Comparison of the outcomes of syndesmotic ankle fractures treated with dynamic fixation versus static fixation versus fibular nail: a meta-analysis and systematic review
Bibliographic record
Abstract
Background: Syndesmotic ankle fractures occur when there is damage to the syndesmosis complex, resulting in severe pain and instability. Treatment methods include static fixation, dynamic fixation, and fibular nailing. This systematic review and meta-analysis aims to compare the outcomes of these surgical interventions for syndesmotic ankle fractures. Methods: PubMed and Embase were searched up until April 2024 for comparison studies that included at least two of the treatment methods and relevant functional outcomes and complication metrics. Review Manager 5.4 was used for statistical analyses, and a P value ≤0.05 was considered statistically significant. Risk of bias was assessed with Review Manager 5.4. and the Newcastle-Ottawa scale. Results: Nineteen studies with a total of 1,182 patients met the inclusion criteria. Compared to static fixation, dynamic fixation had a significantly higher Olerud-Molander Ankle Score (OMAS) at both 1-year [standardized mean difference (SMD) =0.43; 95% confidence interval (CI): 0.22 to 0.65; P<0.05] and 2-year post-operation (SMD =0.76; 95% CI: 0.33 to 1.20; P<0.05). Dynamic fixation had a significantly lower reoperation rate than static fixation [risk ratio (RR) =0.55; 95% CI: 0.36 to 0.83; P=0.004]. Compared to static fixation, fibular nail had a significantly higher OMAS at 1-year post-operation (SMD =0.28; 95% CI: 0.03 to 0.53; P=0.03). Fibular nails had significantly lower infection (RR =0.12; 95% CI: 0.04 to 0.37; P<0.05) and reoperation rates (RR =0.22; 95% CI: 0.06 to 0.86; P=0.03) than static fixation. Compared to fibular nail, dynamic fixation had a significantly higher OMAS at both 1-year (SMD =1.07; 95% CI: 0.83 to 1.31; P<0.05) and 2-year post-operation (SMD =1.03; 95% CI: 0.60 to 1.47; P<0.05). Dynamic fixation had a significantly higher reoperation rate compared to fibular nail (RR =20.41; 95% CI: 2.81 to 148.21; P=0.003). Conclusions: Dynamic fixation seems to be the superior treatment method, displaying better outcomes than static fixation and fibular nailing, with the fibular nail proving to be a viable alternative. Dynamic fixation should be the first choice of treatment for those with syndesmotic ankle fractures due to its clinical advantages compared to static fixation and fibular nailing. Level of Evidence: 3.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.039 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".