Abstract
Background
Anastomotic leak is a feared complication after left-sided colectomy, but its risk can potentially be reduced with the use of a diverting ostomy. However, an ostomy has its own associated negative sequelae; therefore, it is critical to appropriately identify patients to divert. This is difficult in practice since many risk factors for anastomotic leak exist and outside factors bias this decision. We aimed to develop and validate a risk score to predict an individual’s risk of anastomotic leak and aid in the decision.
Methods
The American College of Surgeons National Surgical Quality Improvement Program Colectomy Targeted PUF was queried from 2012 to 2016 for patients undergoing elective left-sided resection for malignancy, benign neoplasm, or diverticular disease. Multivariable logistic regression identified predictors of anastomotic leak in non-diverted patients, and a risk score was developed and validated.
Results
38,475 patients underwent resection with an overall anastomotic leak rate of 3%. Independent risk factors for anastomotic leak included younger age, male sex, tobacco use, and omission of combined bowel preparation. A risk score incorporating independent predictors demonstrated excellent calibration. There was strong visual correspondence between predicted and observed anastomotic leak rates. 3960 patients underwent resection with diversion, yet over half of these patients had a predicted leak rate of less than 4%.
Conclusion
A novel risk score can be used to stratify patients according to anastomotic leak risk after elective left-sided resection. Intraoperative calculation of scores for patients can help guide surgical decision-making in both diverting the highest risk patients and avoiding diversion in low-risk patients.
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Acknowledgments
The Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery provides salary support for Dr. Habermann and Ms. Bews and in kind support for Dr. McKenna. Dr. McKenna receives salary support from the Mayo Clinic Clinical Investigator Training Program. These funding sources did not affect our investigation.
Funding
This publication was made possible by CTSA Grant Number UL1 TR002379 from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH).
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Nicholas McKenna—conception and design of the work, interpretation of the data for the work, drafting of the work, final approval of the version to be published, and agree to be held accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Katherine Bews—acquisition and analysis of the data for the work, revising it critically for important intellectual content, final approval of the version to be published, and agree to be held accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Robert Cima—interpretation of the data for the work, revising it critically for important intellectual content, final approval of the version to be published, and agree to be held accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Cynthia Crowson—analysis and interpretation of the data for the work, revising it critically for important intellectual content, final approval of the version to be published, and agree to be held accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Elizabeth Habermann—conception and design of the work, interpretation of the data for the work, revising it critically for important intellectual content, final approval of the version to be published, and agree to be held accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
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McKenna, N.P., Bews, K.A., Cima, R.R. et al. Development of a Risk Score to Predict Anastomotic Leak After Left-Sided Colectomy: Which Patients Warrant Diversion?. J Gastrointest Surg 24, 132–143 (2020). https://doi.org/10.1007/s11605-019-04293-y
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DOI: https://doi.org/10.1007/s11605-019-04293-y