Zgheib H, Wakil C, Shayya S, Kanso M, Bou Chebl R, Bachir R, El Sayed M. Retrospective cohort study on clinical predictors for acute abnormalities on CT scan in adult patients with abdominal pain.
Eur J Radiol Open 2020;
7:100218. [PMID:
33102637 PMCID:
PMC7569409 DOI:
10.1016/j.ejro.2020.01.007]
[Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 01/09/2020] [Accepted: 01/17/2020] [Indexed: 12/12/2022] Open
Abstract
PURPOSE
Identification of clinical predictors of acute and surgical pathologies on abdominal CT in patients with non-traumatic abdominal pain (NTAP).
METHODS
Retrospective chart review cohort study of adults who had abdominal CT scans for investigation of NTAP in the Emergency Department in a tertiary care center in Lebanon. Multivariate analyses were performed to identify predictors of pathologies on CT scan.
RESULTS
This study included 147 patients who had abdominal CT scans for NTAP. Mean age was 39.8 ± 15.1 years and 58.5 % of patients were females. Less than half (44.9 %) had normal scans. Women had significantly higher rates of normal scans compared to males. Right lower quadrant (RLQ) tenderness was associated with significantly higher odds of having acute abnormalities on CT and of having surgical diagnoses, while epigastric tenderness was negatively associated with these two outcomes. Right and left upper quadrants and diffuse abdominal tenderness, and an abnormal neutrophil count were found to be associated with surgical diagnoses on CT.
CONCLUSIONS
Women are less likely to have acute and surgical pathologies on CT ordered for non traumatic abdominal pain. Epigastric tenderness is negatively associated with abnormal and surgical CT results while RLQ tenderness is associated with an abnormal CT that is likely surgical in nature. These findings should help improve diagnostic accuracy of ordering providers and improve resource utilization.
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