Good long-term patient-reported outcome after shoulder arthroplasty for cuff tear arthropathy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background The use of the reverse shoulder arthroplasty (RSA) for cuff tear arthropathy (CTA) has increased within the last decades, but there is still limited information about the long-term outcome and how it performs in comparison with hemiarthroplasty (HA). The aim of this study was to compare the long-term patient-reported outcomes of RSA and HA for CTA. Methods We included all patients with CTA, who according to the Danish Shoulder Arthroplasty Registry, underwent either HA or RSA between 2006 and 2010. Patients who were alive were sent the Western Ontario Osteoarthritis of the Shoulder (WOOS) questionnaire in 2020. One hundred twenty (65%) patients returned a complete questionnaire. The linear regression model was used to compare RSA and HA. Sex, age, and previous surgery were included in the multivariable model. Results Forty-two HAs and 78 RSAs were evaluated with a mean follow-up time of 11.5 and 10.6 years, respectively. The mean WOOS score was 66.7 for HA and 71.7 for RSA. The difference of 5.0 was neither statistically significant nor clinically important (95% confidence interval: -4.3 to 14.2, P = .17), nor were there any significant risk of a worse WOOS score for sex, age, or previous surgery. Conclusion To our knowledge, this is the first study to compare the long-term patient-reported outcomes of HA and RSA for CTA. Our results indicate that RSA is a reliable and durable treatment option for CTA with good long-term results. Based on this observational study, it is not possible to make safe estimates about the effect of RSA compared with HA, but similar to RSA, HA was associated with relatively good long-term results.
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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 | 0.000 | 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) | 0.003 | 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 it