Mechanical Properties and Engineering Analysis of Intramedullary Bone Fixation Nails Made From Fiber-Reinforced Composites: A Review
Bibliographic record
Abstract
Abstract Intramedullary nails (i.e., cylindrical or noncylindrical rods) for bone fracture fixation are manufactured using titanium or steel, which are stiffer compared to bone. Yet, stiff metal nails can limit interfragmentary fracture motion, which potentially causes delayed callus formation and healing. Also, stiff metal nails may carry too much load relative to bone, which potentially causes bone “stress shielding” adjacent to the nail, bone density loss, bone resorption, and nail loosening. As such, there have been previous attempts to develop flexible nails using nonmetallic materials made from fibers (e.g., carbon, flax, glass) immersed in polymer resins (e.g., epoxy, polyether-ether-ketone, polylactic acid). The goal of prior research has been to produce composite nails with tailor-made mechanical properties and optimal engineering performance versus traditional metal nails. Therefore, this is the first review to survey 40 years of previous literature on composite nails that reported mechanical properties of fibers and resins at the material level (e.g., elastic modulus, ultimate strength), mechanical properties of isolated composite nails at the material level (e.g., fatigue strength, surface hardness), and bone-nail engineering performance (e.g., fracture motion, nail stress). Moreover, applying design principles, improving study protocols, performing future research, and clinical considerations are also discussed to help future researchers to develop intramedullary nails from novel materials.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".