A Prospective Follow-up of Patients Treated Surgically or Non-Surgically for Full-thickness Rotator Cuff Tears
Bibliographic record
Abstract
Objectives: The objectives of this project are: (1) to compare the efficacy of surgical versus non-surgical management of full-thickness rotator cuff tears, and (2) to detect variables that predict success within each treatment group. Methods: Patients who presented to our care for management of symptomatic full-thickness rotator cuff tears were enrolled in our Shoulder Registry and clinical data were collected prospectively. In addition to baseline demographic information, the following outcome measures were collected at baseline, 6 months, 1 year and annually up to 3 years: Western Ontario Rotator Cuff (WORC) Index, American Shoulder and Elbow Surgeons (ASES) score, Modified Marx Shoulder Activity Level Scale, VR-12, 100-point Single Assessment Numeric Evaluation (SANE) rating, 100-point visual analog scale (VAS) for pain, and a patient satisfaction scale. All patients were allocated treatment as recommended by the attending surgeon. We described all patient demographic characteristics, and performed linear and logistic regression for variables associated with treatment allocation and with treatment effects. We also used Student’ t-tests and Wilcoxon rank-sum tests where appropriate, to explore differences in treatment effects between the groups for all outcome measures at all time points. Results: A total of 292 patients were included with 155 allocated to surgery and 137 to non-surgical treatment. Those allocated to surgery were younger (58.6 years vs 65.2 years; P<.0001), less likely to have diabetes (12% vs 21%; P=0.05), more likely to have a known traumatic injury (71% vs 55%; P=0.002), and tended to be worse off on all outcome measures at baseline then the non-surgical group. Both the surgical group and non-surgical group improved on all outcome measures across the follow up period with several variables predicting changes at each time point. Table 1 contains the list of specific variables that predicted improved outcomes separately for both treatment groups. Also, at one year the surgical group improvement was significantly greater than the non-surgical group on all outcome measures. At both two and three years the surgical group showed a significantly greater degree of improvement than the non-surgical group on both the WORC index and the ASES score. Conclusion: We found that patients with rotator cuff tears who undergo surgical or nonsurgical treatment tend to improve, with patients allocated to surgery improving to a greater degree across three years of follow-up. In addition, there appear to be important predictors of improved outcomes that may help us to tailor our treatments to individuals with specific characteristics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".