The stabilizing potential of the supraspinatus is inhibited in tear-associated scapula shapes but can be modulated by kinematic adjustments
Bibliographic record
Abstract
Introduction: Specific scapula shapes are associated with full-thickness tears of the supraspinatus tendon. A primary role of the supraspinatus is to actively stabilize the glenohumeral joint against muscles that generate destabilizing shear forces. Mechanisms that increase the supraspinatus load required to perform this stabilizing function may increase an individual's susceptibility to tears. Previous work has shown that tear-associated scapula shapes increase the destabilizing action of the deltoid during arm-raising, but no work has investigated whether tear-associated shapes inhibit the stabilizing potential of the supraspinatus itself. Methods: We combined statistical shape modeling, kinematics-driven simulations of the glenohumeral joint, and a finite element model of the supraspinatus to investigate the interactions among shape, kinematics, and the stabilizing potential of the supraspinatus. First, we identified tear-associated 3D scapula shapes using partial least squares discriminant analysis. Second, we examined how tear-associated shapes alter the stabilizing potential of the supraspinatus given the same kinematic path. Finally, we examined the extent to which kinematic perturbations could modulate differences in stabilizing potential. Results: Relative to asymptomatic controls, individuals with full-thickness tears possessed a suite of 3D shape differences including narrower supraspinous fossae and anteverted glenoids. For the same abduction path, tear-associated scapula shapes caused supraspinatus fibres to act more anteriorly and less compressively compared to the control shapes, potentially inhibiting the supraspinatus' ability to stabilize the humeral head. When the abduction path of the tear-associated scapula was internally rotated and shifted anteriorly, the supraspinatus line-of-action closely resembled that of the control-associated scapula; however, the tear-associated shape still possessed a narrower breadth in its supraspinatus line-of-action. Discussion: Our findings indicate that tear-associated scapula geometry may inhibit the stabilizing potential of the supraspinatus, but this shape-driven change could be partially modulated when the abduction path of the tear-associated shape was perturbed. The magnitude of kinematic perturbations required to modulate function exceeded the magnitude of shape differences, indicating that the perturbations are not correcting for a simple offset, but rather complex changes in muscle geometry that occur due to 3D shape differences.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".