Dynamic Wound Closure for Decompressive Leg Fasciotomy Wounds
Bibliographic record
Abstract
Decompressive fasciotomy for preservation of lower extremity function and salvage is an essential technique in trauma. The wounds that result from the standard two incision four-compartment leg fasciotomy are often accompanied by a wide soft tissue opening that in the face of true compartment syndrome are often impossible to close in a delayed primary fashion. We describe a technique using a device that allows for dissipation of the workload across the wound margin allowing for successful delayed primary closure. Consecutive patients who presented to the 28th Combat Support Hospital in Baghdad, Iraq with a diagnosis of compartment syndrome of the leg, impending compartment syndrome of the leg, or compartment syndrome of the leg recently treated with fasciotomies were followed. All patients underwent placement of the Canica dynamic wound closure device (Canica, Almonte, ON, Canada). Eleven consecutive patients treated at a combat support hospital in support of Operation Iraqi Freedom underwent four-compartment fasciotomies for penetrating injuries. There were five patients that underwent a vascular repair [three superficial femoral artery (SFA) injuries and two below knee popliteal artery injuries] and six patients that had orthopedic injuries (three comminuted tibial fractures, two fibula fractures, and one closed pilon fracture). Patients returned to the operating room within 24 hours for washout and wound inspection. Mean initial wound size was 8.1 cm; mean postplacement size was 2.7 cm; average time to closure was 2.6 days. All patients were able to undergo primary wound closure of the medial incision and placement of the Canica device over the lateral incision. Ten of the 11 patients (91%) could be closed in delayed primary fashion after application of the device. In our series of patients with penetrating wartime injuries and compartment syndrome of the leg we have found the use of this dynamic wound closure device to be extremely successful and expedient.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".