Predictors of Postoperative Wound Necrosis Following Primary Wound Closure of Open Ankle Fractures
Bibliographic record
Abstract
BACKGROUND: Most open malleolar ankle fracture wounds can be closed primarily after meticulous debridement. However, the development of wound necrosis following operative treatment of open malleolar ankle fractures can have catastrophic consequences. The aim of this study was to identify risk factors predisposing to postoperative wound necrosis following primary wound closure of open malleolar ankle fractures. METHODS: A total of 137 patients with open malleolar ankle fractures were identified. The open fracture wound was primarily closed in 110 of 137 (80%) patients, and postoperative wound necrosis occurred in 18 (16%) of these patients. These patients were compared to the open fracture patients without wound necrosis. Twenty possible risk factors for the development of wound necrosis were studied with logistic regression analysis. RESULTS: The variables that were independently associated with an increased risk for postoperative wound necrosis included ASA class ≥2, Gustilo grade III open injury, and the use of pulsatile lavage at index surgery. CONCLUSIONS: Our study showed that ASA class ≥2, Gustilo grade III open injury, and the use of pulsatile lavage at index surgery were the most important factors predisposing to postoperative wound necrosis following primary wound closure of open malleolar ankle fractures. The findings warrant a further study specifically comparing primary and delayed wound closure in patients with Gustilo grade III open malleolar ankle fractures and different ASA classes. Also, the role of pulsatile lavage should be re-evaluated. LEVEL OF EVIDENCE: Level III, retrospective comparative series.
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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 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".