Clavicle Malunions: Surgical Treatment and Outcome—a Literature Review
Bibliographic record
Abstract
Background Successful treatment of clavicle malunion represents a major challenge for orthopedic surgeons. Questions/Purposes The aim of this study was to provide an overview of surgical options for the treatment of clavicle malunions regarding their technical details and clinical results. Methods A comprehensive search of the literature was performed to retrieve articles and conference abstracts regarding the surgical treatment of clavicle malunions. A total of 1873 records were identified and 29 studies were included in the present review, with a total of 103 patients. Results The majority of the patients (77/103) were treated with an osteotomy and subsequent open reduction internal fixation (ORIF). The next most frequent management choice was debridement, excision, or removal of excess callus or bone ( n = 19), but other techniques like resection of the clavicle ( n = 5) or nerve exploration and decompression ( n = 2) were also reported. The preferred method of fixation was plate fixation ( n = 53) followed by pin fixation ( n = 6). The complication rate was low, reported in less than 6% of patients. Conclusion All of the currently reported surgical techniques to manage symptomatic clavicle malunion have resulted in good clinical outcomes with a low complication rate. Considering biomechanical aspects, correction osteotomy followed by plate fixation seems to be the preferred method. Further studies are needed to compare the various surgical techniques and their specific outcomes in a prospective manner. Nevertheless, this review article can be used as an overview to help choose an optimal operative treatment for patients presenting with a clavicle malunion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".