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Bone & Joint 360
Vol. 13, Issue 4 | Pages 43 - 45
2 Aug 2024
Evans JT Evans JP Whitehouse MR


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.


The Bone & Joint Journal
Vol. 106-B, Issue 7 | Pages 744 - 750
1 Jul 2024
Saeed A Bradley CS Verma Y Kelley SP

Aims

Radiological residual acetabular dysplasia (RAD) has been reported in up to 30% of children who had successful brace treatment of infant developmental dysplasia of the hip (DDH). Predicting those who will resolve and those who may need corrective surgery is important to optimize follow-up protocols. In this study we have aimed to identify the prevalence and predictors of RAD at two years and five years post-bracing.

Methods

This was a single-centre, prospective longitudinal cohort study of infants with DDH managed using a published, standardized Pavlik harness protocol between January 2012 and December 2016. RAD was measured at two years’ mean follow-up using acetabular index-lateral edge (AI-L) and acetabular index-sourcil (AI-S), and at five years using AI-L, AI-S, centre-edge angle (CEA), and acetabular depth ratio (ADR). Each hip was classified based on published normative values for normal, borderline (1 to 2 standard deviations (SDs)), or dysplastic (> 2 SDs) based on sex, age, and laterality.


Bone & Joint Open
Vol. 5, Issue 5 | Pages 411 - 418
20 May 2024
Schneider P Bajammal S Leighton R Witges K Rondeau K Duffy P

Aims

Isolated fractures of the ulnar diaphysis are uncommon, occurring at a rate of 0.02 to 0.04 per 1,000 cases. Despite their infrequency, these fractures commonly give rise to complications, such as nonunion, limited forearm pronation and supination, restricted elbow range of motion, radioulnar synostosis, and prolonged pain. Treatment options for this injury remain a topic of debate, with limited research available and no consensus on the optimal approach. Therefore, this trial aims to compare clinical, radiological, and functional outcomes of two treatment methods: open reduction and internal fixation (ORIF) versus nonoperative treatment in patients with isolated ulnar diaphyseal fractures.

Methods

This will be a multicentre, open-label, parallel randomized clinical trial (under National Clinical Trial number NCT01123447), accompanied by a parallel prospective cohort group for patients who meet the inclusion criteria, but decline randomization. Eligible patients will be randomized to one of the two treatment groups: 1) nonoperative treatment with closed reduction and below-elbow casting; or 2) surgical treatment with ORIF utilizing a limited contact dynamic compression plate and screw construct. The primary outcome measured will be the Disabilities of the Arm, Shoulder and Hand questionnaire score at 12 months post-injury. Additionally, functional outcomes will be assessed using the 36-Item Short Form Health Survey and pain visual analogue scale, allowing for a comparison of outcomes between groups. Secondary outcome measures will encompass clinical outcomes such as range of motion and grip strength, radiological parameters including time to union, as well as economic outcomes assessed from enrolment to 12 months post-injury.


The Bone & Joint Journal
Vol. 106-B, Issue 5 | Pages 492 - 500
1 May 2024
Miwa S Yamamoto N Hayashi K Takeuchi A Igarashi K Tada K Taniguchi Y Morinaga S Asano Y Tsuchiya H

Aims

Surgical site infection (SSI) after soft-tissue sarcoma (STS) resection is a serious complication. The purpose of this retrospective study was to investigate the risk factors for SSI after STS resection, and to develop a nomogram that allows patient-specific risk assessment.

Methods

A total of 547 patients with STS who underwent tumour resection between 2005 and 2021 were divided into a development cohort and a validation cohort. In the development cohort of 402 patients, the least absolute shrinkage and selection operator (LASSO) regression model was used to screen possible risk factors of SSI. To select risk factors and construct the prediction nomogram, multivariate logistic regression was used. The predictive power of the nomogram was evaluated by receiver operating curve (ROC) analysis in the validation cohort of 145 patients.


The Bone & Joint Journal
Vol. 106-B, Issue 4 | Pages 412 - 418
1 Apr 2024
Alqarni AG Nightingale J Norrish A Gladman JRF Ollivere B

Aims

Frailty greatly increases the risk of adverse outcome of trauma in older people. Frailty detection tools appear to be unsuitable for use in traumatically injured older patients. We therefore aimed to develop a method for detecting frailty in older people sustaining trauma using routinely collected clinical data.

Methods

We analyzed prospectively collected registry data from 2,108 patients aged ≥ 65 years who were admitted to a single major trauma centre over five years (1 October 2015 to 31 July 2020). We divided the sample equally into two, creating derivation and validation samples. In the derivation sample, we performed univariate analyses followed by multivariate regression, starting with 27 clinical variables in the registry to predict Clinical Frailty Scale (CFS; range 1 to 9) scores. Bland-Altman analyses were performed in the validation cohort to evaluate any biases between the Nottingham Trauma Frailty Index (NTFI) and the CFS.


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.


Bone & Joint Research
Vol. 13, Issue 1 | Pages 19 - 27
5 Jan 2024
Baertl S Rupp M Kerschbaum M Morgenstern M Baumann F Pfeifer C Worlicek M Popp D Amanatullah DF Alt V

Aims

This study aimed to evaluate the clinical application of the PJI-TNM classification for periprosthetic joint infection (PJI) by determining intraobserver and interobserver reliability. To facilitate its use in clinical practice, an educational app was subsequently developed and evaluated.

Methods

A total of ten orthopaedic surgeons classified 20 cases of PJI based on the PJI-TNM classification. Subsequently, the classification was re-evaluated using the PJI-TNM app. Classification accuracy was calculated separately for each subcategory (reinfection, tissue and implant condition, non-human cells, and morbidity of the patient). Fleiss’ kappa and Cohen’s kappa were calculated for interobserver and intraobserver reliability, respectively.


Bone & Joint Research
Vol. 12, Issue 12 | Pages 702 - 711
1 Dec 2023
Xue Y Zhou L Wang J

Aims

Knee osteoarthritis (OA) involves a variety of tissues in the joint. Gene expression profiles in different tissues are of great importance in order to understand OA.

Methods

First, we obtained gene expression profiles of cartilage, synovium, subchondral bone, and meniscus from the Gene Expression Omnibus (GEO). Several datasets were standardized by merging and removing batch effects. Then, we used unsupervised clustering to divide OA into three subtypes. The gene ontology and pathway enrichment of three subtypes were analyzed. CIBERSORT was used to evaluate the infiltration of immune cells in different subtypes. Finally, OA-related genes were obtained from the Molecular Signatures Database for validation, and diagnostic markers were screened according to clinical characteristics. Quantitative reverse transcription polymerase chain reaction (qRT‐PCR) was used to verify the effectiveness of markers.


Bone & Joint Open
Vol. 4, Issue 10 | Pages 750 - 757
10 Oct 2023
Brenneis M Thewes N Holder J Stief F Braun S

Aims

Accurate skeletal age and final adult height prediction methods in paediatric orthopaedics are crucial for determining optimal timing of growth-guiding interventions and minimizing complications in treatments of various conditions. This study aimed to evaluate the accuracy of final adult height predictions using the central peak height (CPH) method with long leg X-rays and four different multiplier tables.

Methods

This study included 31 patients who underwent temporary hemiepiphysiodesis for varus or valgus deformity of the leg between 2014 and 2020. The skeletal age at surgical intervention was evaluated using the CPH method with long leg radiographs. The true final adult height (FHTRUE) was determined when the growth plates were closed. The final height prediction accuracy of four different multiplier tables (1. Bayley and Pinneau; 2. Paley et al; 3. Sanders – Greulich and Pyle (SGP); and 4. Sanders – peak height velocity (PHV)) was then compared using either skeletal age or chronological age.


Bone & Joint Research
Vol. 12, Issue 9 | Pages 590 - 597
20 Sep 2023
Uemura K Otake Y Takashima K Hamada H Imagama T Takao M Sakai T Sato Y Okada S Sugano N

Aims

This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images.

Methods

The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a calibration phantom were automatically segmented using previously trained deep-learning models. The Hounsfield units of each voxel were converted into density (mg/cm3). Then, a deep-learning model trained by manual landmark selection of 315 cases was developed to select the landmarks at the proximal femur to rotate the CT volume to the neutral position. Finally, the CT volume of the femur was projected onto the coronal plane, and the areal BMD of the proximal femur (CT-aBMD) was quantified. CT-aBMD correlated to DXA-BMD, and a receiver operating characteristic (ROC) analysis quantified the accuracy in diagnosing osteoporosis.


Aims

The purpose of this study was to assess the reliability and responsiveness to hip surgery of a four-point modified Care and Comfort Hypertonicity Questionnaire (mCCHQ) scoring tool in children with cerebral palsy (CP) in Gross Motor Function Classification System (GMFCS) levels IV and V.

Methods

This was a population-based cohort study in children with CP from a national surveillance programme. Reliability was assessed from 20 caregivers who completed the mCCHQ questionnaire on two occasions three weeks apart. Test-retest reliability of the mCCHQ was calculated, and responsiveness before and after surgery for a displaced hip was evaluated in a cohort of children.


Bone & Joint Research
Vol. 12, Issue 8 | Pages 494 - 496
9 Aug 2023
Clement ND Simpson AHRW

Cite this article: Bone Joint Res 2023;12(8):494–496.


Bone & Joint Research
Vol. 12, Issue 7 | Pages 433 - 446
7 Jul 2023
Guo L Guo H Zhang Y Chen Z Sun J Wu G Wang Y Zhang Y Wei X Li P

Aims

To explore the novel molecular mechanisms of histone deacetylase 4 (HDAC4) in chondrocytes via RNA sequencing (RNA-seq) analysis.

Methods

Empty adenovirus (EP) and a HDAC4 overexpression adenovirus were transfected into cultured human chondrocytes. The cell survival rate was examined by real-time cell analysis (RTCA) and EdU and flow cytometry assays. Cell biofunction was detected by Western blotting. The expression profiles of messenger RNAs (mRNAs) in the EP and HDAC4 transfection groups were assessed using whole-transcriptome sequencing (RNA-seq). Volcano plot, Gene Ontology, and pathway analyses were performed to identify differentially expressed genes (DEGs). For verification of the results, the A289E/S246/467/632 A sites of HDAC4 were mutated to enhance the function of HDAC4 by increasing HDAC4 expression in the nucleus. RNA-seq was performed to identify the molecular mechanism of HDAC4 in chondrocytes. Finally, the top ten DEGs associated with ribosomes were verified by quantitative polymerase chain reaction (QPCR) in chondrocytes, and the top gene was verified both in vitro and in vivo.


Bone & Joint Open
Vol. 4, Issue 6 | Pages 399 - 407
1 Jun 2023
Yeramosu T Ahmad W Satpathy J Farrar JM Golladay GJ Patel NK

Aims

To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA.

Methods

Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models.


Bone & Joint Research
Vol. 12, Issue 3 | Pages 165 - 177
1 Mar 2023
Boyer P Burns D Whyne C

Aims

An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodologies for detecting and classifying inertial data collected during in-clinic and at-home shoulder physiotherapy exercise.

Methods

A smartwatch was used to collect inertial data from 42 patients performing shoulder physiotherapy exercises for rotator cuff injuries in both in-clinic and at-home settings. A two-stage ML approach was used to detect out-of-distribution (OOD) data (to remove non-exercise data) and subsequently for classification of exercises. We evaluated the performance impact of grouping exercises by motion type, inclusion of non-exercise data for algorithm training, and a patient-specific approach to exercise classification. Algorithm performance was evaluated using both in-clinic and at-home data.


Bone & Joint Research
Vol. 12, Issue 1 | Pages 80 - 90
20 Jan 2023
Xu J Si H Zeng Y Wu Y Zhang S Liu Y Li M Shen B

Aims

Degenerative cervical spondylosis (DCS) is a common musculoskeletal disease that encompasses a wide range of progressive degenerative changes and affects all components of the cervical spine. DCS imposes very large social and economic burdens. However, its genetic basis remains elusive.

Methods

Predicted whole-blood and skeletal muscle gene expression and genome-wide association study (GWAS) data from a DCS database were integrated, and functional summary-based imputation (FUSION) software was used on the integrated data. A transcriptome-wide association study (TWAS) was conducted using FUSION software to assess the association between predicted gene expression and DCS risk. The TWAS-identified genes were verified via comparison with differentially expressed genes (DEGs) in DCS RNA expression profiles in the Gene Expression Omnibus (GEO) (Accession Number: GSE153761). The Functional Mapping and Annotation (FUMA) tool for genome-wide association studies and Meta tools were used for gene functional enrichment and annotation analysis.


The Bone & Joint Journal
Vol. 104-B, Issue 12 | Pages 1292 - 1303
1 Dec 2022
Polisetty TS Jain S Pang M Karnuta JM Vigdorchik JM Nawabi DH Wyles CC Ramkumar PN

Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered.

Cite this article: Bone Joint J 2022;104-B(12):1292–1303.


Aims

This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue.

Methods

The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed.


The Bone & Joint Journal
Vol. 104-B, Issue 9 | Pages 1011 - 1016
1 Sep 2022
Acem I van de Sande MAJ

Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS.

Cite this article: Bone Joint J 2022;104-B(9):1011–1016.


The Bone & Joint Journal
Vol. 104-B, Issue 8 | Pages 963 - 971
1 Aug 2022
Sun Z Liu W Liu H Li J Hu Y Tu B Wang W Fan C

Aims

Heterotopic ossification (HO) is a common complication after elbow trauma and can cause severe upper limb disability. Although multiple prognostic factors have been reported to be associated with the development of post-traumatic HO, no model has yet been able to combine these predictors more succinctly to convey prognostic information and medical measures to patients. Therefore, this study aimed to identify prognostic factors leading to the formation of HO after surgery for elbow trauma, and to establish and validate a nomogram to predict the probability of HO formation in such particular injuries.

Methods

This multicentre case-control study comprised 200 patients with post-traumatic elbow HO and 229 patients who had elbow trauma but without HO formation between July 2019 and December 2020. Features possibly associated with HO formation were obtained. The least absolute shrinkage and selection operator regression model was used to optimize feature selection. Multivariable logistic regression analysis was applied to build the new nomogram: the Shanghai post-Traumatic Elbow Heterotopic Ossification Prediction model (STEHOP). STEHOP was validated by concordance index (C-index) and calibration plot. Internal validation was conducted using bootstrapping validation.


Bone & Joint Open
Vol. 3, Issue 7 | Pages 573 - 581
1 Jul 2022
Clement ND Afzal I Peacock CJH MacDonald D Macpherson GJ Patton JT Asopa V Sochart DH Kader DF

Aims

The aims of this study were to assess mapping models to predict the three-level version of EuroQoL five-dimension utility index (EQ-5D-3L) from the Oxford Knee Score (OKS) and validate these before and after total knee arthroplasty (TKA).

Methods

A retrospective cohort of 5,857 patients was used to create the prediction models, and a second cohort of 721 patients from a different centre was used to validate the models, all of whom underwent TKA. Patient characteristics, BMI, OKS, and EQ-5D-3L were collected preoperatively and one year postoperatively. Generalized linear regression was used to formulate the prediction models.


The Bone & Joint Journal
Vol. 104-B, Issue 5 | Pages 640 - 644
1 May 2022
Gaston MS Wordie SJ Wagner P Hägglund G Robb JE

Aims

The Uppföljningsprogram för cerebral pares (CPUP) Hip Score distinguishes between children with cerebral palsy (CP) at different levels of risk for displacement of the hip. The score was constructed using data from Swedish children with CP, but has not been confirmed in any other population. The aim of this study was to determine the calibration and discriminatory accuracy of this score in children with CP in Scotland.

Methods

This was a total population-based study of children registered with the Cerebral Palsy Integrated Pathway Scotland. Displacement of the hip was defined as a migration percentage (MP) of > 40%. Inclusion criteria were children in Gross Motor Function Classification System (GMFCS) levels III to V. The calibration slope was estimated and Kaplan-Meier curves produced for five strata of CPUP scores to compare the observed with the predicted risk of displacement of the hip at five years. For discriminatory accuracy, the time-dependent area under the receiver operating characteristic curve (AUC) was estimated. In order to analyze differences in the performance of the score between cohorts, score weights, and subsequently the AUC, were re-estimated using the variables of the original score: the child’s age at the first examination, GMFCS level, head shaft angle, and MP of the worst hip in a logistic regression with imputation of outcomes for those with incomplete follow-up.


Bone & Joint Open
Vol. 3, Issue 3 | Pages 211 - 217
1 Mar 2022
Hsu C Chen C Wang S Huang J Tong K Huang K

Aims

The Coronal Plane Alignment of the Knee (CPAK) classification is a simple and comprehensive system for predicting pre-arthritic knee alignment. However, when the CPAK classification is applied in the Asian population, which is characterized by more varus and wider distribution in lower limb alignment, modifications in the boundaries of arithmetic hip-knee-ankle angle (aHKA) and joint line obliquity (JLO) should be considered. The purposes of this study were as follows: first, to propose a modified CPAK classification based on the actual joint line obliquity (aJLO) and wider range of aHKA in the Asian population; second, to test this classification in a cohort of Asians with healthy knees; third, to propose individualized alignment targets for different CPAK types in kinematically aligned (KA) total knee arthroplasty (TKA).

Methods

The CPAK classification was modified by changing the neutral boundaries of aHKA to 0° ± 3° and using aJLO as a new variable. Radiological analysis of 214 healthy knees in 214 Asian individuals was used to assess the distribution and mean value of alignment angles of each phenotype among different classifications based on the coronal plane. Individualized alignment targets were set according to the mean lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA) of different knee types.


Bone & Joint Open
Vol. 3, Issue 2 | Pages 114 - 122
1 Feb 2022
Green GL Arnander M Pearse E Tennent D

Aims

Recurrent dislocation is both a cause and consequence of glenoid bone loss, and the extent of the bony defect is an indicator guiding operative intervention. Literature suggests that loss greater than 25% requires glenoid reconstruction. Measuring bone loss is controversial; studies use different methods to determine this, with no clear evidence of reproducibility. A systematic review was performed to identify existing CT-based methods of quantifying glenoid bone loss and establish their reliability and reproducibility

Methods

A Preferred Reporting Items for Systematic reviews and Meta-Analyses-compliant systematic review of conventional and grey literature was performed.


Bone & Joint Research
Vol. 10, Issue 12 | Pages 820 - 829
15 Dec 2021
Schmidutz F Schopf C Yan SG Ahrend M Ihle C Sprecher C

Aims

The distal radius is a major site of osteoporotic bone loss resulting in a high risk of fragility fracture. This study evaluated the capability of a cortical index (CI) at the distal radius to predict the local bone mineral density (BMD).

Methods

A total of 54 human cadaver forearms (ten singles, 22 pairs) (19 to 90 years) were systematically assessed by clinical radiograph (XR), dual-energy X-ray absorptiometry (DXA), CT, as well as high-resolution peripheral quantitative CT (HR-pQCT). Cortical bone thickness (CBT) of the distal radius was measured on XR and CT scans, and two cortical indices mean average (CBTavg) and gauge (CBTg) were determined. These cortical indices were compared to the BMD of the distal radius determined by DXA (areal BMD (aBMD)) and HR-pQCT (volumetric BMD (vBMD)). Pearson correlation coefficient (r) and intraclass correlation coefficient (ICC) were used to compare the results and degree of reliability.


The Bone & Joint Journal
Vol. 103-B, Issue 12 | Pages 1754 - 1758
1 Dec 2021
Farrow L Zhong M Ashcroft GP Anderson L Meek RMD

There is increasing popularity in the use of artificial intelligence and machine-learning techniques to provide diagnostic and prognostic models for various aspects of Trauma & Orthopaedic surgery. However, correct interpretation of these models is difficult for those without specific knowledge of computing or health data science methodology. Lack of current reporting standards leads to the potential for significant heterogeneity in the design and quality of published studies. We provide an overview of machine-learning techniques for the lay individual, including key terminology and best practice reporting guidelines.

Cite this article: Bone Joint J 2021;103-B(12):1754–1758.


The Bone & Joint Journal
Vol. 103-B, Issue 8 | Pages 1405 - 1413
1 Aug 2021
Ogura K Fujiwara T Morris CD Boland PJ Healey JH

Aims

Rotating-hinge knee prostheses are commonly used to reconstruct the distal femur after resection of a tumour, despite the projected long-term burden of reoperation due to complications. Few studies have examined the factors that influence their failure and none, to our knowledge, have used competing risk models to do so. The purpose of this study was to determine the risk factors for failure of a rotating-hinge knee distal femoral arthroplasty using the Fine-Gray competing risk model.

Methods

We retrospectively reviewed 209 consecutive patients who, between 1991 and 2016, had undergone resection of the distal femur for tumour and reconstruction using a rotating-hinge knee prosthesis. The study endpoint was failure of the prosthesis, defined as removal of the femoral component, the tibial component, or the bone-implant fixation; major revision (exchange of the femoral component, tibial component, or the bone-implant fixation); or amputation.


Bone & Joint Open
Vol. 2, Issue 7 | Pages 493 - 502
12 Jul 2021
George SZ Yan X Luo S Olson SA Reinke EK Bolognesi MP Horn ME

Aims

Patient-reported outcome measures have become an important part of routine care. The aim of this study was to determine if Patient-Reported Outcomes Measurement Information System (PROMIS) measures can be used to create patient subgroups for individuals seeking orthopaedic care.

Methods

This was a cross-sectional study of patients from Duke University Department of Orthopaedic Surgery clinics (14 ambulatory and four hospital-based). There were two separate cohorts recruited by convenience sampling (i.e. patients were included in the analysis only if they completed PROMIS measures during a new patient visit). Cohort #1 (n = 12,141; December 2017 to December 2018,) included PROMIS short forms for eight domains (Physical Function, Pain Interference, Pain Intensity, Depression, Anxiety, Sleep Quality, Participation in Social Roles, and Fatigue) and Cohort #2 (n = 4,638; January 2019 to August 2019) included PROMIS Computer Adaptive Testing instruments for four domains (Physical Function, Pain Interference, Depression, and Sleep Quality). Cluster analysis (K-means method) empirically derived subgroups and subgroup differences in clinical and sociodemographic factors were identified with one-way analysis of variance.


Bone & Joint Open
Vol. 2, Issue 6 | Pages 388 - 396
1 Jun 2021
Khoshbin A Hoit G Nowak LL Daud A Steiner M Juni P Ravi B Atrey A

Aims

While preoperative bloodwork is routinely ordered, its value in determining which patients are at risk of postoperative readmission following total knee arthroplasty (TKA) and total hip arthroplasty (THA) is unclear. The objective of this study was to determine which routinely ordered preoperative blood markers have the strongest association with acute hospital readmission for patients undergoing elective TKA and THA.

Methods

Two population-based retrospective cohorts were assembled for all adult primary elective TKA (n = 137,969) and THA (n = 78,532) patients between 2011 to 2018 across 678 North American hospitals using the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) registry. Six routinely ordered preoperative blood markers - albumin, haematocrit, platelet count, white blood cell count (WBC), estimated glomerular filtration rate (eGFR), and sodium level - were queried. The association between preoperative blood marker values and all-cause readmission within 30 days of surgery was compared using univariable analysis and multivariable logistic regression adjusted for relevant patient and treatment factors.


Bone & Joint Open
Vol. 2, Issue 6 | Pages 414 - 421
1 Jun 2021
Kim SK Nguyen C Avins AL Abrams GD

Aims

The aim of this study was to screen the entire genome for genetic markers associated with risk for anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) injury.

Methods

Genome-wide association (GWA) analyses were performed using data from the Kaiser Permanente Research Board (KPRB) and the UK Biobank. ACL and PCL injury cases were identified based on electronic health records from KPRB and the UK Biobank. GWA analyses from both cohorts were tested for ACL and PCL injury using a logistic regression model adjusting for sex, height, weight, age at enrolment, and race/ethnicity using allele counts for single nucleotide polymorphisms (SNPs). The data from the two GWA studies were combined in a meta-analysis. Candidate genes previously reported to show an association with ACL injury in athletes were also tested for association from the meta-analysis data from the KPRB and the UK Biobank GWA studies.


The Bone & Joint Journal
Vol. 103-B, Issue 4 | Pages 627 - 634
1 Apr 2021
Sabah SA Alvand A Beard DJ Price AJ

Aims

To estimate the measurement properties for the Oxford Knee Score (OKS) in patients undergoing revision knee arthroplasty (responsiveness, minimal detectable change (MDC-90), minimal important change (MIC), minimal important difference (MID), internal consistency, construct validity, and interpretability).

Methods

Secondary data analysis was performed for 10,727 patients undergoing revision knee arthroplasty between 2013 to 2019 using a UK national patient-reported outcome measure (PROM) dataset. Outcome data were collected before revision and at six months postoperatively, using the OKS and EuroQol five-dimension score (EQ-5D). Measurement properties were assessed according to COnsensus-based Standards for the selection of health status Measurement Instruments (COSMIN) guidelines.


Bone & Joint 360
Vol. 10, Issue 2 | Pages 47 - 50
1 Apr 2021


Bone & Joint Research
Vol. 10, Issue 3 | Pages 173 - 187
1 Mar 2021
Khury F Fuchs M Awan Malik H Leiprecht J Reichel H Faschingbauer M

Aims

To explore the clinical relevance of joint space width (JSW) narrowing on standardized-flexion (SF) radiographs in the assessment of cartilage degeneration in specific subregions seen on MRI sequences in knee osteoarthritis (OA) with neutral, valgus, and varus alignments, and potential planning of partial knee arthroplasty.

Methods

We retrospectively reviewed 639 subjects, aged 45 to 79 years, in the Osteoarthritis Initiative (OAI) study, who had symptomatic knees with Kellgren and Lawrence grade 2 to 4. Knees were categorized as neutral, valgus, and varus knees by measuring hip-knee-angles on hip-knee-ankle radiographs. Femorotibial JSW was measured on posteroanterior SF radiographs using a special software. The femorotibial compartment was divided into 16 subregions, and MR-tomographic measurements of cartilage volume, thickness, and subchondral bone area were documented. Linear regression with adjustment for age, sex, body mass index, and Kellgren and Lawrence grade was used.


The Bone & Joint Journal
Vol. 103-B, Issue 2 | Pages 329 - 337
1 Feb 2021
MacDessi SJ Griffiths-Jones W Harris IA Bellemans J Chen DB

Aims

A comprehensive classification for coronal lower limb alignment with predictive capabilities for knee balance would be beneficial in total knee arthroplasty (TKA). This paper describes the Coronal Plane Alignment of the Knee (CPAK) classification and examines its utility in preoperative soft tissue balance prediction, comparing kinematic alignment (KA) to mechanical alignment (MA).

Methods

A radiological analysis of 500 healthy and 500 osteoarthritic (OA) knees was used to assess the applicability of the CPAK classification. CPAK comprises nine phenotypes based on the arithmetic HKA (aHKA) that estimates constitutional limb alignment and joint line obliquity (JLO). Intraoperative balance was compared within each phenotype in a cohort of 138 computer-assisted TKAs randomized to KA or MA. Primary outcomes included descriptive analyses of healthy and OA groups per CPAK type, and comparison of balance at 10° of flexion within each type. Secondary outcomes assessed balance at 45° and 90° and bone recuts required to achieve final knee balance within each CPAK type.


Bone & Joint 360
Vol. 10, Issue 1 | Pages 41 - 43
1 Feb 2021


The Bone & Joint Journal
Vol. 102-B, Issue 12 | Pages 1752 - 1759
1 Dec 2020
Tsuda Y Tsoi K Stevenson JD Laitinen M Ferguson PC Wunder JS Griffin AM van de Sande MAJ van Praag V Leithner A Fujiwara T Yasunaga H Matsui H Parry MC Jeys LM

Aims

Our aim was to develop and validate nomograms that would predict the cumulative incidence of sarcoma-specific death (CISSD) and disease progression (CIDP) in patients with localized high-grade primary central and dedifferentiated chondrosarcoma.

Methods

The study population consisted of 391 patients from two international sarcoma centres (development cohort) who had undergone definitive surgery for a localized high-grade (histological grade II or III) conventional primary central chondrosarcoma or dedifferentiated chondrosarcoma. Disease progression captured the first event of either metastasis or local recurrence. An independent cohort of 221 patients from three additional hospitals was used for external validation. Two nomograms were internally and externally validated for discrimination (c-index) and calibration plot.


The Bone & Joint Journal
Vol. 102-B, Issue 12 | Pages 1599 - 1607
1 Dec 2020
Marson BA Craxford S Deshmukh SR Grindlay DJC Manning JC Ollivere BJ

Aims

This study evaluates the quality of patient-reported outcome measures (PROMs) reported in childhood fracture trials and recommends outcome measures to assess and report physical function, functional capacity, and quality of life using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) standards.

Methods

A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant systematic review of OVID Medline, Embase, and Cochrane CENTRAL was performed to identify all PROMs reported in trials. A search of OVID Medline, Embase, and PsycINFO was performed to identify all PROMs with validation studies in childhood fractures. Development studies were identified through hand-searching. Data extraction was undertaken by two reviewers. Study quality and risk of bias was evaluated by COSMIN guidelines and recorded on standardized checklists.


The Bone & Joint Journal
Vol. 102-B, Issue 11 | Pages 1574 - 1581
2 Nov 2020
Zhang S Sun J Liu C Fang J Xie H Ning B

Aims

The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an effective diagnostic tool for DDH. Here, we aimed to develop an anteroposterior pelvic radiograph deep learning system for diagnosing DDH in children and analyze the feasibility of its application.

Methods

In total, 10,219 anteroposterior pelvic radiographs were retrospectively collected from April 2014 to December 2018. Clinicians labelled each radiograph using a uniform standard method. Radiographs were grouped according to age and into ‘dislocation’ (dislocation and subluxation) and ‘non-dislocation’ (normal cases and those with dysplasia of the acetabulum) groups based on clinical diagnosis. The deep learning system was trained and optimized using 9,081 radiographs; 1,138 test radiographs were then used to compare the diagnoses made by deep learning system and clinicians. The accuracy of the deep learning system was determined using a receiver operating characteristic curve, and the consistency of acetabular index measurements was evaluated using Bland-Altman plots.


The Bone & Joint Journal
Vol. 102-B, Issue 9 | Pages 1183 - 1193
14 Sep 2020
Anis HK Strnad GJ Klika AK Zajichek A Spindler KP Barsoum WK Higuera CA Piuzzi NS

Aims

The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors.

Methods

Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC.


Bone & Joint Research
Vol. 9, Issue 9 | Pages 593 - 600
1 Sep 2020
Lee J Koh Y Kim PS Kang KW Kwak YH Kang K

Aims

Unicompartmental knee arthroplasty (UKA) has become a popular method of treating knee localized osteoarthritis (OA). Additionally, the posterior cruciate ligament (PCL) is essential to maintaining the physiological kinematics and functions of the knee joint. Considering these factors, the purpose of this study was to investigate the biomechanical effects on PCL-deficient knees in medial UKA.

Methods

Computational simulations of five subject-specific models were performed for intact and PCL-deficient UKA with tibial slopes. Anteroposterior (AP) kinematics and contact stresses of the patellofemoral (PF) joint and the articular cartilage were evaluated under the deep-knee-bend condition.


The Bone & Joint Journal
Vol. 102-B, Issue 7 | Pages 890 - 898
1 Jul 2020
Cheung PWH Wong CKH Cheung JPY

Aims

The health-related quality of life (HRQoL) of paediatric patients with orthopaedic conditions and spinal deformity is important, but existing generic tools have their shortcomings. We aim to evaluate the use of Paediatric Quality of Life Inventory (PedsQL) 4.0 generic core scales in the paediatric population with specific comparisons between those with spinal and limb pathologies, and to explore the feasibility of using PedsQL for studying scoliosis patients’ HRQoL.

Methods

Paediatric patients attending a speciality outpatient clinic were recruited through consecutive sampling. Two groups of patients were included: idiopathic scoliosis, and paediatric orthopaedic upper and lower limb condition without scoliosis. Patients were asked to complete PedsQL 4.0 generic core scales, Youth version of 5-level EuroQol-5-dimension questionnaire, and Refined Scoliosis Research Society 22-item (SRS-22r) questionnaire. Statistical analyses included scores comparison between scoliosis and limb pathology patients using independent-samples t-test, and correlation tests of PedsQL and SRS-22r.


The Bone & Joint Journal
Vol. 102-B, Issue 6 Supple A | Pages 101 - 106
1 Jun 2020
Shah RF Bini SA Martinez AM Pedoia V Vail TP

Aims

The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance.

Methods

A group of 697 patients underwent a first-time revision of a total hip (THA) or total knee arthroplasty (TKA) at our institution between 2012 and 2018. Preoperative anteroposterior (AP) and lateral radiographs, and historical and comorbidity information were collected from their electronic records. Each patient was defined as having loose or fixed components based on the operation notes. We trained a series of convolutional neural network (CNN) models to predict a diagnosis of loosening at the time of surgery from the preoperative radiographs. We then added historical data about the patients to the best performing model to create a final model and tested it on an independent dataset.


Bone & Joint Open
Vol. 1, Issue 3 | Pages 41 - 46
18 Mar 2020
Perry DC Arch B Appelbe D Francis P Spowart C Knight M

Introduction

There is widespread variation in the management of rare orthopaedic disease, in a large part owing to uncertainty. No individual surgeon or hospital is typically equipped to amass sufficient numbers of cases to draw robust conclusions from the information available to them. The programme of research will establish the British Orthopaedic Surgery Surveillance (BOSS) Study; a nationwide reporting structure for rare disease in orthopaedic surgery.

Methods

The BOSS Study is a series of nationwide observational cohort studies of pre-specified orthopaedic disease. All relevant hospitals treating the disease are invited to contribute anonymised case details. Data will be collected digitally through REDCap, with an additional bespoke software solution used to regularly confirm case ascertainment, prompt follow-up reminders and identify potential missing cases from external sources of information (i.e. national administrative data). With their consent, patients will be invited to enrich the data collected by supplementing anonymised case data with patient reported outcomes.

The study will primarily seek to calculate the incidence of the rare diseases under investigation, with 95% confidence intervals. Descriptive statistics will be used to describe the case mix, treatment variations and outcomes. Inferential statistical analysis may be used to analyze associations between presentation factors and outcomes. Types of analyses will be contingent on the disease under investigation.


The Bone & Joint Journal
Vol. 102-B, Issue 3 | Pages 388 - 393
1 Mar 2020
French SR Kaila R Munir S Wood DG

Aims

To validate the Sydney Hamstring Origin Rupture Evaluation (SHORE), a hamstring-specific clinical assessment tool to evaluate patient outcomes following surgical treatment.

Methods

A prospective study of 70 unilateral hamstring surgical repairs, with a mean age of 47.3 years (15 to 73). Patients completed the SHORE preoperatively and at six months post-surgery, and then completed both the SHORE and Perth Hamstring Assessment Tool (PHAT) at three years post-surgery. The SHORE questionnaire was validated through the evaluation of its psychometric properties, including; internal consistency, reproducibility, reliability, sensitivity to change, and ceiling effect. Construct validity was assessed using Pearson’s correlation analysis to examine the strength of association between the SHORE and the PHAT.


The Bone & Joint Journal
Vol. 102-B, Issue 2 | Pages 254 - 260
1 Feb 2020
Cheung JPY Cheung PWH

Aims. The aim of this study was to assess whether supine flexibility predicts the likelihood of curve progression in patients with adolescent idiopathic scoliosis (AIS) undergoing brace treatment. Methods. This was a retrospective analysis of patients with AIS prescribed with an underarm brace between September 2008 to April 2013 and followed up until 18 years of age or required surgery. Patients with structural proximal curves that preclude underarm bracing, those who were lost to follow-up, and those who had poor compliance to bracing (<16 hours a day) were excluded. The major curve Cobb angle, curve type, and location were measured on the pre-brace standing posteroanterior (PA) radiograph, supine whole spine radiograph, initial in-brace standing PA radiograph, and the post-brace weaning standing PA radiograph. Validation of the previous in-brace Cobb angle regression model was performed. The outcome of curve progression post-bracing was tested using a logistic regression model. The supine flexibility cut-off for curve progression was analyzed with receiver operating characteristic curve. Results. A total of 586 patients with mean age of 12.6 years (SD 1.2) remained for analysis after exclusion. The baseline Cobb angle was similar for thoracic major curves (31.6° (SD 3.8°)) and lumbar major curves (30.3° (SD 3.7°)). Curve progression was more common in the thoracic curves than lumbar curves with mean final Cobb angles of 40.5° (SD 12.5°) and 31.8° (SD 9.8°) respectively. This dataset matched the prediction model for in-brace Cobb angle with less mean absolute error in thoracic curves (0.61) as compared to lumbar curves (1.04). Reduced age and Risser stage, thoracic curves, increased pre-brace Cobb angle, and reduced correction and flexibility rates predicted increased likelihood of curve progression. Flexibility rate of more than 28% has likelihood of preventing curve progression with bracing. Conclusion. Supine radiographs provide satisfactory prediction for in-brace correction and post-bracing curve magnitude. The flexibility of the curve is a guide to determine the likelihood for brace success. Cite this article: Bone Joint J 2020;102-B(2):254–260


The Bone & Joint Journal
Vol. 102-B, Issue 1 | Pages 72 - 81
1 Jan 2020
Downie S Lai FY Joss J Adamson D Jariwala AC

Aims

The early mortality in patients with hip fractures from bony metastases is unknown. The objectives of this study were to quantify 30- and 90-day mortality in patients with proximal femoral metastases, and to create a mortality prediction tool based on biomarkers associated with early death.

Methods

This was a retrospective cohort study of consecutive patients referred to the orthopaedic department at a UK trauma centre with a proximal femoral metastasis (PFM) over a seven-year period (2010 to 2016). The study group were compared to a matched control group of non-metastatic hip fractures. Minimum follow-up was one year.


The Bone & Joint Journal
Vol. 101-B, Issue 11 | Pages 1447 - 1458
1 Nov 2019
Chatziagorou G Lindahl H Kärrholm J

Aims

We investigated patient characteristics and outcomes of Vancouver type B periprosthetic fractures treated with femoral component revision and/or osteosynthesis.

Patients and Methods

The study utilized data from the Swedish Hip Arthroplasty Register (SHAR) and information from patient records. We included all primary total hip arthroplasties (THAs) performed in Sweden since 1979, and undergoing further surgery due to Vancouver type B periprosthetic femoral fracture between 2001 and 2011. The primary outcome measure was any further reoperation between 2001 and 2013. Cross-referencing with the National Patient Register was performed in two stages, in order to identify all surgical procedures not recorded on the SHAR.


Bone & Joint Research
Vol. 8, Issue 7 | Pages 290 - 303
1 Jul 2019
Li H Yang HH Sun ZG Tang HB Min JK

Objectives

The aim of this study was to provide a comprehensive understanding of alterations in messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) in cartilage affected by osteoarthritis (OA).

Methods

The expression profiles of mRNAs, lncRNAs, and circRNAs in OA cartilage were assessed using whole-transcriptome sequencing. Bioinformatics analyses included prediction and reannotation of novel lncRNAs and circRNAs, their classification, and their placement into subgroups. Gene ontology and pathway analysis were performed to identify differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed circRNAs (DECs). We focused on the overlap of DEGs and targets of DELs previously identified in seven high-throughput studies. The top ten DELs were verified by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in articular chondrocytes, both in vitro and in vivo.


The Bone & Joint Journal
Vol. 101-B, Issue 6 | Pages 708 - 714
1 Jun 2019
Metcalfe D Costa ML Parsons NR Achten J Masters J Png ME Lamb SE Griffin XL

Aims

This study sought to determine the proportion of older adults with hip fractures captured by a multicentre prospective cohort, the World Hip Trauma Evaluation (WHiTE), whether there was evidence of selection bias during WHiTE recruitment, and the extent to which the WHiTE cohort is representative of the broader population of older adults with hip fractures.

Patients and Methods

The characteristics of patients recruited into the WHiTE cohort study were compared with those treated at WHiTE hospitals during the same timeframe and submitted to the National Hip Fracture Database (NHFD).