Exploring age-related differences in asymptomatic male shoulder kinematics using four-dimensional computed tomography
Bibliographic record
Abstract
Background: Understanding age-related differences in shoulder glenohumeral and scapulothoracic motion has implications for the understanding, treatment, and management of shoulder injuries and diseases.Previous studies have investigated age-related differences, although statically and in single plane motion.The shoulder, however, is a complex joint capable of a wide range of motion and involves coordinated and synchronous movements from both the glenohumeral and scapulothoracic joints.Therefore, the objectives of this study were to measure age-related differences in kinematics of the glenohumeral and scapulothoracic joints during motion, as well as differences in the neutral positioning of the scapula and humerus.Methods: Thirty-one male participants comprised two cohorts based on age (<45 and 45 years).Participants performed two motions, forward elevation (FE) and internal rotation to the back (IR), with four-dimensional CT scanning to dynamically track the bones.The kinematics of the humerus and scapula were calculated with six degrees-of-freedom.The neutral position of the scapula and humerus was also calculated based on a static CT scan.Results: During the FE motion, internal rotation of the humerus was significantly greater (13, p=0.033) in the older cohort while the scapula had significantly more anterior translation (9mm, p=0.022) and medial rotation (9, p=0.021) in the younger cohort.Anterior translation of the humeral head during IR was significantly greater (1mm, p=0.05) in the younger cohort, while scapular superior translation was significantly greater (8mm, p=0.006) in the older cohort.When measuring humeral translation as a percentage of glenoid width rather than absolute translation, the older cohort exhibited significantly less translational ROM during FE (6%, p<0.001), (5%, p=0.036), (5%, p=0.009) and IR (6%, p<0.001), (6%, p<0.001), (4%, p<0.001) in the respective anterior, superior, and lateral directions.Furthermore, compared to the younger cohort, the older J o u r n a l P r e -p r o o f Age-Related Differences in Shoulder Kinematics cohort had a neutral pose with significantly more superior translation (17mm, p=0.05), lateral rotation (8, p=0.009) and posterior tilting (10, p<0.001) of the scapula, and a more anteriorly positioned humerus (2mm, p=0.007). Conclusions:Overall, this study found age-related differences in kinematics and neutral positioning of the scapula and humerus, which may help improve understanding of age-related differences in subluxation, diseases, injuries, and range of motion.
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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 | 0.001 | 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".