The use of pyrocarbon as a bearing surface in shoulder arthroplasty: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Pyrocarbon has been trialed as an alternative bearing surface to metal for young active patients with glenohumeral joint arthritis. The aim of this study was to systematically review and summarize the available evidence on reported outcomes of pyrocarbon implants in shoulder arthroplasty. Methods: A systematic review was conducted according and reported according to standardized guidelines. Patient demographics, complications, implant survivorship and patient-reported outcome measures were extracted and included in the quantitative analysis. Outcome data was summarized with weighted mean differences and proportions. Results: Fifteen studies were included with 904 patients and a median follow-up of 38 months. The pooled mean range of motion improvement was 43.9 degrees (95% confidence interval [95% CI] 36.7-51.2) in forward elevation and 24.1 degrees (95% CI 18.4-29.9) in external rotation. Pooled mean Constant Score improvement was 34.7 (95% CI 29.4-40.1) and Subjective Shoulder Value improvement was 40.6 (95% CI 33.4-47.8). The overall pooled re-operation rate was 8.03% (95% CI 5%-12.7%). Discussion: Pyrocarbon shoulder implants demonstrated improvements in functional outcomes with low revision rates at early- to mid-term follow-up. Further well-designed prospective studies with long-term follow-up are required to verify the safety and efficacy of pyrocarbon implants in shoulder arthroplasty.
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 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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".