Carpal Kinematics following Sequential Scapholunate Ligament Sectioning
Bibliographic record
Abstract
Background The scapholunate ligament (SLL) is the most commonly injured intercarpal ligament of the wrist. It is the primary stabilizer of the scapholunate (SL) joint, but the scaphotrapeziotrapezoid (STT) and radioscaphocapitate (RSC) ligaments may also contribute to SL stability. The contributions of SL joint stabilizers have been reported previously; however, this study aims to examine their contributions to SL stability using a different methodology than previous studies. Purpose The purpose of this in vitro biomechanical study was to quantify changes in SL kinematics during wrist flexion and extension following a previously untested sequential sectioning series of the SL ligament and secondary stabilizers. Methods Eight cadaveric upper extremities underwent active wrist flexion and extension in a custom motion wrist simulator. SL kinematics were captured with respect to the distal radius. A five-stage sequential sectioning protocol was performed, with data analyzed from 45-degree wrist flexion to 45-degree wrist extension. Results Wrist flexion and extension caused the lunate to adopt a more extended posture following sectioning of the SLL and secondary stabilizers compared with the intact state (p < 0.009). The isolated disruption to the dorsal portion of the SLL did not result in significant change in lunate kinematics compared with the intact state (p > 0.05). Scaphoid kinematics were altered in wrist flexion following sequential sectioning (p = 0.013). Additionally, disruption of the primary and secondary stabilizers caused significant change to SL motion in both wrist flexion and wrist extension (p < 0.03). Conclusions The SLL is the primary stabilizer of the SL articulation, with the STT and RSC ligaments playing secondary stabilization roles. Clinical Relevance Understanding the role primary and secondary SL joint stabilizers may assist in the development of more effective treatment strategies and patient outcomes following SLL injuries.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".