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Bone & Joint Research
Vol. 11, Issue 4 | Pages 229 - 238
11 Apr 2022
Jaeger S Eissler M Schwarze M Schonhoff M Kretzer JP Bitsch RG

Aims. One of the main causes of tibial revision surgery for total knee arthroplasty is aseptic loosening. Therefore, stable fixation between the tibial component and the cement, and between the tibial component and the bone, is essential. A factor that could influence the implant stability is the implant design, with its different variations. In an existing implant system, the tibial component was modified by adding cement pockets. The aim of this experimental in vitro study was to investigate whether additional cement pockets on the underside of the tibial component could improve implant stability. The relative motion between implant and bone, the maximum pull-out force, the tibial cement mantle, and a possible path from the bone marrow to the metal-cement interface were determined. Methods. A tibial component with (group S: Attune S+) and without (group A: Attune) additional cement pockets was implanted in 15 fresh-frozen human leg pairs. The relative motion was determined under dynamic loading (extension-flexion 20° to 50°, load-level 1,200 to 2,100 N) with subsequent determination of the maximum pull-out force. In addition, the cement mantle was analyzed radiologically for possible defects, the tibia base cement adhesion, and preoperative bone mineral density (BMD). Results. The BMD showed no statistically significant difference between both groups. Group A showed for all load levels significantly higher maximum relative motion compared to group S for 20° and 50° flexion. Group S improved the maximum failure load significantly compared to group A without additional cement pockets. Group S showed a significantly increased cement adhesion compared to group A. The cement penetration and cement mantle defect analysis showed no significant differences between both groups. Conclusion. From a biomechanical point of view, the additional cement pockets of the component have improved the fixation performance of the implant. Cite this article: Bone Joint Res 2022;11(4):229–238


Bone & Joint Research
Vol. 7, Issue 7 | Pages 468 - 475
1 Jul 2018
He Q Sun H Shu L Zhu Y Xie X Zhan Y Luo C

Objectives. Researchers continue to seek easier ways to evaluate the quality of bone and screen for osteoporosis and osteopenia. Until recently, radiographic images of various parts of the body, except the distal femur, have been reappraised in the light of dual-energy X-ray absorptiometry (DXA) findings. The incidence of osteoporotic fractures around the knee joint in the elderly continues to increase. The aim of this study was to propose two new radiographic parameters of the distal femur for the assessment of bone quality. Methods. Anteroposterior radiographs of the knee and bone mineral density (BMD) and T-scores from DXA scans of 361 healthy patients were prospectively analyzed. The mean cortical bone thickness (CBTavg) and the distal femoral cortex index (DFCI) were the two parameters that were proposed and measured. Intra- and interobserver reliabilities were assessed. Correlations between the BMD and T-score and these parameters were investigated and their value in the diagnosis of osteoporosis and osteopenia was evaluated. Results. The DFCI, as a ratio, had higher reliability than the CBTavg. Both showed significant correlation with BMD and T-score. When compared with DFCI, CBTavg showed better correlation and was better for predicting osteoporosis and osteopenia. Conclusion. The CBTavg and DFCI are simple and reliable screening tools for the prediction of osteoporosis and osteopenia. The CBTavg is more accurate but the DFCI is easier to use in clinical practice. Cite this article: Q-F. He, H. Sun, L-Y. Shu, Y. Zhu, X-T. Xie, Y. Zhan, C-F. Luo. Radiographic predictors for bone mineral loss: Cortical thickness and index of the distal femur. Bone Joint Res 2018;7:468–475. DOI: 10.1302/2046-3758.77.BJR-2017-0332.R1


Bone & Joint Open
Vol. 4, Issue 12 | Pages 914 - 922
1 Dec 2023
Sang W Qiu H Xu Y Pan Y Ma J Zhu L

Aims

Unicompartmental knee arthroplasty (UKA) is the preferred treatment for anterior medial knee osteoarthritis (OA) owing to the rapid postoperative recovery. However, the risk factors for UKA failure remain controversial.

Methods

The clinical data of Oxford mobile-bearing UKAs performed between 2011 and 2017 with a minimum follow-up of five years were retrospectively analyzed. Demographic, surgical, and follow-up data were collected. The Cox proportional hazards model was used to identify the risk factors that contribute to UKA failure. Kaplan-Meier survival was used to compare the effect of the prosthesis position on UKA survival.


Bone & Joint Research
Vol. 13, Issue 5 | Pages 226 - 236
9 May 2024
Jürgens-Lahnstein JH Petersen ET Rytter S Madsen F Søballe K Stilling M

Aims

Micromotion of the polyethylene (PE) inlay may contribute to backside PE wear in addition to articulate wear of total knee arthroplasty (TKA). Using radiostereometric analysis (RSA) with tantalum beads in the PE inlay, we evaluated PE micromotion and its relationship to PE wear.

Methods

A total of 23 patients with a mean age of 83 years (77 to 91), were available from a RSA study on cemented TKA with Maxim tibial components (Zimmer Biomet). PE inlay migration, PE wear, tibial component migration, and the anatomical knee axis were evaluated on weightbearing stereoradiographs. PE inlay wear was measured as the deepest penetration of the femoral component into the PE inlay.


Bone & Joint Research
Vol. 13, Issue 2 | Pages 66 - 82
5 Feb 2024
Zhao D Zeng L Liang G Luo M Pan J Dou Y Lin F Huang H Yang W Liu J

Aims

This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA.

Methods

Six sets of gene expression profiles were obtained from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and multiple machine-learning algorithms were used to screen crucial genes in osteoarthritic cartilage, and genome enrichment and functional annotation analyses were used to decipher the related categories of gene function. Single-sample gene set enrichment analysis was performed to analyze immune cell infiltration. Correlation analysis was used to explore the relationship among the hub genes and immune cells, as well as markers related to articular cartilage degradation and bone mineralization.