The role of clinical presentation in predicting positive findings on whole-body computed tomography in patients presenting to the emergency department with high-energy trauma

Whole-body computed tomography (WBCT) is increasingly used in the evaluation of high-energy trauma patients; however, this approach exposes patients to unnecessary radiation and leads to the detection of many lesions that are clinically insignificant. Clinical gestalt, the numerically expressed form of physician intuition, may help differentiate patients who truly benefit from WBCT. The aim of this study is to evaluate the performance of clinical gestalt in predicting WBCT findings and clinically significant injuries in hemodynamically stable adults presenting with high-energy blunt trauma. A prospective observational study was conducted at a tertiary care emergency department between 1 March 2024 and 28 February 2025. Adults aged 18 years or older with high-energy blunt trauma, a Glasgow Coma Scale of 13 – 15 and a systolic blood pressure >90 mmHg were included. Demographic data, mechanism of injury, vital signs, physical examination findings, and physicians' gestalt assessments (0 – 10 estimates recorded using a VAS [Visual Analogue Scale]) were documented. WBCT findings were classified as positive or negative; those requiring surgery, ward admission or intensive care within 48 hours were defined as clinically significant. Multivariable logistic regression identified predictors of WBCT findings and hospital admissions; receiver operating characteristic (ROC) analysis evaluated VAS performance. Of the 196 patients (mean age 38.9 ± 18.0 years; 70.9% male), at least one WBCT finding was detected in 35.7%. WBCT findings were concentrated in the thoracic (22.4%), cranial (11.7%), vertebral (8.7%) and abdominal (6.6%) regions. Clinically significant WBCT findings were observed in 14.3% overall; among these, thoracic injuries accounted for 7.1%, cranial and abdominal injuries 4.6% each and vertebral injuries 1.5%. Most patients were discharged (75.0%), while 14.3% were admitted to the ward, 7.1% to the intensive care unit and only 0.5% required early surgical intervention. Patients with findings on WBCT had higher respiratory rates and shock indices, higher VAS scores and a higher frequency of abnormal physical examination findings and comorbidity. Multivariable analyses identified increased respiratory rate, high VAS score, presence of a physical examination finding and a history of chronic disease as independent predictors of findings on WBCT. Base excess was the only independent predictor of hospital admission. ROC analysis showed that the VAS-WBCT distinguished WBCT findings with moderate performance (AUC ≈ 0.80). ROC analyses revealed that the VAS-WBCT score is a strong determinant in predicting both the presence of findings on WBCT and the need for admission. For predicting the presence of WBCT findings, the VAS-WBCT 2.45 threshold value stood out, offering high specificity (89.7% Specificity). The most significant contribution to the clinical decision-making process was provided by the results obtained in predicting the need for admission: the VAS-WBCT 1.45 threshold value yielded an extremely high negative predictive value (NPV) of 95.1%. This finding suggests that for patients with a VAS-WBCT score below 1.45, the risk of a severe injury requiring admission is statistically very low, thereby providing a crucial tool to support safe discharge decisions in the emergency physician's clinical practice. Clinical gestalt provides a moderate ability to predict positive and clinically significant WBCT findings in hemodynamically stable highenergy trauma patients. Although higher VAS scores and abnormal vital signs are associated with a greater likelihood of WBCT results, the predictive power of gestalt alone is insufficient to safely avoid WBCT. To prevent missing clinically significant injuries, WBCT remains an essential part of trauma evaluation; however, decision algorithms that integrate gestalt with objective clinical parameters may help reduce unnecessary imaging and optimise patient safety and resource use.