Update on managing diaphragmatic rupture in blunt trauma: a review of 208 consecutive cases.
Bibliographic record
Abstract
BACKGROUND: Blunt diaphragmatic rupture (BDR) is a rare event and represents a diagnostic challenge. The purpose of our study was to review our experience with BDR at the Sunnybrook Health Sciences Centre (Sunnybrook), the largest trauma centre in Canada, and to highlight recent changes in the diagnosis and management of the condition. METHODS: We retrospectively reviewed the cases of patients with BDR who were admitted to Sunnybrook between January 1986 and December 2003 using our trauma registry. We performed Student t and Fisher exact tests to compare our findings on patients with BDR with those on the entire cohort of blunt trauma patients admitted to our centre. RESULTS: Most patients with BDR were men (64.4%) with a mean age of 42 years. Left-sided tears were most common (65.0%). Patients with BDR had a very high Injury Severity Score (38) and very high mortality (28.8%). Of those who were injured as a result of motor vehicle collisions (MVCs), a significantly greater percentage of patients in the BDR group than in the entire cohort of blunt trauma patients were drivers or front-seat passengers. Patients with BDR were also significantly less likely to be pedestrians, to have experienced a fall or to be involved in a motorcycle collision. Patients with BDR had a higher chest, abdomen, pelvis and extremity Abbreviated Injury Scale score than all blunt trauma patients in general. Most of our patients underwent laparotomy (93.3%). The most common causes of death among patients with BDR were head injury (25.0%), intra-abdominal bleeding (23.3%) and pelvic hemorrhage (18.3%). CONCLUSION: Blunt diaphragmatic rupture is rare and difficult to diagnose; however, certain MVC characteristics along with severe associated injuries should raise the index of suspicion. These associated injuries include injuries to the head, chest (including the aorta), abdomen and pelvis. Computed tomographic angiography is essential to rule out associated aortic injury and to increase the diagnostic accuracy of BDR.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".