Implications of humeral short-stem diametral sizing on implant stability
Bibliographic record
Abstract
Background Shoulder arthroplasty humeral stem design has evolved to include various shapes, coatings, lengths, sizes, and fixation methods. While necessary to accommodate patient anatomy characteristics, this creates a surgical paradox of choice. The relationship between the surgeon's selection of short-stem implant size and construct stiffness, resistance to subsidence and micromotion has not been assessed. Methods Eight paired cadaveric humeri were reconstructed with surgeon-selected (SS) and 2-mm diametrically larger (SS+2) short-stemmed press-fit implants. Each reconstruction was subjected to 2000 cycles of 90° forward flexion loading, and stem subsidence and micromotion were measured using optical tracking. Compressive stiffness of the stem-bone reconstruction was then assessed by applying a load in-line with the stem axis that resulted in 5 mm of stem subsidence. Results Increasing stem size by 2 mm resulted in the construct stiffness more than doubling compared to SS stems (−741 ± 243 N/mm vs. −334 ± 120 N/mm; P = .003; power = 0.971). These larger stems also subsided significantly less than their SS counterparts (SS: 1.2 ± 0.6 mm; SS+2: 0.5 ± 0.5 mm; P = .029; power = 0.66), though there were no significant changes in micromotion (SS: 169 ± 59 μm; SS+2: 187 ± 52 μm; P = .506; power = 0.094). Conclusions The results of this study highlight the importance of proper short-stem sizing, as a relatively small 2 mm increase in diametral size was observed to significantly impact construct stiffness, which could increase the risk of stress shielding and implant loosening. Future work should focus on developing tools that objectively quantify bone quality and aid surgeons in selecting the appropriate size short-stem humeral implants for a particular patient.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".