Biomechanical performance of proximal tibia fracture plates: A review
Bibliographic record
Abstract
PURPOSE: Proximal fractures of the tibia (i.e., shin bone) are often treated using proximal tibia fracture plates (PTFPs) that are not always biomechanically optimal. This is a review of biomechanical papers that studied the effect of modifying PTFP plate and screw variables. METHODS: PubMed, Scopus, and Web of Science databases were searched for English-language papers published before February 2024 using the terms "biomechanics" plus "proximal or plateau" plus "tibia" plus "fracture or "plate." Eligibility criteria were applied: (1) biomechanical studies only; (2) optimization studies that systematically permutated plate or screw variables; (3) plate-and-screw fixation only; (4) intra-articular or extra-articular fractures. The papers were examined for implant variables such as plate geometry, plate material, screw number, etc., while papers were also examined for outcome metrics like interfragmentary motion, plate stress, overall stiffness, etc. RESULTS: The 52 eligible PTFP papers considered the biomechanical effect of plate geometry, material, hole type, number, and position, while screw variables included geometry, number, and angle. Outcome metrics were interfragmentary motion (0-22.53 mm or 0°-60.1°), bone stress (1-1170 MPa), plate stress (3-586 MPa), and screw stress (3-1613 MPa), bone stress under the plate (2-11 MPa), number of loading cycles to failure (11,500-1,000,000), overall stiffness (22-24,869 N/mm or 0.4-63.8 Nm/degree), and failure strength (259-14,387 N). Reviewed papers showed that a PTFP's biomechanical stability could be maximized by using 1 or 2 plates that were contoured, larger, locking, metal, and/or placed on the largest surface of the bone fragment(s), while head, kickstand, and/or shaft screws should be longer, thicker, solid, metal, and/or angled. But more future work could be done on the biomechanical effect of plate design (e.g., alternative materials), bone quality (e.g., normal vs. osteoporotic), loading mode (i.e., axial, bending, torsion), etc. CONCLUSIONS: PTFPs should have their plate and screw variables optimized to provide the best biomechanical performance and clinical outcomes, but more work is required to determine the optimal conditions. Engineers and surgeons may find this review beneficial for designing, analyzing, or utilizing PTFPs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".