Pseudopancreatitis on computed tomography in a patient with isolated blunt head trauma: a case report
Bibliographic record
Abstract
INTRODUCTION: Computed tomography is commonly used to exclude occult injuries in patients with trauma, but imaging can reveal findings that are of uncertain etiology or clinical significance. We present a case of unsuspected pancreatic abnormality in a female patient with trauma who sustained an isolated blunt head injury. CASE PRESENTATION: A 25-year-old female Caucasian patient sustained massive blunt and penetrating head trauma, secondary to a large object penetrating through the vehicle windshield. Based on the mechanism of injury and clinical evaluation, it was felt to be an isolated head injury. However, computed tomography of her abdomen revealed an occult, intra-abdominal finding of significant pancreatic enlargement and peripancreatic fluid. There was no computed tomography evidence of parenchymal pancreatic laceration. The appearance of her pancreas on computed tomography was identical to that of acute pancreatitis or low-grade pancreatic injury, but her clinical history and laboratory values were not consistent with this, hence the term 'pseudopancreatitis'. Later surgery for organ donation confirmed diffuse pancreatic and peripancreatic edema, but no hematoma, contusion or other evidence for direct traumatic injury. This was an isolated intra-abdominal abnormality. CONCLUSION: The routine use of computed tomography in patients who have sustained trauma has led to increasing detection of unexpected findings. Clinical information such as mechanism of injury and blood work, along with careful evaluation of ancillary imaging findings (or lack of), is important for the provision of an appropriate differential diagnosis. We discuss the possible mechanism and differential diagnosis of an isolated pancreatic abnormality in the setting of non-abdominal trauma, which includes shock pancreas, overhydration, traumatic pancreatic injury and pancreatitis secondary to other etiologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".