Volar-Dorsal Arthroscopic Repair for Scapholunate Ligament Injuries: A Case Series and Treatment Algorithm
Bibliographic record
Abstract
Objective: Scapholunate interosseus ligament (SLIL) disruption is a challenging injury that presents with varying degrees of severity. The gold standard diagnosis is arthroscopic evaluation of the SLIL, but treatments have traditionally been performed with open surgical technique. This offers powerful correction, but outcomes are inconsistent, and postoperative stiffness is common. There is a paucity of methods for the management of mild SLIL instability, and the morbidity of open techniques may be difficult to justify in these situations. The development of arthroscopic techniques has expanded options to include repair while minimizing soft tissue disruption. This study presents an arthroscopic algorithm for the treatment of predynamic SLIL instability without radiographic deformity, with a case series demonstration of a dorsal and combined volar-dorsal repair. Materials and Methods: Following institutional review board approval, eight patients with clinical symptoms of SLIL injury who underwent diagnostic arthroscopy between November 2021 and July 2023 were identified for inclusion in our retrospective review. Repair techniques, including dorsal capsuloligamentous, as well as combined volar-dorsal suture arthroscopic repair, were performed based on injury severity in accordance with the European Wrist Arthroscopy Society (EWAS) grading system, including patients with grade 3 injuries. Pre- and postoperative range of motion, patient-rated outcomes measures, and radiographic metrics were assessed for all patients. Patients with scapholunate diastasis were excluded from this study and treated with alternative interventions. Results: Median age of the population was 29.5 years, and included six right-sided and two left-sided injuries. Mean time to follow-up was 18.9 months. No patients presented with dorsal intercalated segment instability, and there was minimal change in alignment and scapholunate gapping postoperatively. Following the intervention, patients had excellent subjective function and range of motion. Conclusion: We describe a simple and effective suture-based arthroscopic capsuligamentous repair to treat SLIL injuries that are EWAS grade IIIA to C that resulting in excellent postoperative motion, function, and reduction of pain. Level of Evidence: Level IV/Therapeutic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".