Blunt Vascular Trauma in the Extremity: Diagnosis, Management, and Outcome
Bibliographic record
Abstract
BACKGROUND: Blunt vascular trauma in an extremity is an uncommon diagnosis. Considering the complexity of these injuries, it is worthwhile to determine how select factors affect the outcome of the limb and the patient. The objectives of this study were to review the diagnosis, management, and outcomes of patients who sustained blunt vascular injuries in the extremities and relate factors in their treatment to the outcome of the injured extremity. METHODS: A retrospective review of data on adult and pediatric patients who had a diagnosis of blunt vascular injury in an extremity and underwent some attempt at restoration of vascular flow was conducted. RESULTS: From January 1995 to December 2002, 62 patients (80.3% male; mean age, 33.2 +/- 15.8 years) sustained blunt trauma (mean Injury Severity Score, 14.6 +/- 8.4), with 93 vascular injuries in 65 extremities (16 upper and 49 lower). Hard signs of vascular injury occurred in 41 (66%) patients. An associated fracture and/or dislocation was present in 59 patients (95%). Preoperative arteriograms were obtained in 20 patients (17 occlusions, 2 embolizations, and 1 untreated). Vessel injuries were as follows: 16 upper (brachial artery, 50%) and 63 lower (tibial/peroneal/popliteal, 84%), with ligation being the most common treatment in the latter. Intravascular shunts were used to restore blood flow in 18 vessels (13 arteries and 5 veins) in 13 patients. Delays in diagnosis or treatment occurred in six patients, mostly because of errors in management/judgment. Delayed or late fasciotomies were performed in six patients, and five developed rhabdomyolysis. Six patients died. The age (p = 0.0006), Injury Severity Score (p = 0.0007), and Mangled Extremity Severity Score (p = 0.0009) were significantly different for the survivors compared with the nonsurvivors. CONCLUSION: Blunt vascular injuries in the lower extremities occur most commonly in the anteroposterior tibial arteries; injured arteries in the proximal upper and lower extremity require resection with interposition grafting, whereas those in the forearm or calf are usually ligated; the amputation rate in 65 injured extremities with blunt vascular trauma was 18.%, which is at least three times that for those who sustain penetrating injury; and delays in diagnosis and treatment are uncommon in these patients with multiple injuries.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".