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J. Gastrointest. Surg. · Jun 2016
Comparative StudyComparison of Risk Factors for Unplanned Conversion from Laparoscopic and Robotic to Open Colorectal Surgery Using the Michigan Surgical Quality Collaborative (MSQC) Database.
- Anuradha R Bhama, Abdullah M Wafa, Jane Ferraro, Stacey D Collins, Andrew J Mullard, James F Vandewarker, Greta Krapohl, John C Byrn, and Robert K Cleary.
- Department of Surgery, Division of Colon and Rectal Surgery, St. Joseph Mercy Health System-Ann Arbor, 5325 Elliott Dr, MHVI Suite #104, Ann Arbor, MI, 48106, USA. anuradha.bhama@gmail.com.
- J. Gastrointest. Surg. 2016 Jun 1; 20 (6): 1223-30.
AbstractRobotic colorectal surgery has been shown to have lower rates of unplanned conversion to open surgery when compared to laparoscopic surgery. Risk factors associated with conversion from robotic to open colectomy and comparisons of the risk factors between robotic and laparoscopic approaches have not been previously reported. Patients who underwent elective laparoscopic and robotic colorectal surgeries between July 1, 2012 and April 28, 2015, were identified in the Michigan Surgical Quality Collaborative registry. Candidate covariates were identified, and hierarchical logistic regression models were used to identify risk factors for conversion. There were 4796 cases that met study inclusion criteria. Conversion was required in 18.2 % of laparoscopic and 7.7 % of robotic cases (p < 0.0001). Risk factors for conversion in the laparoscopic group included the following: moderate/severe adhesions, obesity, colorectal cancer, hypertension, rectal operations, urgent priority, and tobacco use. Risk factors for conversion in the robotic group included the following: severe adhesions, bleeding disorder, presence of cancer, cirrhosis, and use of statins. Higher surgeon volume was protective in both groups. Conversion rates are lower for robotic than for laparoscopic colorectal surgery with fewer predictors of conversion. Recognition of factors predicting conversion may allow surgeons to choose an operative approach that optimizes the benefits of the available technologies.
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