Biomechanical design of a new proximal humerus fracture plate using alternative materials
Bibliographic record
Abstract
Abstract Comminuted proximal humerus fractures are often repaired by metal plates, but potentially still experience bone refracture, bone “stress shielding,” screw perforation, delayed healing, and so forth. This “proof of principle” investigation is the initial step towards the design of a new plate using alternative materials to address some of these problems. Finite element modeling was used to create design graphs for bone stress, plate stress, screw stress, and interfragmentary motion via three different fixations (no, 1, or 2 “kickstand” [KS] screws across the fracture) using a wide range of plate elastic moduli (EP = 5–200 GPa). Well‐known design optimization criteria were used that could minimize bone, plate, and screw failure (i.e., peak stress < ultimate tensile strength), reduce bone “stress shielding” (i.e., bone stress under the new plate ≥ bone stress for an intact humerus, titanium plate, and/or steel plate “control”), and encourage callus growth leading to early healing (i.e., 0.2 mm ≤ axial interfragmentary motion ≤ 1 mm; shear/axial interfragmentary motion ratio <1.6). The findings suggest that a potentially optimal configuration involves the new plate being manufactured from a material with an EP of 5–41.5 GPa with 1 KS screw; but, using no KS screws would cause immediate bone fracture and 2 KS screws would almost certainly lead to delayed healing. A prototype plate might be fabricated using alternative materials suggested for orthopedics and other industries, like fiber‐metal laminates, fiber‐reinforced polymers, metal foams, pure polymers, shape memory alloys, or 3D‐printed porous metals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".