Are two plates better than one? A systematic review of dual plating for acute midshaft clavicle fractures
Bibliographic record
Abstract
Background The rate of operative fixation of acute midshaft clavicle fractures has exponentially increased in recent years; however, the rate of reoperation for symptomatic hardware removal remains high and the optimal fixation strategy unknown. This systematic review aimed to summarize available evidence for dual plating of acute displaced midshaft clavicle fractures. Methods EMBASE, MEDLINE, and PubMed searches identified clinical studies evaluating dual plate fixation of acute midshaft clavicle fractures. Pooled analysis was performed using a random-effects model in RevMan 5.3. Results Eleven studies including 672 patients were included. Hardware removal occurred in 4.4% and 12.3% of patients undergoing dual and single plate fixation, respectively. Compared to single plating, dual plating had significantly lower odds of hardware removal ( P = 0.001) with no difference in union rates. There were no significant differences in reoperation (excluding hardware removal), complications, and patient-reported outcomes between the two groups ( P > 0.05). Conclusions This study suggests that dual plating of acute displaced midshaft clavicle fractures may lead to lower rates of reoperation for symptomatic hardware removal without compromising fracture healing. Ultimately, well-designed randomized trials are needed to further investigate the findings from this systematic review.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".