Comparison of surgical treatments of acromioclavicular dislocations
Bibliographic record
Abstract
Background. According to the literature, acromioclavicular dislocations rank third in frequency among all dislocations within the musculoskeletal system. The social significance of acromioclavicular (AC) joint injuries lies in that the majority of affected individuals are part of the working-age population, typically aged 25 to 45 years, frequently involved in physically demanding occupations and high-level sports.Aim. This article seeks to compare various surgical treatment methods for AC dislocations. Materials and methods. This study analyses current Russian and international literature sources regarding the surgical treatment of AC dislocations. The information sources were examined using the eLibrary and PubMed search engines.Results and discussion. In current clinical practice, surgical methods are typically preferred when considering treatment approaches for AC dislocations. This preference stems from the significant advantages associated with surgery, including a shorter rehabilitation period and high patient satisfaction with long-term treatment outcomes, despite the risks of postoperative complications.Conclusion. The most promising methods for stabilising the AC joint include the use of a hookshaped plate and the button suture. While a hook-shaped plate offers greater stability compared to the button suture, it necessitates informing the patient about the need for plate removal three months post-surgery to reduce the risk of osteoarthritis development. On the other hand, the button suture does not require additional surgical procedures for implant removal but may result in less rigid fixation, potentially leading to recurrence of dislocation.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".