Effect of a Controlled Ankle Motion Walking Boot on Syndesmotic Instability During Weightbearing: A Cadaveric Study
Bibliographic record
Abstract
BACKGROUND: Syndesmotic injuries can lead to long-term complications; hence, they require careful management. Conservative treatment is adequate when 1 syndesmotic ligament is injured, but surgery is often necessary to achieve articular congruity when 3 syndesmotic ligaments are ruptured. However, there is some controversy over the best treatment for 2-ligament injuries. PURPOSE: To evaluate the effect of a controlled ankle motion (CAM) walking boot on syndesmotic instability following iatrogenic isolated anterior inferior tibiofibular ligament (AiTFL) injury and combined AiTFL/interosseous ligament (IOL) injuries in a cadaveric simulated weightbearing model. STUDY DESIGN: Controlled laboratory study. METHODS: Ten cadaveric specimens were dissected to expose the tibial plateau and syndesmosis. The specimens were fitted to a custom-made device, and a reproducible axial load of 750 N was applied. Iatrogenic rupture of the syndesmotic ligaments (AiTFL + IOL) was done sequentially. Uninjured syndesmoses, isolated AiTFL rupture, and combined AiTFL/IOL rupture were compared with and without axial loading (AL) and CAM boot. The distal tibiofibular relationship was evaluated using a previously validated computed tomography scan measurement system. Wilcoxon tests for paired samples and nonparametric data were used. RESULTS: = .005). CONCLUSION: AL did not cause a significant displacement between the tibia and fibula, even when 2 ligaments were ruptured. However, the CAM boot produced a significant external rotation with 1 or 2 injured ligaments. CLINICAL RELEVANCE: Further studies are needed to assess the capacity of the CAM walking boot to prevent malreduction when external rotation forces are applied to the ankle. Moreover, special care should be taken during the fitting of the CAM boot to avoid overinflation of the cushions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".