ArticleJournal of orthopaedic surgery and research2024
Stochastic lattice-based porous implant design for improving the stress transfer in unicompartmental knee arthroplasty.
Article in Journal of orthopaedic surgery and research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Patient-specific osteoarticular reconstruction of the proximal tibia for giant cell tumor using a 3D-printed trabecular implant and hinged knee arthroplasty: a case report.Frontiers in medicine · 2026Article
- Novel Clinical Applications of 3D-Printed Highly Porous Titanium for Off-the-Shelf Cementless Joint Replacement Prostheses.Biomimetics (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundUnicompartmental knee arthroplasty (UKA) has been proved to be a successful treatment for osteoarthritis patients. However, the stress shielding caused by mismatch in mechanical properties between human bones and artificial implants remains as a challenging issue. This study aimed to properly design a bionic porous tibial implant and evaluate its biomechanical effect in reconstructing stress transfer pathway after UKA surgery.
methodsVoronoi structures with different strut sizes and porosities were designed and manufactured with Ti6Al4V through additive manufacturing and subjected to quasi-static compression tests. The Gibson-Ashby model was used to relate mechanical properties with design parameters. Subsequently, finite element models were developed for porous UKA, conventional UKA, and native knee to evaluate the biomechanical effect of tibial implant with designed structures during the stance phase.
resultsThe internal stress distribution on the tibia plateau in the medial compartment of the porous UKA knee was found to closely resemble that of the native knee. Furthermore, the mean stress values in the medial regions of the tibial plateau of the porous UKA knee were at least 44.7% higher than that of the conventional UKA knee for all subjects during the most loading conditions. The strain shielding reduction effect of the porous UKA knee model was significant under the implant and near the load contact sites. For subject 1 to 3, the average percentages of nodes in bone preserving and building region (strain values range from 400 to 3000 μm/m) of the porous UKA knee model, ranging from 68.7 to 80.5%, were higher than that of the conventional UKA knee model, ranging from 61.6 to 68.6%.
conclusionsThe comparison results indicated that the tibial implant with designed Voronoi structure offered better biomechanical functionality on the tibial plateau after UKA. Additionally, the model and associated analysis provide a well-defined design process and dependable selection criteria for design parameters of UKA implants with Voronoi structures.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.