A scoping review of biomechanical testing for proximal humerus fracture implants
Bibliographic record
Abstract
BACKGROUND: Fixation failure is a relatively common sequela of surgical management of proximal humerus fractures (PHF). The purpose of this study is to understand the current state of the literature with regard to the biomechanical testing of proximal humerus fracture implants. METHODS: A scoping review of the proximal humerus fracture literature was performed, and studies testing the mechanical properties of a PHF treatment were included in this review. Descriptive statistics were used to summarize the characteristics and methods of the included studies. RESULTS: 1,051 proximal humerus fracture studies were reviewed; 67 studies met our inclusion criteria. The most common specimen used was cadaver bone (87%), followed by sawbones (7%) and animal bones (4%). A two-part fracture pattern was tested most frequently (68%), followed by three-part (23%), and four-part (8%). Implants tested included locking plates (52%), intramedullary devices (25%), and non-locking plates (25%). Hemi-arthroplasty was tested in 5 studies (7%), with no studies using reverse total shoulder arthroplasty (RTSA) implants. Torque was the most common mode of force applied (51%), followed by axial loading (45%), and cantilever bending (34%). Substantial testing diversity was observed across all studies. CONCLUSIONS: The biomechanical literature was found to be both diverse and heterogeneous. More complex fracture patterns and RTSA implants have not been adequately tested. These gaps in the current literature will need to be addressed to ensure that future biomechanical research is clinically relevant and capable of improving the outcomes of challenging proximal humerus fracture patterns.
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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 | 0.018 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.037 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".