Are We Missing Traumatic Bowel and Mesenteric Injuries?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Traumatic bowel and mesenteric injury (TBMI), although an uncommon entity, can be lethal if not detected and treated in a timely manner. The purpose of our study was to evaluate the diagnostic accuracy of 64-slice multidetector computed tomography (MDCT) for the detection of TBMI in patients at our level 1 trauma centre. METHODS: We used our hospital's trauma registry to identify patients with a diagnosis of TBMI from January 1, 2006, to June 30, 2013. Only patients who had a 64-slice MDCT scan at presentation and subsequently underwent laparotomy or laparoscopy were included in the study cohort. Using the surgical findings as the gold standard, the accuracy of prospective radiology reports was analyzed. RESULTS: Of the 4781 trauma patients who presented to our institution, 44 (0.92%) had surgically proven TBMI. Twenty-two of 44 were excluded as they did not have MDCT before surgery. The study cohort consisted of 14 males and 8 females with a median age of 41.5 years and a median injury severity score of 27. In total 17 of 22 had blunt trauma and 5 of 22 had penetrating injury. A correct preoperative imaging diagnosis of TBMI was made in 14 of 22 of patients. The overall sensitivity of the radiology reports was 63.6% (95% confidence interval [CI]: 41%-82%), specificity was 79.6% (95% CI: 67%-89%), PPV was 53.9% (95% CI: 33%-73%), and the NPV was 85.5% (95% CI: 73%-94%). Accuracy was calculated at 75.3%. However, only 59% (10 of 17) of patients with blunt injury had a correct preoperative diagnosis. Review of the findings demonstrated that majority of patients with missed blunt TBMI (5 of 7) demonstrated only indirect signs of injury. CONCLUSION: The detection of TBMI in trauma patients on 64-slice MDCT can be improved, especially in patients presenting with blunt injury. Missed cases in this population occurred because the possibility of TBMI was not considered despite the presence of indirect imaging signs. The prospective diagnosis of TBMI remains challenging despite advances in CT technology and widespread use of 64-slice MDCT.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it