Challenges in diagnosing abdominal pain after bariatric surgery

With the increasing prevalence of obesity, the number of bariatric procedures being performed is also rising. However, these procedures carry risks and potential complications, with abdominal pain being a common complaint. This thesis provides insight into the diagnostic approaches undertaken for abdominal pain and the resulting diagnoses. In addition, it examines both the existing literature and findings from a cohort study on the improvement of abdominal pain following reoperation for these complaints. Finally, this thesis explores methods to improve the diagnostic process for abdominal pain.
Internal herniation is often the primary concern in patients with a history of a gastric bypass and is typically evaluated using abdominal CT imaging. One study demonstrated that standardized assessment models can improve the interpretation of abdominal CT scans. Moreover, a clinical decision tree was developed to exclude internal herniation as a possible diagnosis using machine learning techniques, incorporating patient history, clinical presentation, and physical examination findings.
Overall, this thesis contributes to a better understanding of the diagnostic pathways and diagnostic accuracy in patients presenting with abdominal pain after bariatric surgery, and outlines potential strategies for further improvement in the future.