105. ORIF OF HIGH-ENERGY PILON FRACTURES: VIOLATING THE 7-CM SKIN BRIDGE RULE
Bibliographic record
Abstract
Purpose: The purpose of this study was to review our results in patients with pilon fractures treated with ORIF in which surgical planning involved multiple skin incisions, ensuring that the distance incisions overlapped was less than the distance between them. We hypothesized that soft-tissue complications would be minimal despite incisions placed Method: A retrospective chart review identified 37 pilon fractures in 32 patients treated by three orthopedic traumatologists at The Ottawa Hospital between August 2000 and February 2007. Follow-up included measurements of incision placement and functional outcome measures. Results: There were nine OTA type B and 28 OTA type C fractures; 28 were closed and nine were open. The mean age was 46.5 ±14.5 years, and average follow-up was 3.2 ±1.7 years. Of the patients reviewed, the average number of incisions was 3.7 ±1.1. The average overlap between incisions was 4.6-cm ±1.9 and the average skin bridge between incisions was 5.9-cm ±1.9, with 80% of the skin bridges Conclusion: With careful planning and good soft-tissue management, incisions can be placed to maximize articular exposure based on fracture lines. It does not appear that the dogma of keeping incisions >7-cm apart must be followed in most cases. Prudent surgical timing and meticulous soft-tissue handling can allow for multiple incisions to be placed as necessary for fracture reduction and optimal fixation while maintaining a low rate of complications.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".