Surgical repair of the supraspinatus: pre- and postoperative architectural changes in the muscle
Bibliographic record
Abstract
INTRODUCTION: Shortening of the tendon and muscle is recognised as a strong predictor of surgical failure of supraspinatus tendon tears. Changes in muscle architecture following repair have not been thoroughly investigated. Hence, we aimed to compare the pre- and postoperative architecture of the supraspinatus. METHODS: We recruited eight participants with full-thickness supraspinatus tears. Images of the supraspinatus were captured preoperatively (pre-op) and postoperatively at one month (post-op1), three months (post-op2) and six months (post-op3) in relaxed and contracted states (0º and 60º glenohumeral abduction). Fibre bundle length (FBL), pennation angle (PA) and muscle thickness were quantified. Self-reported function, and maximal isometric abduction and external rotation strengths were assessed. RESULTS: The mean FBL increased from pre-op to post-op1 (p = 0.001) in the relaxed state and from pre-op to post-op2 (p = 0.002) in the contracted state. Decrease in FBL was observed from post-op2 to post-op3 in the relaxed state. The mean PA decreased from pre-op to post-op1 (p < 0.001) in the relaxed state, but increased from post-op2 to post-op3 in both relaxed (p = 0.006) and contracted (p = 0.004) states. At post-op3, external rotation (p = 0.009) and abduction (p = 0.005) strengths were greater than at post-op2. Overall function increased by 47.67% from pre-op to post-op3. CONCLUSION: Lengthening of the supraspinatus occurs with surgery, altering the length-tension relationship of the muscle, which can compromise muscle function and lead to inferior surgical outcomes. These findings may guide clinicians to optimise loads, velocities and shoulder ranges for effective postoperative rehabilitation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".