Back

Assessment of WBCT Use in Trauma Patients: A National audit for Radiology Resource Management and Limiting Radiation Exposure

Alkandari, L.; Masoomi, M. A.; El Gargani, A. E. G.; Hamza, M. A.; Agha, R. M.

2025-04-10 radiology and imaging
10.1101/2025.04.09.25325527 medRxiv
Show abstract

IntroductionWhole-body computed tomography (WBCT) is often indiscriminately used in trauma cases. This study aimed to assess the effective use of WBCT in trauma patients across emergency departments in State of Kuwait, evaluate the true incidence of critical injuries, and minimize unnecessary radiation exposure. MethodsThis multicenter, retrospective study across seven radiology departments included 1,367 trauma patients who underwent WBCT between 2022 and 2023, according to the American College of Radiology guidelines. Data on age, sex, injury mechanism, clinical indications, dose-length product, and WBCT findings were collected and analyzed using IBM SPSS version 25. ResultsOf 1,367 referrals, 578 (42.3%) had no significant findings, while 789 (57.7%) showed positive trauma-related results. Among the positive findings, 530 patients (38.8%) had major injuries, including solid organ and vertebral column injuries. The most common causes of WBCT referrals were road traffic accidents (RTAs) (911 patients, 66.6%), falls from height (FFH) (182 patients, 13%), falls of heavy objects (112 patients, 8%), head trauma (82 patients, 6%), buggy accidents (28 patients, 2%) and others. Negative WBCT findings had a mean effective dose (ED) of 19.98 {+/-} 10.26 mSv. ConclusionsPositive WBCT findings were seen in 57.7% of cases, but the 42.3% negative findings rate, was significantly higher than the 20.4% average reported in similar centers in Europe such as UK and Germany, which highlights the need to optimize WBCT usage in emergency department to reduce unnecessary scans and minimize radiation exposure.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.