View clinical trials related to Small Bowel Obstruction.
Filter by:The goal of this prospective observational study is to evaluate the diagnostic and therapeutic utility of an enteral contrast challenge for pediatric patients with adhesive small bowel obstruction (ASBO). The aims are to 1. Determine if an enteral contrast challenge is safe in the evaluation of children with ASBO 2. Determine if an enteral contrast challenge decreases the need for operation among children with ASBO Children with ASBO who are cared for at one of 9 participating sites who undergo a trial of non operative management will be observed. Comparisons will be made between those who receive and enteral contrast challenge and those who do not. Outcomes to be evaluated include adverse events related to the contrast, rate of operative intervention, and hospital length of stay.
Small bowel obstruction (SBO) is a common non-traumatic surgical emergency. All guidelines recommend computed tomography (CT) as the first-line imaging test for patients with suspected SBO. The objectives of CT are multiple: (i) to confirm or refute the diagnosis of GI obstruction, defined as distension of the digestive tracts greater than 25 mm, and, when SBO is present, (ii) to confirm the mechanism (mechanical vs. functional), (iii) to localize the site of obstruction, i.e., the transition zone (TZ), (iv) to identify the cause, and (v) to look for complications such as strangulation or perforation, influencing management. Given the exponential increase in the number of scans being performed, especially in the setting of emergency management, methods to assist the radiologist would be useful to: 1. Sort the scans performed, allowing prioritization of the analysis of scans with a higher probability of pathology (occlusion in our case) 2. Help the radiologist to diagnose occlusion and its type (functional or mechanical), and to identify signs of severity. 3. To help the emergency physician and the digestive surgeon to make a decision on the management of the disease (surgical or medical). Machine learning has developed rapidly over the last decades, first thanks to the increase in data storage capacities, then thanks to the arrival of parallel processing hardware based on graphic processing units, in the context of radiological diagnostic assistance. Consequently, the number of studies on deep neural networks in medical imaging is increasing rapidly. However, few teams focus on SBO. The only published classification models have been produced for standard abdominal radiographs. No studies have used CT or 3D models, apart from our preliminary study on ZTs, despite the recognized advantages of CT for the diagnosis of SBO and the likely contribution of 3D models, which may be comparable to that of multiplanar reconstruction for the analysis of images in multiple planes of space.
This study has two segments the first is a chart and outcome assessment of patients treated at Clear Passage (CP) with a history of small bowel obstruction (SBO). These patients have completed multiple questionnaires as a standard of care for outcome monitoring in the clinic setting, no new data will be collected. The second segment is a prospective observational, online questionnaire based study of subjects with a history of SBO not treated at CP. Data on the impact of quality of life (QOL) over time of subjects not treated at CP will be assessed using the same questionnaire used as standard of care in the clinic twice, 90 days apart. This will be accomplished using the NIH Assessment Center, with subjects able to complete the questionnaires with ease via the internet. As this segment is observational, there is minimal risk to these subjects. The data obtained from the untreated subjects will allow for reporting of overall impact on QOL in this population, data that is not available, as well as provide a control group for assessment of improvement for interventions for SBO.