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The Bone & Joint Journal
Vol. 107-B, Issue 1 | Pages 124 - 132
1 Jan 2025
Thompson P Khattak M Joseph PJ Perry DC Cootes TF Lindner C

Aims

The aims of this study were to develop an automatic system capable of calculating four radiological measurements used in the diagnosis and monitoring of cerebral palsy (CP)-related hip disease, and to demonstrate that these measurements are sufficiently accurate to be used in clinical practice.

Methods

We developed a machine-learning system to automatically measure Reimer’s migration percentage (RMP), acetabular index (ACI), head shaft angle (HSA), and neck shaft angle (NSA). The system automatically locates points around the femoral head and acetabulum on pelvic radiographs, and uses these to calculate measurements. The system was evaluated on 1,650 pelvic radiographs of children with CP (682 females and 968 males, mean age 8.3 years (SD 4.5)). Each radiograph was manually measured by five clinical experts. Agreement between the manual clinical measurements and the automatic system was assessed by mean absolute deviation (MAD) from the mean manual measurement, type 1 and type 2 intraclass correlation coefficients (ICCs), and a linear mixed-effects model (LMM) for assessing bias.


Bone & Joint Research
Vol. 13, Issue 12 | Pages 790 - 792
17 Dec 2024
Mangwani J Brockett C Pegg E

Cite this article: Bone Joint Res 2024;13(12):790–792.


The Bone & Joint Journal
Vol. 106-B, Issue 12 | Pages 1377 - 1384
1 Dec 2024
Fontalis A Yasen AT Giebaly DE Luo TD Magan A Haddad FS

Periprosthetic joint infection (PJI) represents a complex challenge in orthopaedic surgery associated with substantial morbidity and healthcare expenditures. The debridement, antibiotics, and implant retention (DAIR) protocol is a viable treatment, offering several advantages over exchange arthroplasty. With the evolution of treatment strategies, considerable efforts have been directed towards enhancing the efficacy of DAIR, including the development of a phased debridement protocol for acute PJI management. This article provides an in-depth analysis of DAIR, presenting the outcomes of single-stage, two-stage, and repeated DAIR procedures. It delves into the challenges faced, including patient heterogeneity, pathogen identification, variability in surgical techniques, and antibiotics selection. Moreover, critical factors that influence the decision-making process between single- and two-stage DAIR protocols are addressed, including team composition, timing of the intervention, antibiotic regimens, and both anatomical and implant-related considerations. By providing a comprehensive overview of DAIR protocols and their clinical implications, this annotation aims to elucidate the advancements, challenges, and potential future directions in the application of DAIR for PJI management. It is intended to equip clinicians with the insights required to effectively navigate the complexities of implementing DAIR strategies, thereby facilitating informed decision-making for optimizing patient outcomes. Cite this article: Bone Joint J 2024;106-B(12):1377–1384


The Bone & Joint Journal
Vol. 106-B, Issue 12 | Pages 1363 - 1368
1 Dec 2024
Chen DB Wood JA Griffiths-Jones W Bellemans J Haddad FS MacDessi SJ

As advancements in total knee arthroplasty progress at an exciting pace, two areas are of special interest, as they directly impact implant design and surgical decision making. Knee morphometry considers the three-dimensional shape of the articulating surfaces within the knee joint, and knee phenotyping provides the ability to categorize alignment into practical groupings that can be used in both clinical and research settings. This annotation discusses the details of these concepts, and the ways in which they are helping us better understand the individual subtleties of each patient’s knee. Cite this article: Bone Joint J 2024;106-B(12):1363–1368


The Bone & Joint Journal
Vol. 106-B, Issue 11 | Pages 1199 - 1202
1 Nov 2024
Watts AC Tennent TD Haddad FS


The Bone & Joint Journal
Vol. 106-B, Issue 11 | Pages 1348 - 1360
1 Nov 2024
Spek RWA Smith WJ Sverdlov M Broos S Zhao Y Liao Z Verjans JW Prijs J To M Åberg H Chiri W IJpma FFA Jadav B White J Bain GI Jutte PC van den Bekerom MPJ Jaarsma RL Doornberg JN

Aims

The purpose of this study was to develop a convolutional neural network (CNN) for fracture detection, classification, and identification of greater tuberosity displacement ≥ 1 cm, neck-shaft angle (NSA) ≤ 100°, shaft translation, and articular fracture involvement, on plain radiographs.

Methods

The CNN was trained and tested on radiographs sourced from 11 hospitals in Australia and externally validated on radiographs from the Netherlands. Each radiograph was paired with corresponding CT scans to serve as the reference standard based on dual independent evaluation by trained researchers and attending orthopaedic surgeons. Presence of a fracture, classification (non- to minimally displaced; two-part, multipart, and glenohumeral dislocation), and four characteristics were determined on 2D and 3D CT scans and subsequently allocated to each series of radiographs. Fracture characteristics included greater tuberosity displacement ≥ 1 cm, NSA ≤ 100°, shaft translation (0% to < 75%, 75% to 95%, > 95%), and the extent of articular involvement (0% to < 15%, 15% to 35%, or > 35%).


Aims

This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously.

Methods

Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.


The Bone & Joint Journal
Vol. 106-B, Issue 10 | Pages 1039 - 1043
1 Oct 2024
Luo TD Kayani B Magan A Haddad FS

The subject of noise in the operating theatre was recognized as early as 1972 and has been compared to noise levels on a busy highway. While noise-induced hearing loss in orthopaedic surgery specifically has been recognized as early as the 1990s, it remains poorly studied. As a result, there has been renewed focus in this occupational hazard. Noise level is typically measured in decibels (dB), whereas noise adjusted for human perception uses A-weighted sound levels and is expressed in dBA. Mean operating theatre noise levels range between 51 and 75 dBA, with peak levels between 80 and 119 dBA. The greatest sources of noise emanate from powered surgical instruments, which can exceed levels as high as 140 dBA. Newer technology, such as robotic-assisted systems, contribute a potential new source of noise. This article is a narrative review of the deleterious effects of prolonged noise exposure, including noise-induced hearing loss in the operating theatre team and the patient, intraoperative miscommunication, and increased cognitive load and stress, all of which impact the surgical team’s overall performance. Interventions to mitigate the effects of noise exposure include the use of quieter surgical equipment, the implementation of sound-absorbing personal protective equipment, or changes in communication protocols. Future research endeavours should use advanced research methods and embrace technological innovations to proactively mitigate the effects of operating theatre noise.

Cite this article: Bone Joint J 2024;106-B(10):1039–1043.


The Bone & Joint Journal
Vol. 106-B, Issue 10 | Pages 1050 - 1058
1 Oct 2024
Holleyman RJ Jameson SS Meek RMD Khanduja V Reed MR Judge A Board TN

Aims

This study evaluates the association between consultant and hospital volume and the risk of re-revision and 90-day mortality following first-time revision of primary hip arthroplasty for aseptic loosening.

Methods

We conducted a cohort study of first-time, single-stage revision hip arthroplasties (RHAs) performed for aseptic loosening and recorded in the National Joint Registry (NJR) data for England, Wales, Northern Ireland, and the Isle of Man between 2003 and 2019. Patient identifiers were used to link records to national mortality data, and to NJR data to identify subsequent re-revision procedures. Multivariable Cox proportional hazard models with restricted cubic splines were used to define associations between volume and outcome.


The Bone & Joint Journal
Vol. 106-B, Issue 9 | Pages 887 - 891
1 Sep 2024
Whyte W Thomas AM

The critical relationship between airborne microbiological contamination in an operating theatre and surgical site infection (SSI) is well known. The aim of this annotation is to explain the scientific basis of using settle plates to audit the quality of air, and to provide information about the practicalities of using them for the purposes of clinical audit. The microbiological quality of the air in most guidance is defined by volumetric sampling, but this method is difficult for surgical departments to use on a routine basis. Settle plate sampling, which mimics the mechanism of deposition of airborne microbes onto open wounds and sterile instruments, is a good alternative method of assessing the quality of the air. Current practice is not to sample the air in an operating theatre during surgery, but to rely on testing the engineering systems which deliver the clean air. This is, however, not good practice and microbiological testing should be carried out routinely during operations as part of clinical audit. Cite this article: Bone Joint J 2024;106-B(9):887–891


The Bone & Joint Journal
Vol. 106-B, Issue 9 | Pages 884 - 886
1 Sep 2024
Brown R Bendall S Aronow M Ramasamy A


Bone & Joint Research
Vol. 13, Issue 8 | Pages 411 - 426
28 Aug 2024
Liu D Wang K Wang J Cao F Tao L

Aims

This study explored the shared genetic traits and molecular interactions between postmenopausal osteoporosis (POMP) and sarcopenia, both of which substantially degrade elderly health and quality of life. We hypothesized that these motor system diseases overlap in pathophysiology and regulatory mechanisms.

Methods

We analyzed microarray data from the Gene Expression Omnibus (GEO) database using weighted gene co-expression network analysis (WGCNA), machine learning, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify common genetic factors between POMP and sarcopenia. Further validation was done via differential gene expression in a new cohort. Single-cell analysis identified high expression cell subsets, with mononuclear macrophages in osteoporosis and muscle stem cells in sarcopenia, among others. A competitive endogenous RNA network suggested regulatory elements for these genes.


Bone & Joint Open
Vol. 5, Issue 8 | Pages 671 - 680
14 Aug 2024
Fontalis A Zhao B Putzeys P Mancino F Zhang S Vanspauwen T Glod F Plastow R Mazomenos E Haddad FS

Aims. Precise implant positioning, tailored to individual spinopelvic biomechanics and phenotype, is paramount for stability in total hip arthroplasty (THA). Despite a few studies on instability prediction, there is a notable gap in research utilizing artificial intelligence (AI). The objective of our pilot study was to evaluate the feasibility of developing an AI algorithm tailored to individual spinopelvic mechanics and patient phenotype for predicting impingement. Methods. This international, multicentre prospective cohort study across two centres encompassed 157 adults undergoing primary robotic arm-assisted THA. Impingement during specific flexion and extension stances was identified using the virtual range of motion (ROM) tool of the robotic software. The primary AI model, the Light Gradient-Boosting Machine (LGBM), used tabular data to predict impingement presence, direction (flexion or extension), and type. A secondary model integrating tabular data with plain anteroposterior pelvis radiographs was evaluated to assess for any potential enhancement in prediction accuracy. Results. We identified nine predictors from an analysis of baseline spinopelvic characteristics and surgical planning parameters. Using fivefold cross-validation, the LGBM achieved 70.2% impingement prediction accuracy. With impingement data, the LGBM estimated direction with 85% accuracy, while the support vector machine (SVM) determined impingement type with 72.9% accuracy. After integrating imaging data with a multilayer perceptron (tabular) and a convolutional neural network (radiograph), the LGBM’s prediction was 68.1%. Both combined and LGBM-only had similar impingement direction prediction rates (around 84.5%). Conclusion. This study is a pioneering effort in leveraging AI for impingement prediction in THA, utilizing a comprehensive, real-world clinical dataset. Our machine-learning algorithm demonstrated promising accuracy in predicting impingement, its type, and direction. While the addition of imaging data to our deep-learning algorithm did not boost accuracy, the potential for refined annotations, such as landmark markings, offers avenues for future enhancement. Prior to clinical integration, external validation and larger-scale testing of this algorithm are essential. Cite this article: Bone Jt Open 2024;5(8):671–680


Bone & Joint Research
Vol. 13, Issue 7 | Pages 362 - 371
17 Jul 2024
Chang H Liu L Zhang Q Xu G Wang J Chen P Li C Guo X Yang Z Zhang F

Aims. The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA. Methods. Cartilage samples from patients with KBD (n = 10) and patients with OA (n = 10) were collected during total knee arthroplasty surgery. An untargeted metabolomics approach using liquid chromatography coupled with mass spectrometry (LC-MS) was conducted to investigate the metabolomics profiles of KBD and OA. LC-MS raw data files were converted into mzXML format and then processed by the XCMS, CAMERA, and metaX toolbox implemented with R software. The online Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the metabolites by matching the exact molecular mass data of samples with those from the database. Results. A total of 807 ion features were identified for KBD and OA, including 577 positive (240 for upregulated and 337 for downregulated) and 230 negative (107 for upregulated and 123 for downregulated) ions. After annotation, LC-MS identified significant expressions of ten upregulated and eight downregulated second-level metabolites, and 183 upregulated and 162 downregulated first-level metabolites between KBD and OA. We identified differentially expressed second-level metabolites that are highly associated with cartilage damage, including dimethyl sulfoxide, uric acid, and betaine. These metabolites exist in sulphur metabolism, purine metabolism, and glycine, serine, and threonine metabolism. Conclusion. This comprehensive comparative analysis of metabolism in OA and KBD cartilage provides new evidence of differences in the pathogenetic mechanisms underlying cartilage damage in these two conditions. Cite this article: Bone Joint Res 2024;13(7):362–371


Bone & Joint Open
Vol. 5, Issue 6 | Pages 479 - 488
6 Jun 2024
Paksoy A Meller S Schwotzer F Moroder P Trampuz A Imiolczyk J Perka C Hackl M Plachel F Akgün D

Aims

Current diagnostic tools are not always able to effectively identify periprosthetic joint infections (PJIs). Recent studies suggest that circulating microRNAs (miRNAs) undergo changes under pathological conditions such as infection. The aim of this study was to analyze miRNA expression in hip arthroplasty PJI patients.

Methods

This was a prospective pilot study, including 24 patients divided into three groups, with eight patients each undergoing revision of their hip arthroplasty due to aseptic reasons, and low- and high-grade PJI, respectively. The number of intraoperative samples and the incidence of positive cultures were recorded for each patient. Additionally, venous blood samples and periarticular tissue samples were collected from each patient to determine miRNA expressions between the groups. MiRNA screening was performed by small RNA-sequencing using the miRNA next generation sequencing (NGS) discovery (miND) pipeline.


The Bone & Joint Journal
Vol. 106-B, Issue 6 | Pages 525 - 531
1 Jun 2024
MacDessi SJ van de Graaf VA Wood JA Griffiths-Jones W Bellemans J Chen DB

The aim of mechanical alignment in total knee arthroplasty is to align all knees into a fixed neutral position, even though not all knees are the same. As a result, mechanical alignment often alters a patient’s constitutional alignment and joint line obliquity, resulting in soft-tissue imbalance. This annotation provides an overview of how the Coronal Plane Alignment of the Knee (CPAK) classification can be used to predict imbalance with mechanical alignment, and then offers practical guidance for bone balancing, minimizing the need for soft-tissue releases. Cite this article: Bone Joint J 2024;106-B(6):525–531


Bone & Joint Research
Vol. 13, Issue 5 | Pages 237 - 246
17 May 2024
Cheng B Wu C Wei W Niu H Wen Y Li C Chen P Chang H Yang Z Zhang F

Aims

To assess the alterations in cell-specific DNA methylation associated with chondroitin sulphate response using peripheral blood collected from Kashin-Beck disease (KBD) patients before initiation of chondroitin sulphate treatment.

Methods

Peripheral blood samples were collected from KBD patients at baseline of chondroitin sulphate treatment. Methylation profiles were generated using reduced representation bisulphite sequencing (RRBS) from peripheral blood. Differentially methylated regions (DMRs) were identified using MethylKit, while DMR-related genes were defined as those annotated to the gene body or 2.2-kilobase upstream regions of DMRs. Selected DMR-related genes were further validated by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) to assess expression levels. Tensor composition analysis was performed to identify cell-specific differential DNA methylation from bulk tissue.


The Bone & Joint Journal
Vol. 106-B, Issue 5 | Pages 430 - 434
1 May 2024
Eardley WGP


The Bone & Joint Journal
Vol. 106-B, Issue 4 | Pages 312 - 318
1 Apr 2024
Sheth NP Jones SA Sanghavi SA Manktelow A

The advent of modular porous metal augments has ushered in a new form of treatment for acetabular bone loss. The function of an augment can be seen as reducing the size of a defect or reconstituting the anterosuperior/posteroinferior columns and/or allowing supplementary fixation. Depending on the function of the augment, the surgeon can decide on the sequence of introduction of the hemispherical shell, before or after the augment. Augments should always, however, be used with cement to form a unit with the acetabular component. Given their versatility, augments also allow the use of a hemispherical shell in a position that restores the centre of rotation and biomechanics of the hip. Progressive shedding or the appearance of metal debris is a particular finding with augments and, with other radiological signs of failure, should be recognized on serial radiographs. Mid- to long-term outcomes in studies reporting the use of augments with hemispherical shells in revision total hip arthroplasty have shown rates of survival of > 90%. However, a higher risk of failure has been reported when augments have been used for patients with chronic pelvic discontinuity.

Cite this article: Bone Joint J 2024;106-B(4):312–318.


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. Results. A total of 46 genes were obtained from the intersection of significantly upregulated genes in osteoarthritic cartilage and the key module genes screened by WGCNA. Functional annotation analysis revealed that these genes were closely related to pathological responses associated with OA, such as inflammation and immunity. Four key dysregulated genes (cartilage acidic protein 1 (CRTAC1), iodothyronine deiodinase 2 (DIO2), angiopoietin-related protein 2 (ANGPTL2), and MAGE family member D1 (MAGED1)) were identified after using machine-learning algorithms. These genes had high diagnostic value in both the training cohort and external validation cohort (receiver operating characteristic > 0.8). The upregulated expression of these hub genes in osteoarthritic cartilage signified higher levels of immune infiltration as well as the expression of metalloproteinases and mineralization markers, suggesting harmful biological alterations and indicating that these hub genes play an important role in the pathogenesis of OA. A competing endogenous RNA network was constructed to reveal the underlying post-transcriptional regulatory mechanisms. Conclusion. The current study explores and validates a dysregulated key gene set in osteoarthritic cartilage that is capable of accurately diagnosing OA and characterizing the biological alterations in osteoarthritic cartilage; this may become a promising indicator in clinical decision-making. This study indicates that dysregulated key genes play an important role in the development and progression of OA, and may be potential therapeutic targets. Cite this article: Bone Joint Res 2024;13(2):66–82