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25.06.2019 | Original Article | Ausgabe 7/2019

Techniques in Coloproctology 7/2019

The REAL (REctal Anastomotic Leak) score for prediction of anastomotic leak after rectal cancer surgery

Zeitschrift:
Techniques in Coloproctology > Ausgabe 7/2019
Autoren:
A. Arezzo, M. Migliore, P. Chiaro, S. Arolfo, C. Filippini, D. Di Cuonzo, R. Cirocchi, M. Morino, REAL Score Collaborators
Wichtige Hinweise
REAL Score Collaborators members are listed in “Acknowledgements” section.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

Background

Anastomotic leak after rectal cancer surgery is a severe complication associated with poorer oncologic outcome and quality of life. Preoperative assessment of the risk for anastomotic leak is a key component of surgical planning, including the opportunity to create a defunctioning stoma.

Objective

The purpose of this study was to identify and quantify the risk factors for anastomotic leak to minimize risk by either not restoring bowel continuity or protecting the anastomosis with a temporary diverting stoma.

Methods

Potentially relevant studies were identified from the following databases: PubMed, Embase and Cochrane Library. This meta-analysis included studies on transabdominal resection for rectal cancer that reported data about anastomotic leak. The risk for anastomotic leak after rectal cancer surgery was investigated. Preoperative, intraoperative, and postoperative factors were extracted and used to compare anastomotic leak rates. All variables demonstrating a p value < 0.1 in the univariate analysis were entered into a multivariate logistic regression model to determine the risk factors for anastomotic leak.

Results

Twenty-six centers provided individual data on 9735 patients. Selected preoperative covariates (time before surgery, age, gender, smoking, previous abdominal surgery, BMI, diabetes, ASA, hemoglobin level, TNM classification stage, anastomotic distance) were used as independent factors in a logistic regression model with anastomotic leak as dependent variable. With a threshold value of the receiver operating characteristics (ROC) curve corresponding to 0.0791 in the training set, the area under the ROC curve (AUC) was 0.585 (p < 0.0001). Sensitivity and specificity of the model’s probability > 0.0791 to identify anastomotic leak were 79.1% and 32.9%, respectively. Accuracy of the threshold value was confirmed in the validation set with 77.8% sensitivity and 35.2% specificity.

Conclusions

We trust that, with further refinement using prospective data, this nomogram based on preoperative risk factors may assist surgeons in decision making. The score is now available online (http://​www.​real-score.​org).

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