High rate of clinically relevant improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis
Bibliographic record
Abstract
BACKGROUND The minimal clinically important difference (MCID) is defined as the smallest meaningful change in a health domain that a patient would identify as important. Thus, an improvement that exceeds the MCID can be used to define a successful treatment for the individual patient. AIM To quantify the rate of clinical improvement following anatomical total shoulder arthroplasty for glenohumeral osteoarthritis. METHODS Patients were treated with the Global Unite total shoulder platform arthroplasty between March 2017 and February 2019 at Herlev and Gentofte Hospital, Denmark. The patients were evaluated preoperatively and 3 months, 6 months, 12 months, and 24 months postoperatively using the Western Ontario Osteoarthritis of the Shoulder index (WOOS), Oxford Shoulder Score (OSS) and Constant-Murley Score (CMS). The rate of clinically relevant improvement was defined as the proportion of patients who had an improvement 24 months postoperatively that exceeded the MCID. Based on previous literature, MCID for WOOS, OSS, and CMS were defined as 12.3, 4.3, and 12.8 respectively. RESULTS Forty-nine patients with a Global Unite total shoulder platform arthroplasty were included for the final analysis. Mean age at the time of surgery was 66 years (range 49.0-79.0, SD: 8.3) and 65% were women. One patient was revised within the two years follow-up. The mean improvement from the preoperative assessment to the two-year follow-up was 46.1 points [95% confidence interval (95%CI): 39.7-53.3, P < 0.005] for WOOS, 18.2 points (95%CI: 15.5-21.0, P < 0.005) for OSS and 37.8 points (95%CI: 31.5-44.0, P < 0.005) for CMS. Two years postoperatively, 41 patients (87%) had an improvement in WOOS that exceeded the MCID, 45 patients (94%) had an improvement in OSS that exceeded the MCID, and 42 patients (88%) had an improvement in CMS that exceeded the MCID. CONCLUSION Based on three shoulder-specific outcome measures we find that approximately 90% of patients has a clinically relevant improvement. This is a clear message when informing patients about their prognosis.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".