Early repair of trauma-related full-thickness rotator cuff tears does not eliminate the problem of healing failure
Bibliographic record
Abstract
Aims Failure of healing is a well-known problem after repair of the rotator cuff. This study aimed to investigate if early repair of trauma-related full-thickness rotator cuff tears (FTRCTs) could prevent this failure. Patients and Methods In this prospective trial, 62 consecutive patients (14 women (23%), 48 men (77%); median age 61 years (interquartile range (IQR) 54 to 65)) with trauma-related FTRCT underwent arthroscopic single-row repair within six weeks of trauma. Tendon integrity was assessed one year after surgery using the Sugaya score on MR images. Patients were followed up with Western Ontario Rotator Cuff (WORC) index, EuroQol visual analogue scale (EQ VAS), and the Constant–Murley score (CS) two years after repair. Results A total of 57 patients (92%) had MR images available at one year; 59 patients (95%) had CS (one year), WORC (two years), and EQ VAS scores (two years). Intact repair was found on MRI in 36 patients (63%); 13 patients (23%) displayed healing failure of at least one repaired tendon and eight patients (14%) displayed total healing failure. Median WORC index and relative CS improved from 30.8 points (IQR 20.1 to 38.6) at baseline to 85.0 points (IQR 60.6 to 95.7) at two years and 26.5 points (IQR 21.2 to 37.4) to 83.2 points (IQR 71.9 to 97.5) at one year, respectively. The relative CS at one year was significantly better among those with intact repairs compared with those with healing failure (91.6 vs 78.1 points; p = 0.031). Conclusion Although early repair of trauma-related FTRCT improved patient relevant outcomes over two years for the entire cohort, only two out of three repaired rotator cuffs displayed intact structural integrity on MRI after one year. Consequently, early repair did not seem to prevent healing failure after trauma-related FTRCT. Cite this article: Bone Joint J 2019;101-B:603–609.
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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 | 0.002 | 0.000 |
| 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 | 0.001 |
| 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".