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Diagnostic Accuracy of the Combination of Clinical Symptoms and CT or MR Angiography in Patients With Chronic Gastrointestinal Ischemia

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No golden diagnostic standard is available to diagnose chronic gastrointestinal ischemia (CGI).


We aimed to establish an accurate prediction model for CGI, based on clinical symptoms and radiologic evaluation of the amount of stenosis in the celiac artery (CA) and superior mesenteric artery (SMA) by means of computed tomography-angiography or magnetic resonance (MR)-angiography.


We prospectively included 436 consecutive patients with clinical suspicion of CGI in a tertiary referral center. Predictors for CGI were obtained by comparing clinical parameters to the diagnosis of CGI. Multivariable logistic regression was used to combine the strongest predictors in a model. A score chart based on the prediction model was provided to calculate the risk of CGI.


CGI was present in 171/436 (39%) patients (67 y; range, 54 to 74 y; 27% male). Strongest predictors for CGI were female gender [odds ratio (OR)=1.44; 95% confidence interval (CI), 0.85-2.43], weight loss (OR=1.63, 95% CI, 0.98-2.72), concomitant cardiovascular disease (OR=1.70, 95% CI, 1.04-2.78), duration of symptoms (OR=0.88, 95% CI, 0.79-0.99), and stenosis of CA and SMA (50% to 70% stenosis CA: OR=1.33, 95% CI, 0.56-3.19; >70% stenosis CA: OR=5.79, 95% CI, 3.42-9.81; 50% to 70% stenosis SMA: OR=3.21, 95% CI, 0.81-12.74; >70% stenosis SMA: OR=4.39, 95% CI, 2.30-8.41). A model based on clinical symptoms alone showed limited discriminative ability for diagnosing CGI (c-statistic 0.62). Adding radiologic imaging of the mesenteric arteries improved the discriminative ability (c-statistic 0.79).


Clinical symptoms alone are insufficient to predict the risk of CGI. Radiologic evaluation of the mesenteric arteries is essential. This tool may be useful for clinicians to assess the risk of CGI and to decide whether further diagnostic work-up for CGI is needed.
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Keywords: chronic gastrointestinal ischemia; diagnosis; prediction model; radiology

Document Type: Research Article

Affiliations: 1: Departments of Gastroenterology and Hepatology 2: Public Health 3: Departments of Gastroenterology and Hepatology, Department of Gastroenterology and Hepatology, Medisch Spectrum Twente, Enschede, The Netherlands 4: Departments of Gastroenterology and Hepatology, Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam

Publication date: July 1, 2017

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