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A clinical and radiographic model to predict surgery for acute small bowel obstruction in Crohn’s disease

Authors :
Alec J. Megibow
David Hudesman
Shannon Chang
Justin M. Ream
Hua Zhong
Bari Dane
Lisa Malter
Brian P. Bosworth
Yuhe Xia
Sarina C. Lowe
Source :
Abdominal Radiology. 45:2663-2668
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

For more than half of Crohn’s disease patients, strictures will cause bowel obstructions that require surgery within 10 years of their initial diagnosis. This study utilizes computed tomography imaging and clinical data obtained at the initial emergency room visit to create a prediction model for progression to surgery in Crohn’s disease patients with acute small bowel obstructions. A retrospective chart review was performed for patients who presented to the emergency room with an ICD-10 diagnosis for Crohn’s disease and visit diagnosis of small bowel obstruction. Two expert abdominal radiologists evaluated the CT scans for bowel wall thickness, maximal and minimal luminal diameters, length of diseased segment, passage of oral contrast, evidence of penetrating disease, bowel wall hyperenhancement or stratification, presence of a comb sign, fat hypertrophy, and small bowel feces sign. The primary outcome was progression to surgery within 6 months of presentation. The secondary outcome was time to readmission. Forty patients met the inclusion criteria, with 78% receiving medical treatment alone and 22% undergoing surgery within 6 months of presentation to the emergency room. Multivariable analysis produced a model with an AUC of 92% (95% CI 0.82–1.00), 78% sensitivity, and 97% specificity, using gender, body mass index, and the radiographic features of segment length, penetrating disease, and bowel wall hyperenhancement. The model demonstrates that routine clinical and radiographic data from an emergency room visit can predict progression to surgery, and has the potential to risk stratify patients, guide management in the acute setting, and predict readmission.

Details

ISSN :
23660058 and 2366004X
Volume :
45
Database :
OpenAIRE
Journal :
Abdominal Radiology
Accession number :
edsair.doi.dedup.....a8b753a3b3053aec5b90823569466b6a
Full Text :
https://doi.org/10.1007/s00261-020-02514-6