Role of multislice computed tomography in evaluation and management of intestinal obstruction
AbstractThe aims and objectives of this study were: i) to evaluate the efficacy of computed tomography (CT) imaging in diagnosing the presence, level, degree, and cause of intestinal obstruction, and the role of CT in detecting presence of complications; ii) to assess impact of CT in decision making and management (surgical/conservative); iii) to correlate CT findings with intra operative findings whenever possible. A prospective study of 40 patients presented in outpatient/emergency department with features suggestive of intestinal obstruction. Multislice contrast enhanced computed tomography of whole abdomen was done in all patients after preliminary investigations. Whenever indicated, patients were explored. Statistical analysis was performed to determine the efficacy of multidetector computed tomography (MDCT) in diagnosing intestinal obstruction and its complications. Out of 40, 30 patients underwent exploratory laparotomy and it was found that MDCT was 85% sensitive and 70% specific in diagnosing bowel obstruction. Association between MDCT findings suggestive of obstruction and intra-operative findings turn out to be significant (P=0.003). MDCT findings were consistent with intraoperative findings in 22 out of 30 patients (73%). MDCT is sensitive and specific in determining the presence of bowel obstruction and should be recommended for patients with suspected bowel obstruction because it affects outcome in these patients.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2013 Durgesh Kumar Saini, Poras Chaudhary, Chikkala Kanak Durga, Kiran Saini
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.