BACKGROUND & AIMS: The diagnosis of chronic gastrointestinal ischemia (CGI) remains a clinical challenge. We aimed to assess the diagnostic value of clinical features, visualization of the gastrointestinal arteries, and evaluation of mucosal perfusion in patients clinically suspected of CGI. METHODS: A total of 186 patients referred for suspicion of CGI were prospectively included and followed up. All patients had an extensive diagnostic work-up, including visualization of the gastrointestinal arteries with computed tomography, magnetic resonance, or conventional angiography, and mucosal perfusion with tonometry. The reference standard for CGI was persistent clinical response after adequate therapy. The diagnostic value of individual and combined tests was assessed with multivariable logistic regression analysis. RESULTS: A total of 116 (62%) patients were diagnosed with CGI. In a multivariable model solely based on clinical features, the strongest predictors for CGI were the presence of postprandial pain, weight loss per month in kilograms, concomitant cardiovascular disease, and presence of an abdominal bruit. However, this model showed limited discriminative ability for the presence or absence of CGI (c-statistic, 0.62). Adding radiologic imaging to the prediction model improved the discriminative ability substantially (c-statistic, 0.81). Adding tonometry to the prediction model further improved the discriminative ability of the model (c-statistic, 0.90). The combination of clinical features and tonometry with a c-statistic of 0.88 approximated the discriminative ability of the latter model. CONCLUSIONS: Clinical features alone have a limited value to assess CGI correctly. Visualization of the gastrointestinal arteries and evaluation of mucosal perfusion substantially improve the diagnosis of CGI. The strongest diagnostic contribution comes from mucosal perfusion assessment.
BACKGROUND & AIMS: The diagnosis of chronic gastrointestinal ischemia (CGI) remains a clinical challenge. We aimed to assess the diagnostic value of clinical features, visualization of the gastrointestinal arteries, and evaluation of mucosal perfusion in patients clinically suspected of CGI. METHODS: A total of 186 patients referred for suspicion of CGI were prospectively included and followed up. All patients had an extensive diagnostic work-up, including visualization of the gastrointestinal arteries with computed tomography, magnetic resonance, or conventional angiography, and mucosal perfusion with tonometry. The reference standard for CGI was persistent clinical response after adequate therapy. The diagnostic value of individual and combined tests was assessed with multivariable logistic regression analysis. RESULTS: A total of 116 (62%) patients were diagnosed with CGI. In a multivariable model solely based on clinical features, the strongest predictors for CGI were the presence of postprandial pain, weight loss per month in kilograms, concomitant cardiovascular disease, and presence of an abdominal bruit. However, this model showed limited discriminative ability for the presence or absence of CGI (c-statistic, 0.62). Adding radiologic imaging to the prediction model improved the discriminative ability substantially (c-statistic, 0.81). Adding tonometry to the prediction model further improved the discriminative ability of the model (c-statistic, 0.90). The combination of clinical features and tonometry with a c-statistic of 0.88 approximated the discriminative ability of the latter model. CONCLUSIONS: Clinical features alone have a limited value to assess CGI correctly. Visualization of the gastrointestinal arteries and evaluation of mucosal perfusion substantially improve the diagnosis of CGI. The strongest diagnostic contribution comes from mucosal perfusion assessment.
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Authors: Luke G Terlouw; Adriaan Moelker; Jan Abrahamsen; Stefan Acosta; Olaf J Bakker; Iris Baumgartner; Louis Boyer; Olivier Corcos; Louisa Jd van Dijk; Mansur Duran; Robert H Geelkerken; Giulio Illuminati; Ralph W Jackson; Jussi M Kärkkäinen; Jeroen J Kolkman; Lars Lönn; Maria A Mazzei; Alexandre Nuzzo; Felice Pecoraro; Jan Raupach; Hence Jm Verhagen; Christoph J Zech; Desirée van Noord; Marco J Bruno Journal: United European Gastroenterol J Date: 2020-04-16 Impact factor: 4.623