A population-based comparison of joint survival of hemiarthroplasty <i>versus</i> total shoulder arthroplasty in osteoarthritis and rheumatoid arthritis
Bibliographic record
Abstract
AIMS: Few studies have compared survivorship of total shoulder arthroplasty (TSA) with hemiarthroplasty (HA). This observational study compared survivorship of TSA with HA while controlling for important covariables and accounting for death as a competing risk. PATIENTS AND METHODS: All patients who underwent shoulder arthroplasty in Ontario, Canada between April 2002 and March 2012 were identified using population-based health administrative data. We used the Fine-Gray sub-distribution hazard model to measure the association of arthroplasty type with time to revision surgery (accounting for death as a competing risk) controlling for age, gender, Charlson Comorbidity Index, income quintile, diagnosis, and surgeon factors. RESULTS: During the study period, 5777 patients underwent shoulder arthroplasty (4079 TSA, 70.6%; 1698 HA, 29.4%), 321 (5.6%) underwent revision, and 1090 (18.9%) died. TSA patients were older (TSA mean age 68.4 years (sd 10.2) vs HA mean age 66.5 years (sd 12.7); p = 0.001). The proportion of female patients was slightly lower in the TSA group (58.0% vs 58.4%). The adjusted association between surgery type and time to shoulder revision interacted significantly with patient age. Compared with TSA patients, revision was more common in the HA group (adjusted-health ratio (HR) 1.214, 95% confidence interval (CI) 0.96 to 1.53) but this did not reach statistical significance. CONCLUSION: Although there was a trend towards higher revision risk in patients undergoing HA, we found no statistically significant difference in survivorship between patients undergoing TSA or HA. Cite this article: Bone Joint J 2019;101-B:454-460.
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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 | 0.000 |
| 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".