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The Bone & Joint Journal
Vol. 102-B, Issue 11 | Pages 1446 - 1456
1 Nov 2020
Halim UA Elbayouk A Ali AM Cullen CM Javed S

Aims. Gender bias and sexual discrimination (GBSD) have been widely recognized across a range of fields and are now part of the wider social consciousness. Such conduct can occur in the medical workplace, with detrimental effects on recipients. The aim of this review was to identify the prevalence and impact of GBSD in orthopaedic surgery, and to investigate interventions countering such behaviours. Methods. A systematic review was conducted by searching Medline, EMCARE, CINAHL, PsycINFO, and the Cochrane Library Database in April 2020, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to which we adhered. Original research papers pertaining to the prevalence and impact of GBSD, or mitigating strategies, within orthopaedics were included for review. Results. Of 570 papers, 27 were eligible for inclusion. These were published between 1998 and 2020. A narrative review was performed in light of the significant heterogeneity displayed by the eligible studies. A total of 13 papers discussed the prevalence of GBSD, while 13 related to the impact of these behaviours, and six discussed mitigating strategies. GBSD was found to be common in the orthopaedic workplace, with all sources showing women to be the subjects. The impact of this includes poor workforce representation, lower salaries, and less career success, including in academia, for women in orthopaedics. Mitigating strategies in the literature are focused on providing female role models, mentors, and educational interventions. Conclusion. GBSD is common in orthopaedic surgery, with a substantial impact on sufferers. A small number of mitigating strategies have been tested but these are limited in their scope. As such, the orthopaedic community is obliged to participate in more thoughtful and proactive strategies that mitigate against GBSD, by improving female recruitment and retention within the specialty. Cite this article: Bone Joint J 2020;102-B(11):1446–1456


Bone & Joint Research
Vol. 9, Issue 11 | Pages 808 - 820
1 Nov 2020
Trela-Larsen L Kroken G Bartz-Johannessen C Sayers A Aram P McCloskey E Kadirkamanathan V Blom AW Lie SA Furnes ON Wilkinson JM

Aims. To develop and validate patient-centred algorithms that estimate individual risk of death over the first year after elective joint arthroplasty surgery for osteoarthritis. Methods. A total of 763,213 hip and knee joint arthroplasty episodes recorded in the National Joint Registry for England and Wales (NJR) and 105,407 episodes from the Norwegian Arthroplasty Register were used to model individual mortality risk over the first year after surgery using flexible parametric survival regression. Results. The one-year mortality rates in the NJR were 10.8 and 8.9 per 1,000 patient-years after hip and knee arthroplasty, respectively. The Norwegian mortality rates were 9.1 and 6.0 per 1,000 patient-years, respectively. The strongest predictors of death in the final models were age, sex, body mass index, and American Society of Anesthesiologists grade. Exposure variables related to the intervention, with the exception of knee arthroplasty type, did not add discrimination over patient factors alone. Discrimination was good in both cohorts, with c-indices above 0.76 for the hip and above 0.70 for the knee. Time-dependent Brier scores indicated appropriate estimation of the mortality rate (≤ 0.01, all models). Conclusion. Simple demographic and clinical information may be used to calculate an individualized estimation for one-year mortality risk after hip or knee arthroplasty (. https://jointcalc.shef.ac.uk. ). These models may be used to provide patients with an estimate of the risk of mortality after joint arthroplasty. Cite this article: Bone Joint Res 2020;9(11):808–820


Bone & Joint Open
Vol. 4, Issue 3 | Pages 168 - 181
14 Mar 2023
Dijkstra H Oosterhoff JHF van de Kuit A IJpma FFA Schwab JH Poolman RW Sprague S Bzovsky S Bhandari M Swiontkowski M Schemitsch EH Doornberg JN Hendrickx LAM

Aims. To develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials. Methods. This study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration). Results. The developed algorithms distinguished between patients at high and low risk for 90-day and one-year mortality. The penalized logistic regression algorithm had the best performance metrics for both 90-day (c-statistic 0.80, calibration slope 0.95, calibration intercept -0.06, and Brier score 0.039) and one-year (c-statistic 0.76, calibration slope 0.86, calibration intercept -0.20, and Brier score 0.074) mortality prediction in the hold-out set. Conclusion. Using high-quality data, the ML-based prediction models accurately predicted 90-day and one-year mortality in patients aged 50 years or older with a FNF. The final models must be externally validated to assess generalizability to other populations, and prospectively evaluated in the process of shared decision-making. Cite this article: Bone Jt Open 2023;4(3):168–181


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. Results. Male sex, obesity, open wound, dislocations, late definitive surgical treatment, and lack of use of non-steroidal anti-inflammatory drugs were identified as adverse predictors and incorporated to construct the STEHOP model. It displayed good discrimination with a C-index of 0.80 (95% confidence interval 0.75 to 0.84). A high C-index value of 0.77 could still be reached in the internal validation. The calibration plot showed good agreement between nomogram prediction and observed outcomes. Conclusion. The newly developed STEHOP model is a valid and convenient instrument to predict HO formation after surgery for elbow trauma. It could assist clinicians in counselling patients regarding treatment expectations and therapeutic choices. Cite this article: Bone Joint J 2022;104-B(8):963–971


The Bone & Joint Journal
Vol. 104-B, Issue 4 | Pages 486 - 494
4 Apr 2022
Liu W Sun Z Xiong H Liu J Lu J Cai B Wang W Fan C

Aims. The aim of this study was to develop and internally validate a prognostic nomogram to predict the probability of gaining a functional range of motion (ROM ≥ 120°) after open arthrolysis of the elbow in patients with post-traumatic stiffness of the elbow. Methods. We developed the Shanghai Prediction Model for Elbow Stiffness Surgical Outcome (SPESSO) based on a dataset of 551 patients who underwent open arthrolysis of the elbow in four institutions. Demographic and clinical characteristics were collected from medical records. The least absolute shrinkage and selection operator regression model was used to optimize the selection of relevant features. Multivariable logistic regression analysis was used to build the SPESSO. Its prediction performance was evaluated using the concordance index (C-index) and a calibration graph. Internal validation was conducted using bootstrapping validation. Results. BMI, the duration of stiffness, the preoperative ROM, the preoperative intensity of pain, and grade of post-traumatic osteoarthritis of the elbow were identified as predictors of outcome and incorporated to construct the nomogram. SPESSO displayed good discrimination with a C-index of 0.73 (95% confidence interval 0.64 to 0.81). A high C-index value of 0.70 could still be reached in the interval validation. The calibration graph showed good agreement between the nomogram prediction and the outcome. Conclusion. The newly developed SPESSO is a valid and convenient model which can be used to predict the outcome of open arthrolysis of the elbow. It could assist clinicians in counselling patients regarding the choice and expectations of treatment. Cite this article: Bone Joint J 2022;104-B(4):486–494


The Bone & Joint Journal
Vol. 103-B, Issue 11 | Pages 1725 - 1730
1 Nov 2021
Baumber R Gerrand C Cooper M Aston W

Aims. The incidence of bone metastases is between 20% to 75% depending on the type of cancer. As treatment improves, the number of patients who need surgical intervention is increasing. Identifying patients with a shorter life expectancy would allow surgical intervention with more durable reconstructions to be targeted to those most likely to benefit. While previous scoring systems have focused on surgical and oncological factors, there is a need to consider comorbidities and the physiological state of the patient, as these will also affect outcome. The primary aim of this study was to create a scoring system to estimate survival time in patients with bony metastases and to determine which factors may adversely affect this. Methods. This was a retrospective study which included all patients who had presented for surgery with metastatic bone disease. The data collected included patient, surgical, and oncological variables. Univariable and multivariable analysis identified which factors were associated with a survival time of less than six months and less than one year. A model to predict survival based on these factors was developed using Cox regression. Results. A total of 164 patients were included with a median survival time of 1.6 years (interquartile range 0.5 to 3.1) after surgery. On multivariable analysis, a higher American Society of Anesthesiologists grade (p < 0.001), a high white cell count (p = 0.002), hyponatraemia (p = 0.001), a preoperative resting heart rate of > 100 bpm (p = 0.052), and the type of primary cancer (p = 0.026) remained significant predictors of reduced survival time. The predictive model developed showed good discrimination and calibration to predict both six- and 12-month survival in patients with metastatic bone disease. Conclusion. In addition to surgical and oncological factors, the level of comorbidity and physiological state of the patient has a significant impact on survival in patients with metastatic bone disease. These factors should be considered when assessing the appropriateness of surgical intervention. This is the first study to examine other patient factors alongside surgical and oncological data to identify a relationship between these and survival. Cite this article: Bone Joint J 2021;103-B(11):1725–1730


The Bone & Joint Journal
Vol. 104-B, Issue 6 | Pages 687 - 695
1 Jun 2022
Sabah SA Knight R Alvand A Beard DJ Price AJ

Aims. Routinely collected patient-reported outcome measures (PROMs) have been useful to quantify and quality-assess provision of total hip arthroplasty (THA) and total knee arthroplasty (TKA) in the UK for the past decade. This study aimed to explore whether the outcome following primary THA and TKA had improved over the past seven years. Methods. Secondary data analysis of 277,430 primary THAs and 308,007 primary TKAs from the NHS PROMs programme was undertaken. Outcome measures were: postoperative Oxford Hip/Knee Score (OHS/OKS); proportion of patients achieving a clinically important improvement in joint function (responders); quality of life; patient satisfaction; perceived success; and complication rates. Outcome measures were compared based on year of surgery using multiple linear and logistic regression models. Results. For primary THA, multiple linear regression modelling found that more recent year of surgery was associated with higher postoperative OHS (unstandardized coefficient (B) 0.15 points (95% confidence interval (CI) 0.14 to 0.17); p < 0.001) and higher EuroQol five-dimension index (EQ-5D) utility (B 0.002 (95% CI 0.001 to 0.002); p < 0.001). The odds of being a responder (odds ratio (OR) 1.02 (95% CI 1.02 to 1.03); p < 0.001) and patient satisfaction (OR 1.02 (95% CI 1.01 to 1.03); p < 0.001) increased with year of surgery, while the odds of any complication reduced (OR 0.97 (95% CI 0.97 to 0.98); p < 0.001). No trend was found for perceived success (p = 0.555). For primary TKA, multiple linear regression modelling found that more recent year of surgery was associated with higher postoperative OKS (B 0.21 points (95% CI 0.19 to 0.22); p < 0.001) and higher EQ-5D utility (B 0.002 (95% CI 0.002 to 0.003); p < 0.001). The odds of being a responder (OR 1.04 (95% CI 1.03 to 1.04); p < 0.001), perceived success (OR 1.02 (95% CI 1.01 to 1.02); p < 0.001), and patient satisfaction (OR 1.02 (95% CI 1.01 to 1.02); p < 0.001) all increased with year of surgery, while the odds of any complication reduced (OR 0.97 (95% CI 0.97 to 0.97); p < 0.001). Conclusion. Nearly all patient-reported outcomes following primary THA/TKA improved by a small amount over the past seven years. Due to the high proportion of patients achieving good outcomes, PROMs following THA and TKA may need to focus on better discrimination of patients achieving high scores to be able to continue to measure improvement in outcomes. Cite this article: Bone Joint J 2022;104-B(6):687–695


The Bone & Joint Journal
Vol. 103-B, Issue 9 | Pages 1472 - 1478
1 Sep 2021
Shoji T Saka H Inoue T Kato Y Fujiwara Y Yamasaki T Yasunaga Y Adachi N

Aims. Rotational acetabular osteotomy (RAO) has been reported to be effective in improving symptoms and preventing osteoarthritis (OA) progression in patients with mild to severe develomental dysplasia of the hip (DDH). However, some patients develop secondary OA even when the preoperative joint space is normal; determining who will progress to OA is difficult. We evaluated whether the preoperative cartilage condition may predict OA progression following surgery using T2 mapping MRI. Methods. We reviewed 61 hips with early-stage OA in 61 patients who underwent RAO for DDH. They underwent preoperative and five-year postoperative radiological analysis of the hip. Those with a joint space narrowing of more than 1 mm were considered to have 'OA progression'. Preoperative assessment of articular cartilage was also performed using 3T MRI with the T2 mapping technique. The region of interest was defined as the weightbearing portion of the acetabulum and femoral head. Results. There were 16 patients with postoperative OA progression. The T2 values of the centre to the anterolateral region of the acetabulum and femoral head in the OA progression cases were significantly higher than those in patients without OA progression. The preoperative T2 values in those regions were positively correlated with the narrowed joint space width. The receiver operating characteristic analysis revealed that the T2 value of the central portion in the acetabulum provided excellent discrimination, with OA progression patients having an area under the curve of 0.858. Furthermore, logistic regression analysis showed T2 values of the centre to the acetabulum’s anterolateral portion as independent predictors of subsequent OA progression (p < 0.001). Conclusion. This was the first study to evaluate the relationship between intra-articular degeneration using T2 mapping MRI and postoperative OA progression. Our findings suggest that preoperative T2 values of the hip can be better prognostic factors for OA progression than radiological measures following RAO. Cite this article: Bone Joint J 2021;103-B(9):1472–1478


The Bone & Joint Journal
Vol. 103-B, Issue 3 | Pages 469 - 478
1 Mar 2021
Garland A Bülow E Lenguerrand E Blom A Wilkinson M Sayers A Rolfson O Hailer NP

Aims. To develop and externally validate a parsimonious statistical prediction model of 90-day mortality after elective total hip arthroplasty (THA), and to provide a web calculator for clinical usage. Methods. We included 53,099 patients with cemented THA due to osteoarthritis from the Swedish Hip Arthroplasty Registry for model derivation and internal validation, as well as 125,428 patients from England and Wales recorded in the National Joint Register for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey (NJR) for external model validation. A model was developed using a bootstrap ranking procedure with a least absolute shrinkage and selection operator (LASSO) logistic regression model combined with piecewise linear regression. Discriminative ability was evaluated by the area under the receiver operating characteristic curve (AUC). Calibration belt plots were used to assess model calibration. Results. A main effects model combining age, sex, American Society for Anesthesiologists (ASA) class, the presence of cancer, diseases of the central nervous system, kidney disease, and diagnosed obesity had good discrimination, both internally (AUC = 0.78, 95% confidence interval (CI) 0.75 to 0.81) and externally (AUC = 0.75, 95% CI 0.73 to 0.76). This model was superior to traditional models based on the Charlson (AUC = 0.66, 95% CI 0.62 to 0.70) and Elixhauser (AUC = 0.64, 95% CI 0.59 to 0.68) comorbidity indices. The model was well calibrated for predicted probabilities up to 5%. Conclusion. We developed a parsimonious model that may facilitate individualized risk assessment prior to one of the most common surgical interventions. We have published a web calculator to aid clinical decision-making. Cite this article: Bone Joint J 2021;103-B(3):469–478


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. Results. In the development cohort, the CISSD at ten years was 32.9% (95% confidence interval (CI) 19.8% to 38.4%). Age at diagnosis, grade, and surgical margin were found to have significant effects on CISSD and CIDP in multivariate analyses. Maximum tumour diameter was also significantly associated with CISSD. In the development cohort, the c-indices for CISSD and CIDP at five years were 0.743 (95% CI 0.700 to 0.819) and 0.761 (95% CI 0.713 to 0.800), respectively. When applied to the validation cohort, the c-indices for CISSD and CIDP at five years were 0.839 (95% CI 0.763 to 0.916) and 0.749 (95% CI 0.672 to 0.825), respectively. The calibration plots for these two nomograms demonstrated good fit. Conclusion. Our nomograms performed well on internal and external validation and can be used to predict CISSD and CIDP after resection of localized high-grade conventional primary central and dedifferentiated chondrosarcomas. They provide a new tool with which clinicians can assess and advise individual patients about their prognosis. Cite this article: Bone Joint J 2020;102-B(12):1752–1759


The Journal of Bone & Joint Surgery British Volume
Vol. 88-B, Issue 8 | Pages 1048 - 1052
1 Aug 2006
Jerosch-Herold C Rosén B Shepstone L

Locognosia, the ability to localise touch, is one aspect of tactile spatial discrimination which relies on the integrity of peripheral end-organs as well as the somatosensory representation of the surface of the body in the brain. The test presented here is a standardised assessment which uses a protocol for testing locognosia in the zones of the hand supplied by the median and/or ulnar nerves. The test-retest reliability and discriminant validity were investigated in 39 patients with injuries to the median or ulnar nerve. Intraclass correlation coefficients were used to calculate the test-retest reliability. Discriminant validity was assessed by comparing the injured with the unaffected hand. Excellent test-retest reliability was demonstrated for the injuries to the median (intraclass correlation coefficient 0.924, 95% confidence interval 0.848 to 1.00) and the ulnar nerves (intraclass correlation coefficient 0.859, 95% confidence interval 0.693 to 1.00). The magnitude of the difference in scores between affected and unaffected hands showed good discriminant validity. For injuries to the median nerve the mean difference was 11.1 points (1 to 33; . sd. 7.4), which was statistically significant (p < 0.0001, paired t-test) and for those of the ulnar nerve it was 4.75 points (1 to 13.5; . sd. 3.16), which was also statistically significant (paired t-test, p < 0.0001). The locognosia test has excellent test-retest reliability, is a valid test of tactile spatial discrimination and should be included in the evaluation of outcome after injury to peripheral nerves


The Bone & Joint Journal
Vol. 102-B, Issue 4 | Pages 463 - 469
1 Apr 2020
Qin L Hu N Li X Chen Y Wang J Huang W

Aims. Prosthetic joint infection (PJI) remains a major clinical challenge. Neutrophil CD64 index, Fc-gamma receptor 1 (FcγR1), plays an important role in mediating inflammation of bacterial infections and therefore could be a valuable biomarker for PJI. The aim of this study is to compare the neutrophil CD64 index in synovial and blood diagnostic ability with the standard clinical tests for discrimination PJI and aseptic implant failure. Methods. A total of 50 patients undergoing revision hip and knee arthroplasty were enrolled into a prospective study. According to Musculoskeletal Infection Society (MSIS) criteria, 25 patients were classified as infected and 25 as not infected. In all patients, neutrophil CD64 index and percentage of polymorphonuclear neutrophils (PMN%) in synovial fluid, serum CRP, ESR, and serum CD64 index levels were measured preoperatively. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were analyzed for each biomarker. Results. Serum CD64 index showed no significant difference between the two groups (p = 0.091). Synovial fluid CD64 index and PMN% discriminated good differentiation between groups of PJI and aseptic failure with AUC of 0.946 (95% confidence interval (CI) 0.842 to 0.990) and 0.938 (95% CI 0.832 to 0.987) separately. The optimal threshold value of synovial CD64 index for the diagnosis of PJI was 0.85, with a sensitivity of 92.00%, a specificity of 96.00%, and diagnostic odds ratio (DOR) of 227.11. Conclusion. The present study demonstrates that CD64 index in synovial fluid could be a promising laboratory marker for screening PJI. The cut-off values of 0.85 for synovial CD64 index has the potential to distinguish aseptic failure from PJI. Cite this article: Bone Joint J 2020;102-B(4):463–469


Bone & Joint Research
Vol. 7, Issue 1 | Pages 12 - 19
1 Jan 2018
Janz V Schoon J Morgenstern C Preininger B Reinke S Duda G Breitbach A Perka CF Geissler S

Objectives. The objective of this study was to develop a test for the rapid (within 25 minutes) intraoperative detection of bacteria from synovial fluid to diagnose periprosthetic joint infection (PJI). Methods. The 16s rDNA test combines a polymerase chain reaction (PCR) for amplification of 16s rDNA with a lateral flow immunoassay in one fully automated system. The synovial fluid of 77 patients undergoing joint aspiration or primary or revision total hip or knee surgery was prospectively collected. The cohort was divided into a proof-of-principle cohort (n = 17) and a validation cohort (n = 60). Using the proof-of-principle cohort, an optimal cut-off for the discrimination between PJI and non-PJI samples was determined. PJI was defined as detection of the same bacterial species in a minimum of two microbiological samples, positive histology, and presence of a sinus tract or intra-articular pus. Results. The 16s rDNA test proved to be very robust and was able to provide a result in 97% of all samples within 25 minutes. The 16s rDNA test was able to diagnose PJI with a sensitivity of 87.5% and 82%, and a specificity of 100% and 89%, in the proof-of-principle and validation cohorts, respectively. The microbiological culture of synovial fluid achieved a sensitivity of 80% and a specificity of 93% in the validation cohort. Conclusion. The 16s rDNA test offers reliable intraoperative detection of all bacterial species within 25 minutes with a sensitivity and specificity comparable with those of conventional microbiological culture of synovial fluid for the detection of PJI. The 16s rDNA test performance is independent of possible blood contamination, culture time and bacterial species. Cite this article: V. Janz, J. Schoon, C. Morgenstern, B. Preininger, S. Reinke, G. Duda, A. Breitbach, C. F. Perka, S. Geissler. Rapid detection of periprosthetic joint infection using a combination of 16s rDNA polymerase chain reaction and lateral flow immunoassay: A Pilot Study. Bone Joint Res 2018;7:12–19. DOI: 10.1302/2046-3758.71.BJR-2017-0103.R2


Bone & Joint Research
Vol. 3, Issue 8 | Pages 241 - 245
1 Aug 2014
Kanamoto T Shiozaki Y Tanaka Y Yonetani Y Horibe S

Objectives. To evaluate the applicability of MRI for the quantitative assessment of anterior talofibular ligaments (ATFLs) in symptomatic chronic ankle instability (CAI). Methods. Between 1997 and 2010, 39 patients with symptomatic CAI underwent surgical treatment (22 male, 17 female, mean age 25.4 years (15 to 40)). In all patients, the maximum diameters of the ATFLs were measured on pre-operative T2-weighted MR images in planes parallel to the path of the ATFL. They were classified into three groups based on a previously published method with modifications: ‘normal’, diameter = 1.0 - 3.2 mm; ‘thickened’, diameter > 3.2 mm; ‘thin or absent’, diameter < 1.0 mm. Stress radiography was performed with the maximum manual force in inversion under general anaesthesia immediately prior to surgery. In surgery, ATFLs were macroscopically divided into two categories: ‘thickened’, an obvious thickened ligament and ‘thin or absent’. The imaging results were compared with the macroscopic results that are considered to be of a gold standard. Results. Agreement was reached when comparison was made between groups, based on MRI and macroscopic findings. ATFLs were abnormal in all 39 cases and classified as ten ‘thickened’ and 29 ‘thin or absent’. As to talar tilt stress radiography, a clear cut-off angle, which would allow discrimination between ‘thickened’ and ‘thin or absent’ patients, was not identified. Conclusion. MRI is valuable as a pre-operative assessment tool that can provide the quantitative information of ATFLs in patients with CAI. Cite this article Bone Joint Res 2014;3:241–5


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.


The Bone & Joint Journal
Vol. 105-B, Issue 6 | Pages 702 - 710
1 Jun 2023
Yeramosu T Ahmad W Bashir A Wait J Bassett J Domson G

Aims

The aim of this study was to identify factors associated with five-year cancer-related mortality in patients with limb and trunk soft-tissue sarcoma (STS) and develop and validate machine learning algorithms in order to predict five-year cancer-related mortality in these patients.

Methods

Demographic, clinicopathological, and treatment variables of limb and trunk STS patients in the Surveillance, Epidemiology, and End Results Program (SEER) database from 2004 to 2017 were analyzed. Multivariable logistic regression was used to determine factors significantly associated with five-year cancer-related mortality. Various machine learning models were developed and compared using area under the curve (AUC), calibration, and decision curve analysis. The model that performed best on the SEER testing data was further assessed to determine the variables most important in its predictive capacity. This model was externally validated using our institutional dataset.


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.


Bone & Joint 360
Vol. 13, Issue 1 | Pages 22 - 26
1 Feb 2024

The February 2024 Wrist & Hand Roundup360 looks at: Occupational therapy for thumb carpometacarpal osteoarthritis?; Age and patient-reported benefits from operative management of intra-articular distal radius fractures: a meta-regression analysis; Long-term outcomes of nonsurgical treatment of thumb carpometacarpal osteoarthritis: a cohort study; Semi-occlusive dressing versus surgery in fingertip injuries: a randomized controlled trial; Re-fracture in partial union of the scaphoid waist?; The WALANT distal radius fracture: a systematic review; Endoscopic carpal tunnel release with or without hand therapy?; Ten-year trends in the level of evidence in hand surgery.


Bone & Joint Research
Vol. 13, Issue 8 | Pages 392 - 400
5 Aug 2024
Barakat A Evans J Gibbons C Singh HP

Aims

The Oxford Shoulder Score (OSS) is a 12-item measure commonly used for the assessment of shoulder surgeries. This study explores whether computerized adaptive testing (CAT) provides a shortened, individually tailored questionnaire while maintaining test accuracy.

Methods

A total of 16,238 preoperative OSS were available in the National Joint Registry (NJR) for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey dataset (April 2012 to April 2022). Prior to CAT, the foundational item response theory (IRT) assumptions of unidimensionality, monotonicity, and local independence were established. CAT compared sequential item selection with stopping criteria set at standard error (SE) < 0.32 and SE < 0.45 (equivalent to reliability coefficients of 0.90 and 0.80) to full-length patient-reported outcome measure (PROM) precision.


Bone & Joint Research
Vol. 6, Issue 9 | Pages 550 - 556
1 Sep 2017
Tsang C Boulton C Burgon V Johansen A Wakeman R Cromwell DA

Objectives. The National Hip Fracture Database (NHFD) publishes hospital-level risk-adjusted mortality rates following hip fracture surgery in England, Wales and Northern Ireland. The performance of the risk model used by the NHFD was compared with the widely-used Nottingham Hip Fracture Score. Methods. Data from 94 hospitals on patients aged 60 to 110 who had hip fracture surgery between May 2013 and July 2013 were analysed. Data were linked to the Office for National Statistics (ONS) death register to calculate the 30-day mortality rate. Risk of death was predicted for each patient using the NHFD and Nottingham models in a development dataset using logistic regression to define the models’ coefficients. This was followed by testing the performance of these refined models in a second validation dataset. Results. The 30-day mortality rate was 5.36% in the validation dataset (n = 3861), slightly lower than the 6.40% in the development dataset (n = 4044). The NHFD and Nottingham models showed a slightly lower discrimination in the validation dataset compared with the development dataset, but both still displayed moderate discriminative power (c-statistic for NHFD = 0.71, 95% confidence interval (CI) 0.67 to 0.74; Nottingham model = 0.70, 95% CI 0.68 to 0.75). Both models defined similar ranges of predicted mortality risk (1% to 18%) in assessment of calibration. Conclusions. Both models have limitations in predicting mortality for individual patients after hip fracture surgery, but the NHFD risk adjustment model performed as well as the widely-used Nottingham prognostic tool and is therefore a reasonable alternative for risk adjustment in the United Kingdom hip fracture population. Cite this article: Bone Joint Res 2017;6:550–556