Ultrasound Assessment of Syndesmotic Injuries in a Pediatric Population
Bibliographic record
Abstract
Background: Syndesmotic injuries have a higher prevalence in athletes and can present long-term complications particularly in pediatric population. Early diagnosis is necessary and can be done using various modalities, but, they either present poor sensitivity, poor clinical feasibility or are exclusively static. Ultrasound (US) could compensate for those drawbacks. Hypothesis/Purpose: The aim of this study was to determine (1) the benefit of direct visualization of the anterior-inferior tibiofibular ligament (AiTFL) and (2) tibiofibular clear space (TFCS) cut-off points regarding the integrity of the syndesmotic ligaments using US imaging. Methods: A prospective cohort study including all suspected syndesmotic injury in a pediatric population was done. Participants had both ankles assessed with US imaging for description of AiTFL integrity as our static assessment and for TFCS measures as our dynamic evaluation. For dynamic assessment, the distance between the distal tibia and fibula was first measure in neutral position then in external rotation for each ankle. This providing a total of five different TFCS combinations for receiver operating characteristics (ROC) curves analysis. Afterward, the syndesmotic ligament complex and deltoid ligament of the injured ankle were examined using MRI as the gold standard. Results: A total of 26 participants with suspected syndesmotic injuries were included. Mean age was 14.8 years (SD = 1.3 years). Mean time between trauma and US imaging was 56 days (SD = 43.9 days). Sensitivity and specificity of direct visualization of the AiTFL were respectively 0.79 and 1.00 with four false negative tests only found on partial tears. Only two TFCS combinations had an area under the curve (AUC) greater than 0.7 and were then considered for further analysis. The two combinations were the TFCS difference between the injured and uninjured ankle in neutral position (TFCS N I-U ) and external rotation (TFCS ER I-U ). Cut-off points were ranging from 0.23 mm to 0.37 mm for TFCS N I-U and from 0.11 mm to 0. 30 mm for TFCS ER I-U using ROC curve analysis. Conclusion: US imaging does bring an added value as a screening tool for direct visualization of the AiTFL in pediatric patients by having a good sensitivity, an excellent specificity, a low cost and being easily accessible. The complementary use of dynamic evaluation using TFCS measures could also identify dynamic instability. Cut-off points determined in this study had good sensitivity and specificity but, by being under one millimeter, further studies using dynamic US imaging are needed.
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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 | 0.003 |
| 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) | 0.002 | 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".