Suspension Suture Augmentation for Repair of Coracoclavicular Ligament Disruptions
Bibliographic record
Abstract
UNLABELLED: Surgical reconstruction of the coracoclavicular ligament is a fundamental part of management of high-grade acromioclavicular dislocations and Type II lateral third clavicular fractures. However, no single surgical procedure is fully satisfactory because of failure or complications. We present an alternative coracoclavicular stabilization technique, which avoids the use of hardware or tendon graft, that was used in 10 consecutive patients with complete coracoclavicular ligament disruptions. These patients were followed for a minimum of 14 months (average, 34.8 months; range, 14-55 months). At the final followup, functional outcome measurement instruments (University of California-Los Angeles shoulder rating system and Western Ontario Shoulder Instability Index) and radiographic analysis were adopted as the main outcome measures of shoulder function. The mean University of California-Los Angeles shoulder rating score and the mean Western Ontario Shoulder Instability Index aggregation score at 12 months after surgery were 33.8 (95% confidence interval, 32.8-34.8) and 93.4 (95% confidence interval, 88.2-98.6), respectively. The radiographic analysis revealed all patients had maintained reduction on radiographs at the final followup. These preliminary results suggest that this simple technique can achieve stable coracoclavicular reconstruction and facilitate healing of the repaired ligaments or fractures. LEVEL OF EVIDENCE: Level IV, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".