Anatomical Evaluation of the Proximity of Neurovascular Structures During Arthroscopically Assisted Acromioclavicular Joint Reconstruction: A Cadaveric Pilot Study
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The purpose of this study was to examine the safety of an arthroscopic technique for acromioclavicular joint (ACJ) reconstruction by investigating its proximity to important neurovascular structures. METHODS: Six shoulders from 4 cadaveric specimens were used for ACJ reconstruction in this study. The procedure consists of performing an arthroscopic acromioclavicular (AC) reduction with a double button construct, followed by coracoclavicular ligament reconstruction without drilling clavicular tunnels. Shoulders were subsequently dissected in order to identify and measure distances to adjacent neurovascular structures. RESULTS: The suprascapular artery and nerve were the closest neurovascular structures to implanted materials. The mean distances were 8.2 (standard deviation [SD] = 3.6) mm to the suprascapular nerve and 5.6 (SD = 4.2) mm to the suprascapular artery. The mean distance of the suprascapular nerve from implants was found to be greater than 5 mm (P = .040), while the distance to the suprascapular artery was not (P > .5). Neither difference was statistically significant (P = .80 for artery; P = .08 for nerve). CONCLUSIONS: Mini-open, arthroscopically assisted ACJ reconstruction safely avoids the surrounding nerves, with no observed damage to any neurovascular structures including the suprascapular nerve and artery, and may be a viable alternative to open techniques. However, surgeons must remain cognizant of possible close proximity to the suprascapular artery. CLINICAL RELEVANCE: This study represents an evaluation of the safety and feasibility of a minimally invasive ACJ reconstruction as it relates to the proximity of neurovascular structures.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it