Management of Ankle Fractures With Syndesmotic Disruption: A Survey of Orthopaedic Surgeons
Bibliographic record
Abstract
INTRODUCTION: With no current "gold standard" fixation strategy for syndesmotic injuries and differences in preferred preoperative and intraoperative diagnostic techniques and criteria, methods of reduction, fixation constructs, and postoperative management, the goals of this study were to determine how orthopaedic surgeons currently manage ankle fractures with concomitant syndesmotic disruption, as well as to identify surgeon demographics predictive of syndesmotic management techniques. METHODS: This study was conducted as a web-based survey of foot and ankle fellowship-trained surgeons, Orthopaedic Trauma Association (OTA) members, and Canadian Orthopaedic Association (COA) members. The survey, sent and completed via the HIPAA-compliant Research Electronic Data Capture (REDCap) system, consisted of 18 questions: 6 surgeon demographic questions and 12 specific syndesmotic management questions regarding perioperative protocols and syndesmotic fixation construct techniques. RESULTS: One hundred and ten orthopaedic surgeons completed our survey. Years of practice and type of fellowship were found to be the variables that influenced perioperative syndesmotic management strategies the most, while a number of fractures operated on per year, country of practice, and practice setting also influenced management decisions. Additionally, 59% (65/110) surgeons indicated that the way they have managed syndesmotic injuries has changed at some point in their career, while 33% (36/110) specified that they could foresee themselves changing their management of these injuries in the future. CONCLUSIONS: There was significant variability among responders in preoperative and intraoperative assessment technique, fixation construct, screw removal protocol, and postoperative weightbearing protocol. This study raises awareness of differences in and factors predictive of management strategies and should be used for further discussion when determining a potential gold standard for the management of these complex injuries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 teacher head, 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".