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Bone & Joint Research
Vol. 13, Issue 5 | Pages 201 - 213
1 May 2024
Hamoodi Z Gehringer CK Bull LM Hughes T Kearsley-Fleet L Sergeant JC Watts AC

Aims. The aims of this study were to identify and evaluate the current literature examining the prognostic factors which are associated with failure of total elbow arthroplasty (TEA). Methods. Electronic literature searches were conducted using MEDLINE, Embase, PubMed, and Cochrane. All studies reporting prognostic estimates for factors associated with the revision of a primary TEA were included. The risk of bias was assessed using the Quality In Prognosis Studies (QUIPS) tool, and the quality of evidence was assessed using the modified Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework. Due to low quality of the evidence and the heterogeneous nature of the studies, a narrative synthesis was used. Results. A total of 19 studies met the inclusion criteria, investigating 28 possible prognostic factors. Most QUIPS domains (84%) were rated as moderate to high risk of bias. The quality of the evidence was low or very low for all prognostic factors. In low-quality evidence, prognostic factors with consistent associations with failure of TEA in more than one study were: the sequelae of trauma leading to TEA, either independently or combined with acute trauma, and male sex. Several other studies investigating sex reported no association. The evidence for other factors was of very low quality and mostly involved exploratory studies. Conclusion. The current evidence investigating the prognostic factors associated with failure of TEA is of low or very low quality, and studies generally have a moderate to high risk of bias. Prognostic factors are subject to uncertainty, should be interpreted with caution, and are of little clinical value. Higher-quality evidence is required to determine robust prognostic factors for failure of TEA. Cite this article: Bone Joint Res 2024;13(5):201–213


Bone & Joint Open
Vol. 5, Issue 1 | Pages 9 - 19
16 Jan 2024
Dijkstra H van de Kuit A de Groot TM Canta O Groot OQ Oosterhoff JH Doornberg JN

Aims. Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool. Methods. A systematic search screening 3,252 studies identified 45 ML-based prediction models in orthopaedic trauma up to January 2023. The TRIPOD statement assessed transparent reporting and the PROBAST tool the risk of bias. Results. A total of 40 studies reported on training and internal validation; four studies performed both development and external validation, and one study performed only external validation. The most commonly reported outcomes were mortality (33%, 15/45) and length of hospital stay (9%, 4/45), and the majority of prediction models were developed in the hip fracture population (60%, 27/45). The overall median completeness for the TRIPOD statement was 62% (interquartile range 30 to 81%). The overall risk of bias in the PROBAST tool was low in 24% (11/45), high in 69% (31/45), and unclear in 7% (3/45) of the studies. High risk of bias was mainly due to analysis domain concerns including small datasets with low number of outcomes, complete-case analysis in case of missing data, and no reporting of performance measures. Conclusion. The results of this study showed that despite a myriad of potential clinically useful applications, a substantial part of ML studies in orthopaedic trauma lack transparent reporting, and are at high risk of bias. These problems must be resolved by following established guidelines to instil confidence in ML models among patients and clinicians. Otherwise, there will remain a sizeable gap between the development of ML prediction models and their clinical application in our day-to-day orthopaedic trauma practice. Cite this article: Bone Jt Open 2024;5(1):9–19


The Bone & Joint Journal
Vol. 105-B, Issue 11 | Pages 1140 - 1148
1 Nov 2023
Liukkonen R Vaajala M Mattila VM Reito A

Aims

The aim of this study was to report the pooled prevalence of post-traumatic osteoarthritis (PTOA) and examine whether the risk of developing PTOA after anterior cruciate ligament (ACL) injury has decreased in recent decades.

Methods

The PubMed and Web of Science databases were searched from 1 January 1980 to 11 May 2022. Patient series, observational studies, and clinical trials having reported the prevalence of radiologically confirmed PTOA after ACL injury, with at least a ten-year follow-up, were included. All studies were analyzed simultaneously, and separate analyses of the operative and nonoperative knees were performed. The prevalence of PTOA was calculated separately for each study, and pooled prevalence was reported with 95% confidence intervals (CIs) using either a fixed or random effects model. To examine the effect of the year of injury on the prevalence, a logit transformed meta-regression analysis was used with a maximum-likelihood estimator. Results from meta-regression analyses were reported with the unstandardized coefficient (β).


The Bone & Joint Journal
Vol. 105-B, Issue 1 | Pages 21 - 28
1 Jan 2023
Ndlovu S Naqshband M Masunda S Ndlovu K Chettiar K Anugraha A

Aims

Clinical management of open fractures is challenging and frequently requires complex reconstruction procedures. The Gustilo-Anderson classification lacks uniform interpretation, has poor interobserver reliability, and fails to account for injuries to musculotendinous units and bone. The Ganga Hospital Open Injury Severity Score (GHOISS) was designed to address these concerns. The major aim of this review was to ascertain the evidence available on accuracy of the GHOISS in predicting successful limb salvage in patients with mangled limbs.

Methods

We searched electronic data bases including PubMed, CENTRAL, EMBASE, CINAHL, Scopus, and Web of Science to identify studies that employed the GHOISS risk tool in managing complex limb injuries published from April 2006, when the score was introduced, until April 2021. Primary outcome was the measured sensitivity and specificity of the GHOISS risk tool for predicting amputation at a specified threshold score. Secondary outcomes included length of stay, need for plastic surgery, deep infection rate, time to fracture union, and functional outcome measures. Diagnostic test accuracy meta-analysis was performed using a random effects bivariate binomial model.


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

The aim of this study was to review the current evidence surrounding curve type and morphology on curve progression risk in adolescent idiopathic scoliosis (AIS).

Methods

A comprehensive search was conducted by two independent reviewers on PubMed, Embase, Medline, and Web of Science to obtain all published information on morphological predictors of AIS progression. Search items included ‘adolescent idiopathic scoliosis’, ‘progression’, and ‘imaging’. The inclusion and exclusion criteria were carefully defined. Risk of bias of studies was assessed with the Quality in Prognostic Studies tool, and level of evidence for each predictor was rated with the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. In all, 6,286 publications were identified with 3,598 being subjected to secondary scrutiny. Ultimately, 26 publications (25 datasets) were included in this review.


The Bone & Joint Journal
Vol. 103-B, Issue 6 | Pages 1021 - 1030
1 Jun 2021
Liu X Dai T Li B Li C Zheng Z Liu Y

Aims. The aim of this meta-analysis was to assess the prognosis after early functional rehabilitation or traditional immobilization in patients who underwent operative or nonoperative treatment for rupture of the Achilles tendon. Methods. PubMed, Embase, Web of Science, and Cochrane Library were searched for randomized controlled trials (RCTs) from their inception to 3 June 2020, using keywords related to rupture of the Achilles tendon and rehabilitation. Data extraction was undertaken by independent reviewers and subgroup analyses were performed based on the form of treatment. Risk ratios (RRs) and weighted mean differences (WMDs) (with 95% confidence intervals (CIs)) were used as summary association measures. Results. We included 19 trials with a total of 1,758 patients. There was no difference between the re-rupture rate (RR 0.84 (95% CI 0.56 to 1.28); p = 0.423), time to return to work (WMD -1.29 (95% CI -2.63 to 0.05); p = 0.060), and sporting activity (WMD -1.50 (95% CI -4.36 to 1.37); p = 0.306) between the early functional rehabilitation and the traditional immobilization treatment strategies. Early rehabilitation up to 12 weeks yielded significantly better Achilles tendon Total Rupture Scores ((ATRS) WMD 5.11 (95% CI 2.10 to 8.12); p < 0.001). Patients who underwent functional rehabilitation had significantly lower limb symmetry index of heel-rise work ((HRW) WMD -4.19 (95% CI -8.20 to 0.17); p = 0.041) at one year. Conclusion. Early functional rehabilitation is safe and provides better early function and the same functional outcome in the longer term. Cite this article: Bone Joint J 2021;103-B(6):1021–1030


Bone & Joint Research
Vol. 10, Issue 2 | Pages 122 - 133
1 Feb 2021
He CP Jiang XC Chen C Zhang HB Cao WD Wu Q Ma C

Osteoarthritis (OA), one of the most common motor system disorders, is a degenerative disease involving progressive joint destruction caused by a variety of factors. At present, OA has become the fourth most common cause of disability in the world. However, the pathogenesis of OA is complex and has not yet been clarified. Long non-coding RNA (lncRNA) refers to a group of RNAs more than 200 nucleotides in length with limited protein-coding potential, which have a wide range of biological functions including regulating transcriptional patterns and protein activity, as well as binding to form endogenous small interference RNAs (siRNAs) and natural microRNA (miRNA) molecular sponges. In recent years, a large number of lncRNAs have been found to be differentially expressed in a variety of pathological processes of OA, including extracellular matrix (ECM) degradation, synovial inflammation, chondrocyte apoptosis, and angiogenesis. Obviously, lncRNAs play important roles in regulating gene expression, maintaining the phenotype of cartilage and synovial cells, and the stability of the intra-articular environment. This article reviews the results of the latest research into the role of lncRNAs in a variety of pathological processes of OA, in order to provide a new direction for the study of OA pathogenesis and a new target for prevention and treatment.

Cite this article: Bone Joint Res 2021;10(2):122–133.


The Bone & Joint Journal
Vol. 102-B, Issue 7 | Pages 811 - 821
1 Jul 2020
You D Sepehri A Kooner S Krzyzaniak H Johal H Duffy P Schneider P Powell J

Aims

Dislocation is the most common indication for further surgery following total hip arthroplasty (THA) when undertaken in patients with a femoral neck fracture. This study aimed to assess the complication rates of THA with dual mobility components (THA-DMC) following a femoral neck fracture and to compare outcomes between THA-DMC, conventional THA, and hemiarthroplasty (HA).

Methods

We performed a systematic review of all English language articles on THA-DMC published between 2010 and 2019 in the MEDLINE, EMBASE, and Cochrane databases. After the application of rigorous inclusion and exclusion criteria, 23 studies dealing with patients who underwent treatment for a femoral neck fracture using THA-DMC were analyzed for the rate of dislocation. Secondary outcomes included reoperation, periprosthetic fracture, infection, mortality, and functional outcome. The review included 7,189 patients with a mean age of 77.8 years (66.4 to 87.6) and a mean follow-up of 30.9 months (9.0 to 68.0).


Bone & Joint Research
Vol. 9, Issue 3 | Pages 120 - 129
1 Mar 2020
Guofeng C Chen Y Rong W Ruiyu L Kunzheng W

Aims

Patients with metabolic syndrome (MetS) are known to be at increased risk of postoperative complications, but it is unclear whether MetS is also associated with complications after total hip arthroplasty (THA) or total knee arthroplasty (TKA). Here, we perform a systematic review and meta-analysis linking MetS to postoperative complications in THA and TKA.

Methods

The PubMed, OVID, and ScienceDirect databases were comprehensively searched and studies were selected and analyzed according to the guidelines of the Meta-analysis of Observational Studies in Epidemiology (MOOSE). We assessed the methodological quality of each study using the Newcastle-Ottawa Scale (NOS), and we evaluated the quality of evidence using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Data were extracted and meta-analyzed or qualitatively synthesized for several outcomes.


The Bone & Joint Journal
Vol. 101-B, Issue 1 | Pages 7 - 14
1 Jan 2019
Sorel JC Veltman ES Honig A Poolman RW

Aims

We performed a meta-analysis investigating the association between preoperative psychological distress and postoperative pain and function after total knee arthroplasty (TKA).

Materials and Methods

Pubmed/Medline, Embase, PsycINFO, and the Cochrane library were searched for studies on the influence of preoperative psychological distress on postoperative pain and physical function after TKA. Two blinded reviewers screened for eligibility and assessed the risk of bias and the quality of evidence. We used random effects models to pool data for the meta-analysis.