THE IMPACT OF DESIGN PARAMETERS ON IMPLANT WEAR IN REVERSE TOTAL SHOULDER ARTHROPLASTY
Bibliographic record
Abstract
Reducing articular wear in reverse total shoulder arthroplasty (RTSA) implants is beneficial in extending device lifespan and avoiding biological complications resulting from wear debris (1). A better understanding of the relationship between implant design parameters and wear rate can help inform the design process, but performing extensive wear testing in an in-vitro setting is both time- and cost-prohibitive. This study aims to investigate the relationships between implant diameter, neck-shaft angle, and presence of scapular notching on articular wear rates in RTSA in silico. Three implant diameters (38mm, 40mm, 42mm), three neck-shaft angles (135°, 145°, 155°), and two scapular notching conditions (unnotched and with a simulated 3mm X 10mm notch in the inferior edge) were tested. Articular contact pressures were determined using finite element analysis during a discretized circumduction motion (representing 30°-97.5° add-abd and ±22.5° flex-ext) for all design configurations, and then used in a computational wear model which applied cross-shear-based empirical pressure-dependent (Archard) and pressure-independent (polyethylene) wear equations to calculate the wear morphology and volumetric material loss after one million cycles of motion. Several trends emerge from the simulated volumetric wear rates (Table 1). First, wear rates increase with increasing implant diameter. This has previously been observed in vitro (2) and reinforces the idea that the decrease in contact pressure associated with a larger diameter cannot make up for the increase in both contacting surface area and relative sliding distance of the articulating surfaces. Next, the decreased neck-shaft angle which is beneficial in avoiding scapular impingement (3) also results in lower articular wear rates. This is likely due to the decrease in contact area between the humeral cup and the glenosphere which results from the centre of the contact area shifting towards the inferior edge of the cup (Figure 1). Finally, the presence of a simulated scapular notch results in decreased articular wear for most of the implant design combinations, which is consistent with the results of in-vitro testing on wear and scapular notching (4, 5). This effect is more pronounced in smaller diameter implants and in implants with a greater neck-shaft angle. This is likely because the same notch size represents a greater proportion of the total surface area of smaller diameter implants, and because the notch removes a lower-wear region of material in the low neck-shaft angle implants. The in-silico model confirms the trend of increasing volumetric wear rate with increasing implant diameter and exhibits a trend of increasing articular wear rate with increasing neck-shaft angle. These trends can facilitate the design of implants with favourable wear behaviour. For any figures or tables, please contact the authors directly.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".