Efficacy and safety of different fixation methods for acute syndesmosis injuries: protocol for a network meta-analysis of randomised and observational studies
Bibliographic record
Abstract
INTRODUCTION: Acute unstable syndesmosis injuries require accurate reduction and stable fixation to improve short-term and long-term outcomes. Several different fixation methods have been established for acute syndesmosis injuries, each with pros and cons. Although some meta-analyses have reported better outcomes with suture-buttons than screws, the optimal fixation method remains uncertain because of heterogeneous study results and limited comparisons of emerging techniques. This network meta-analysis combining randomised and observational studies aims to determine the optimal fixation method for acute syndesmosis injuries. METHODS AND ANALYSIS: Five electronic databases (PubMed, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data and Embase) will be comprehensively searched from their inception through 1 June 2025 for randomised and observational studies, published in English or Chinese, that compared two or more fixation methods for acute syndesmosis injuries. Inclusion and exclusion criteria will be used for selection based on patient, intervention, comparison, outcome and study standards. Risk of bias will be evaluated by the Cochrane risk-of-bias tool 2 and the Newcastle-Ottawa scale, respectively. Conventional pairwise meta-analyses with the DerSimonian-Laird random effects model will be conducted first, followed by network meta-analyses with a three-level Bayesian hierarchical model. The outcome measures include functional outcomes, radiological indicators and postoperative complications. Data analysis will be conducted using Review Manager 5.3 and R 4.1.2. Heterogeneity, transitivity and inconsistency tests, subgroup and sensitivity analyses and publication bias will also be assessed. ETHICS AND DISSEMINATION: No ethical approval is required because all the data will be collected from published research. The results of this study will be published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: INPLASY202480027.
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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 | 0.065 | 0.096 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.045 | 0.004 |
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".