Outcomes of Fixation of Lateral-End Clavicle Fractures Using Locking Clavicular Plate With Acromioclavicular TightRope Augmentation: A Meta-Analysis
Bibliographic record
Abstract
Lateral-end clavicle fractures, especially unstable Neer IIb patterns, are prone to nonunion due to disruption of the acromioclavicular (AC) ligaments. Conventional plate or hook plate fixation may provide inadequate stability. Locking plate fixation augmented with AC TightRope (Arthrex, Naples, FL, USA) or suture button construct aims to improve stability, accelerate healing, and enhance functional recovery. The objective of this study is to evaluate the efficacy of augmented fixation compared with conventional fixation in terms of union, functional outcomes, pain, and complications. A systematic review and meta-analysis of studies published up to October 2025 was conducted, including clinical and biomechanical studies comparing locking plate with or without AC augmentation. Outcomes included Constant-Murley Score (CMS), Visual Analog Scale (VAS), union rate, union time, and complications. Quality was assessed using the Newcastle-Ottawa Scale and a biomechanical checklist. Five studies met the inclusion criteria. Augmented fixation showed higher CMS (MD = 4.4; 95% CI [2.1, 6.7]), faster union (-2.2 weeks; 95% CI [-3.5, -0.9]), lower VAS (-1.54; 95% CI [-2.3, -0.8]), and fewer complications (OR = 0.38; 95% CI [0.15, 0.95]) compared with conventional fixation. Union rates were consistently high (97-100%) in clinical studies, and biomechanical data demonstrated superior construct stability. Locking plate fixation with AC TightRope or suture-button augmentation provides improved function, faster healing, reduced pain, and lower complication rates in unstable lateral-end clavicle fractures.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.042 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".