Imaging of Blunt Pancreatic Trauma: A Systematic Review
Bibliographic record
Abstract
PURPOSE: Despite several published reports on the value of imaging in acute blunt pancreatic trauma, there remains a large variability in the reported performance of ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI). The purpose of this study is to present a systematic review on the utility of these imaging modalities in the acute assessment of blunt pancreatic trauma. In addition, a brief overview of the various signs of pancreatic trauma will be presented. METHODS: Keyword search was performed in MEDLINE, EMBASE, and Web of Science databases for relevant studies in the last 20 years (1999 onward). Titles and abstracts were screened, followed by full-text screening. Inclusion criteria were defined as studies reporting on the effectiveness of imaging modality (US, CT, or MRI) in detecting blunt pancreatic trauma. RESULTS: After initial search of 743 studies, a total of 37 studies were included in the final summary. Thirty-six studies were retrospective in nature. Pancreatic injury was the primary study objective in 21 studies. Relevant study population varied from 5 to 299. Seventeen studies compared the imaging findings against intraoperative findings. Seven studies performed separate analysis for pancreatic ductal injuries and 9 studies only investigated ductal injuries. The reported sensitivities for the detection of pancreatic injuries at CT ranged from 33% to 100% and specificity ranged from 62% to 100%. Sensitivity at US ranged from 27% to 96%. The sensitivity at MRI was only reported in 1 study and was 92%. CONCLUSION: There remains a large heterogeneity among reported studies in the accuracy of initial imaging modalities for blunt pancreatic injury. Although technological advances in imaging equipment would be expected to improve accuracy, the current body of literature remains largely divided. There is a need for future studies utilizing the most advanced imaging equipment with appropriately defined gold standards and outcome measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".