Should surgeon-performed intraoperative ultrasound be the preferred test for detecting main pancreatic duct injuries in operative trauma cases?
Bibliographic record
Abstract
BACKGROUND: The diagnostic performance of multiple tests for detecting the presence of a main pancreatic duct injury remains poor. Given the central importance of main duct integrity for both subsequent treatment algorithms and patient outcomes, poor test reliability is problematic. The primary aim was to evaluate the comparative test performance of computed tomography (CT), magnetic resonance cholangiopancreatography (MRCP), endoscopic retrograde cholangiopancreatography (ERCP), and intraoperative ultrasound (IOUS) for detecting main pancreatic duct injuries. METHODS: All severely injured adult patients with pancreatic trauma (2010-2021) were evaluated. Patients who received an IOUS pancreas-focused evaluation, with Grades III, IV, and V injuries (main duct injury) were compared with those with Grade I and Grade II trauma (no main duct injury). Test performances were analyzed. RESULTS: Of 248 pancreatic injuries, 74 underwent an IOUS. The additional mix of diagnostic studies (CT, MRCP, ERCP) was variable across grade of injury. Of these 74 IOUS cases for pancreatic injuries, 48 (64.8%) were confirmed as Grades III, IV, or V main duct injuries. The patients were predominantly young (median age = 33, IQR:21-45) blunt injured (70%) males (74%) with severe injury demographics (injury severity score = 28, (IQR:19-36); 30% hemodynamic instability; 91% synchronous intra-abdominal injuries). Thirty-five percent of patients required damage-control surgery. Patient outcomes included a median 13-day hospital length of stay and 1% mortality rate. Test performance was variable across groups (CT = 58% sensitive/77% specific; MRCP = 71% sensitive/100% specific; ERCP = 100% sensitive; IOUS = 98% sensitive/100% specific). CONCLUSION: Intraoperative ultrasound is a highly sensitive and specific test for detecting main pancreatic duct injuries. This technology is simple to learn, readily available, and should be considered in patients who require concurrent non-damage-control abdominal operations. LEVEL OF EVIDENCE: Diagnostic Test/Criteria; Level III.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".