Clinical Diagnoses in Patients that Underwent Abdominal CT in the Emergency Department

Maria Segev Eyal Klang Shelly Soffer Eli Konen Michal Marianne Amitai
Radiology, Sheba Medical Center, Israel

Purpose: Abdominal CT is an important diagnostic tool in the emergency department (ED). We aimed to investigate what are the most common surgical and non-surgical clinical diagnoses in patients that underwent abdominal CT in the ED of a single large tertiary medical center.

Methods: The records of all adult patients presented to the ED between 1/1/2012 – 31/12/2018 were reviewed.
We evaluated the overall frequency of abdominal CT scan in the ED, both IV contrast and non-IV contrast. We retrieved the International Classification of Diseases, Ninth Revision (ICD-9) ED clinical codes of the patients who underwent CT in the ED. We used the Clinical Classifications Software (CCS) to group the most common ICD-9 coded diagnoses. We divided the CCS diagnoses into surgical and non-surgical groups.

Results: Overall, 17,343/799,522 (2.2%) of adult patients who presented to our ED underwent an abdominal CT (IV contrast 1.7%, non-IV contrast 0.5%). ED ICD-9 clinical diagnoses were available for 15,886/17,343 (91.6%) of the patients.

The most common surgical clinical diagnoses included: appendicitis 1,147 (6.2%), intestinal obstruction without hernia 673 (3.7%), diverticulitis 616 (3.3%), biliary related diagnoses 244 (1.3%) and abdominal hernia 224 (1.2%).

The most common non-surgical clinical diagnoses were: abdominal pain 3,989 (21.7%), nephrolithiasis 2,019 (11.0%), unclassified 1,176 (6.4%), viral infection 849 (4.6%), urinary tract infection 331 (1.8%) and chest pain 259 (1.4%).

Conclusion: Within patients that underwent abdominal CT in the ED the most common surgical clinical diagnoses were appendicitis, intestinal obstruction, diverticulitis and biliary complications.
The most common non-surgical clinical diagnoses were abdominal pain and nephrolithiasis.
Such knowledge is needed as a stepping stone for devising clinical decision protocols.

Maria Segev
Maria Segev








Powered by Eventact EMS