Sex-related differences in stemless total shoulder arthroplasty
Bibliographic record
Abstract
BACKGROUND: The use of stemless humeral implants for shoulder arthroplasty is becoming increasingly widespread. However, little is known about the difference in clinical, functional, and radiographic outcomes of stemless shoulder arthroplasty between men and women. Men and women do have reported differences in size, strength, and bone quality. As such, the purpose of this study was to evaluate sex-related differences in outcomes when using stemless humeral implants. METHODS: A retrospective review of 227 patients (men = 143 and women = 84) undergoing stemless shoulder arthroplasty was compared for sex-related differences. Clinical, functional, and radiographic outcomes were compared, including American Shoulder and Elbow Surgeons (ASES) scores, visual analog scale pain scores, range of motion, radiolucencies, operative data, implant data, and complications. Statistical analysis included descriptive statistics, t-tests, chi-square tests, and logistic regression. RESULTS: < .01). There was no significant difference in surgical complications, including dislocation, fracture, infection, or loosening. The three-year revision-free survival was 98.8% for women and 97.9% for men. CONCLUSION: Patient sex is not predictive of postoperative functional outcomes after stemless shoulder arthroplasty. The operative time was significantly shorter in female patients, and there was no significant difference in surgical complications between men and women.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".