Learning curve for robotic-assisted laparoscopic colorectal surgery.

BACKGROUND: Robotic-assisted laparoscopic surgery (RALS) is evolving as an important surgical approach in the field of colorectal surgery. We aimed to evaluate the learning curve for RALS procedures involving resections of the rectum and rectosigmoid. METHODS: A series of 50 consecutive RALS procedures were performed between August 2008 and September 2009. Data were entered into a retrospective database and later abstracted for analysis. The surgical procedures included abdominoperineal resection (APR), anterior rectosigmoidectomy (AR), low anterior resection (LAR), and rectopexy (RP). Demographic data and intraoperative parameters including docking time (DT), surgeon console time (SCT), and total operative time (OT) were analyzed. The learning curve was evaluated using the cumulative sum (CUSUM) method. RESULTS: The procedures performed for 50 patients (54% male) included 25 AR (50%), 15 LAR (30%), 6 APR (12%), and 4 RP (8%). The mean age of the patients was 54.4 years, the mean BMI was 27.8 kg/m(2), and the median American Society of Anesthesiologists (ASA) classification was 2. The series had a mean DT of 14 min, a mean SCT of 115.1 min, and a mean OT of 246.1 min. The DT and SCT accounted for 6.3% and 46.8% of the OT, respectively. The SCT learning curve was analyzed. The CUSUM(SCT) learning curve was best modeled as a parabola, with equation CUSUM(SCT) in minutes equal to 0.73 × case number(2) - 31.54 × case number - 107.72 (R = 0.93). The learning curve consisted of three unique phases: phase 1 (the initial 15 cases), phase 2 (the middle 10 cases), and phase 3 (the subsequent cases). Phase 1 represented the initial learning curve, which spanned 15 cases. The phase 2 plateau represented increased competence with the robotic technology. Phase 3 was achieved after 25 cases and represented the mastery phase in which more challenging cases were managed. CONCLUSIONS: The three phases identified with CUSUM analysis of surgeon console time represented characteristic stages of the learning curve for robotic colorectal procedures. The data suggest that the learning phase was achieved after 15 to 25 cases.

Risk factors for surgical site infections among patients undergoing major colon surgery in the United States 2007-2009

Background: Surgical site infections (SSIs) after abdominal surgeries account for approximately 26% of all reported SSIs. The Center for Disease Control and Prevention (CDC) defines 3 types of SSIs: superficial incisional, deep incisional, and organ/space. Preventing SSIs has become a national focus. This dissertation assesses several associations with the individual types of SSI in patients that have undergone colon surgery. ^ Methods: Data for this dissertation was obtained from the American College of Surgeons' National Surgical Quality Improvement Program (NSQIP); major colon surgeries were identified in the database that occurred between the time period of 2007 and 2009. NSQIP data includes more than 50 preoperative and 30 intraoperative factors; 40 collected postoperative occurrences are based on a follow-up period of 30 days from surgery. Initially, four individual logistic regressions were modeled to compare the associations between risk factors and each of the SSI groups: superficial, deep, organ/space and a composite of any single SSI. A second analysis used polytomous regression to assess simultaneously the associations between risk factors and the different types of SSIs, as well as, formally test the different effect estimates of 13 common risk factors for SSIs. The final analysis explored the association between venous thromboembolism (VTEs) and the different types of SSIs and risk factors. ^ Results: A total of 59,365 colon surgeries were included in the study. Overall, 13% of colon cases developed a single type of SSI; 8% of these were superficial SSIs, 1.4% was deep SSIs, and 3.8% were organ/space SSIs. The first article identifies the unique set of risk factors associated with each of the 4 SSI models. Distinct risk factors for superficial SSIs included factors, such as alcohol, chronic obstructive pulmonary disease, dyspnea and diabetes. Organ/space SSIs were uniquely associated with disseminated cancer, preoperative dialysis, preoperative radiation treatment, bleeding disorder and prior surgery. Risk factors that were significant in all models had different effect estimates. The second article assesses 13 common SSI risk factors simultaneously across the 3 different types of SSIs using polytomous regression. Then each risk factor was formally tested for the effect heterogeneity exhibited. If the test was significant the final model would allow for the effect estimations for that risk factor to vary across each type of SSI; if the test was not significant, the effect estimate would remain constant across the types of SSIs using the aggregate SSI value. The third article explored the relationship of venous thromboembolism (VTE) and the individual types of SSIs and risk factors. The overall incidence of VTEs after the 59,365 colon cases was 2.4%. All 3 types of SSIs and several risk factors were independently associated with the development of VTEs. ^ Conclusions: Risk factors associated with each type of SSI were different in patients that have undergone colon surgery. Each model had a unique cluster of risk factors. Several risk factors, including increased BMI, duration of surgery, wound class, and laparoscopic approach, were significant across all 4 models but no statistical inferences can be made about their different effect estimates. These results suggest that aggregating SSIs may misattribute and hide true associations with risk factors. Using polytomous regression to assess multiple risk factors with the multiple types of SSI, this study was able to identify several risk factors that had significant effect heterogeneity across the 3 types of SSI challenging the use of aggregate SSI outcomes. The third article recognizes the strong association between VTEs and the 3 types of SSIs. Clinicians understand the difference between superficial, deep and organ/space SSIs. Our results indicate that they should be considered individually in future studies.^