Early complication detection after colorectal surgery (CONDOR): study protocol for a prospective clinical diagnostic study View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-02

AUTHORS

Verena Kornmann, Bert van Ramshorst, Susan van Dieren, Nanette van Geloven, Marja Boermeester, Djamila Boerma

ABSTRACT

PURPOSE: Anastomotic leakage is one of the most feared complications following colorectal surgery with a high morbidity and mortality rate. Multiple risk factors have been identified, but leakage still occurs. Early detection is crucial in order to reduce morbidity and mortality. The aim of this study is to create a decision algorithm for early detection of anastomotic leakage. METHODS: All patients who undergo elective colorectal surgery for benign or malignant disease are enrolled in this multicenter study. The primary endpoint is the accuracy of the prediction of anastomotic leakage. The main study parameter is the occurrence of postoperative anastomotic leakage. Secondary study parameters are clinical (vital) parameters, additional laboratory or radiology examination, other complications, mortality, re-intervention, duration of hospital and intensive care stay, emergency room visits, readmission to the hospital and total costs. Daily physical examination and each step in clinical decision making will be evaluated prospectively in a standardized manner. The focus of the analysis will be on the added value of diagnostic tools, such as laboratory results and imaging studies, over physical examination by using logistic regression and decision tree analysis. CONCLUSION: This study aims to develop an optimal diagnostic algorithm that can act as a guideline for surgeons or surgical residents to early identify patients with anastomotic leakage after colorectal surgery. More... »

PAGES

459-464

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00384-015-2468-3

DOI

http://dx.doi.org/10.1007/s00384-015-2468-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1001321400

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26670674


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