Relationship between clinical and surgical findings and reparability of large and massive rotator cuff tears: a longitudinal study
Bibliographic record
Abstract
BACKGROUND: The literature has shown good results with partial repairs of large and massive tears of rotator cuff but the role of factors that affect reparability is less clear. The purpose of this study was twofold, 1) to examine clinical outcomes following complete or partial repair of large or massive full-thickness rotator cuff tear, and 2) to explore the value of clinical and surgical factors in predicting reparability. METHODS: This was a secondary data analysis of consecutive patients with large or massive rotator cuff tear who required surgical treatment (arthroscopic complete or partial repair) and were followed up for two years. Disability measures included the American Shoulder and Elbow Surgeons (ASES), the relative Constant-Murley score (CMS) and the shortened version of the Western Ontario Rotator Cuff Index (ShortWORC). The relationship between predictors and reparability was examined through logistic regressions and chi-square statistics as appropriate. Within group change over time and between group differences in disability outcomes, range of motion and strength were examined by student's T-tests and non-parametric statistics. RESULTS: One hundred and twenty two patients (41 women, 81 men, mean age 64, SD=9) were included in the analysis. There were 86 large (39 fully reparable, 47 partially reparable) and 36 (10 fully reparable, 26 partially reparable) massive tears. Reparability was not associated with age, sex, or pre-operative active flexion or abduction (p0>0.05) but the fully reparable tear group showed a better pre-operative ASES score (p=0.01) and better active external rotation in neutral (p=0.01). Reparability was associated with tear shape (p<0.0001), size (p=0.002), and tendon quality (p<0.0001). CONCLUSIONS: Reparability of large or massive tears is affected by a number of clinical and surgical factors. Patients whose tears could not be fully repaired showed a statistically significant improvement in range of motion, strength and disability at 2 years, although they had slightly inferior results compared to those with complete repairs.
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 | 0.001 | 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 | 0.000 |
| 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".