Inter and intra-system size variability of reverse shoulder arthroplasty polyethylene inserts
Bibliographic record
Abstract
BACKGROUND: As the incidence of reverse shoulder arthroplasty (RSA) increases, so will the revision burden. At times, the revision surgeon may be faced with a well-fixed component on one side of the joint and revision implants from a different manufacturer. The ability to use glenoid and humeral implants from different manufacturers could simplify the revision procedure. This study hypothesized that across a range of RSA systems, some implants would demonstrate high size compatibility and others would demonstrate low compatibility. MATERIALS AND METHODS: Six polyethylene inserts each from eight reverse total shoulder arthroplasty systems were examined (48 total inserts). All inserts were scanned using a laboratory micro-computed tomography scanner at 50 μm isotropic voxel spacing, and their surface geometries were reconstructed. The different implant geometries were co-registered, and the three-dimensional (3D) variability between the articular surfaces of the different implant systems was measured. Intrasystem manufacturing variability was also determined by measuring the 3D variability of inserts from the same system. RESULTS: The intersystem polyethylene articular surface deviations between same-size systems were not significantly different (P = 0.61) and were a mean maximum of 60 ± 16 μm (range: 30-80 μm). Intrasystem manufacturing variability was equivalent between all but two models, averaging 49 ± 17 μm (range: 23-99 μm). DISCUSSION: Differences in articular geometry between same-size inserts from different systems were on the same scale as intrasystem manufacturing variability, suggesting that different implant systems of the same nominal diameter could potentially be used interchangeably in revision or extenuating circumstances. CONCLUSION: The results of this study suggest that surgeons can theoretically interchange same-sized implant components from the different RSA systems tested when conducting revisions.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".