conclusions
Outpatient robotic-assisted minimally invasive surgery is safe and feasible for most gynecologic oncology patients and appears to have a low readmission rate. Older age, preoperative lung disease, and later surgical end time were risk factors for prolonged hospital stay. These patients may benefit from preoperative measures to facilitate earlier discharge.
Objective
The objective of this study was to evaluate the ability of the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) surgical risk calculator to predict complications in gynecologic oncology patients undergoing laparotomy.
Methods
A chart review of patients who underwent laparotomy on the gynecologic oncology service at a single academic hospital from January 2009 to December 2013 was performed. Preoperative variables were abstracted and NSQIP surgical risk scores were calculated. The risk of any complication, serious complication, death, urinary tract infection, venous thromboembolism, cardiac event, renal complication, pneumonia and surgical site infection were correlated with actual patient outcomes using logistic regression. The c-statistic and Brier score were used to calculate the prediction capability of the risk calculator.
Results
Of the 1,094 patients reviewed, the majority were <65 years old (70.9%), independent (95.2%), ASA class 1-2 (67.3%), and overweight or obese (76.1%). Higher calculated risk scores were associated with an increased risk of the actual complication occurring for all events (p<0.05). The calculator performed best for predicting death (c-statistic=0.851, Brier=0.008) and cardiac complications (c-statistic=0.708, Brier=0.011). The calculator did not accurately predict most complications.
Conclusions
The NSQIP surgical risk calculator adequately predicts specific serious complications, such as postoperative death and cardiac complications. However, the overall performance of the calculator was worse for gynecologic oncology patients than reported in general surgery patients. A tailored prediction model may be needed for this patient population.
Intra-operative glove changing prior to abdominal closure during cesarean section significantly reduced the incidence of post-operative wound complications.
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