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Record W4414561653 · doi:10.1115/1.4069949

Mechanical Properties and Engineering Analysis of Intramedullary Bone Fixation Nails Made From Fiber-Reinforced Composites: A Review

2025· article· en· W4414561653 on OpenAlexaff
Radovan Zdero, Emil H. Schemitsch, Pawel Brzozowski

Bibliographic record

VenueJournal of Medical Devices · 2025
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsIntramedullary rodFixation (population genetics)Ultimate tensile strengthNail (fastener)Composite numberBone healingFracture (geology)Biomechanics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.014
GPT teacher head0.276
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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Same venueJournal of Medical DevicesSame topicBone fractures and treatmentsFrench-language works237,207