Postoperative Rehabilitation After Rotator Cuff Repair
Bibliographic record
Abstract
BACKGROUND: Postoperative rehabilitation after arthroscopic rotator cuff repair (ARCR) remains controversial and suffers from limited high-quality evidence. Therefore, appropriate use criteria must partially depend on expert opinion. HYPOTHESIS/PURPOSE: The purpose of the study was to determine and report on the standard and modified rehabilitation protocols after ARCR used by member orthopaedic surgeons of the American Orthopaedic Society for Sports Medicine (AOSSM) and the Arthroscopy Association of North America (AANA). We hypothesized that there will exist a high degree of variability among rehabilitation protocols. We also predict that surgeons will be prescribing accelerated rehabilitation. STUDY DESIGN: Cross-sectional study; Level of evidence, 4. METHODS: A 29-question survey in English language was sent to all 3106 associate and active members of the AOSSM and the AANA. The questionnaire consisted of 4 categories: standard postoperative protocol, modification to postoperative rehabilitation, operative technique, and surgeon demographic data. Via email, the survey was sent on September 4, 2013. RESULTS: The average response rate per question was 22.7%, representing an average of 704 total responses per question. The most common immobilization device was an abduction pillow sling with the arm in neutral or slight internal rotation (70%). Surgeons tended toward later unrestricted passive shoulder range of motion at 6 to 7 weeks (35%). Strengthening exercises were most commonly prescribed between 6 weeks and 3 months (56%). Unrestricted return to activities was most commonly allowed at 5 to 6 months. The majority of the respondents agreed that they would change their protocol based on differences expressed in this survey. CONCLUSION: There is tremendous variability in postoperative rehabilitation protocols after ARCR. Five of 10 questions regarding standard rehabilitation reached a consensus statement. Contrary to our hypothesis, there was a trend toward later mobilization.
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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) | 0.001 | 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) | 0.001 | 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".