Advertisement for orthosearch.org.uk
Results 1 - 20 of 56
Results per page:
Bone & Joint Research
Vol. 13, Issue 8 | Pages 372 - 382
1 Aug 2024
Luger M Böhler C Puchner SE Apprich S Staats K Windhager R Sigmund IK

Aims. Serum inflammatory parameters are widely used to aid in diagnosing a periprosthetic joint infection (PJI). Due to their limited performances in the literature, novel and more accurate biomarkers are needed. Serum albumin-to-globulin ratio (AGR) and serum CRP-to-albumin ratio (CAR) have previously been proposed as potential new parameters, but results were mixed. The aim of this study was to assess the diagnostic accuracy of AGR and CAR in diagnosing PJI and to compare them to the established and widely used marker CRP. Methods. From 2015 to 2022, a consecutive series of 275 cases of revision total hip (n = 129) and knee arthroplasty (n = 146) were included in this retrospective cohort study. Based on the 2021 European Bone and Joint Infection Society (EBJIS) definition, 144 arthroplasties were classified as septic. Using receiver operating characteristic curve (ROC) analysis, the ideal thresholds and diagnostic performances were calculated. The areas under the curve (AUCs) were compared using the z-test. Results. AGR, CAR, and CRP were associated with PJI (p < 0.001). Sensitivities were 62.5% (95% CI 54.3 to 70.0), 73.6% (95% CI 65.8 to 80.1), and 71.5% (95% CI 63.6 to 78.3), respectively. Specificities were calculated with 84.7% (95% CI 77.5 to 89.9), 86.3% (95% CI 79.2 to 91.2), and 87.8% (95% CI 80.9 to 92.4), respectively. The AUC of CRP (0.797 (95% CI 0.750 to 0.843)) was significantly higher than the AUC of AGR (0.736 (95% CI 0.686 to 0.786), p < 0.001), and similar to AUC of CAR (0.799 (95% CI 0.753 to 0.846), p = 0.832). Decreased sensitivities were observed in PJIs caused by low-virulence organisms (AGR: 60%, CAR: 78%) compared to high-virulence pathogens (AGR: 80%, p = 0.042; CAR: 88%, p = 0.158). Higher sensitivities were seen in acute haematogenous (AGR: 83%, CAR: 96%) compared to chronic PJIs (AGR: 54%, p = 0.001; CAR: 65%, p < 0.001). Conclusion. Serum AGR and CAR showed limited diagnostic accuracy (especially in low-grade and chronic infections) and did not outperform the established marker CRP in our study. Hence, neither parameter can be recommended as an additional tool for diagnosing PJI. Cite this article: Bone Joint Res 2024;13(8):372–382


Bone & Joint 360
Vol. 13, Issue 3 | Pages 28 - 31
3 Jun 2024

The June 2024 Wrist & Hand Roundup. 360. looks at: One-year outcomes of the anatomical front and back reconstruction for scapholunate dissociation; Limited intercarpal fusion versus proximal row carpectomy in the treatment of SLAC or SNAC wrist: results after 3.5 years; Prognostic factors for clinical outcomes after arthroscopic treatment of traumatic central tears of the triangular fibrocartilage complex; The rate of nonunion in the MRI-detected occult scaphoid fracture: a multicentre cohort study; Does correction of carpal malalignment influence the union rate of scaphoid nonunion surgery?; Provision of a home-based video-assisted therapy programme in thumb carpometacarpal arthroplasty; Is replantation associated with better hand function after traumatic hand amputation than after revision amputation?; Diagnostic performance of artificial intelligence for detection of scaphoid and distal radius fractures: a systematic review


The Bone & Joint Journal
Vol. 106-B, Issue 4 | Pages 372 - 379
1 Apr 2024
Straub J Staats K Vertesich K Kowalscheck L Windhager R Böhler C

Aims

Histology is widely used for diagnosis of persistent infection during reimplantation in two-stage revision hip and knee arthroplasty, although data on its utility remain scarce. Therefore, this study aims to assess the predictive value of permanent sections at reimplantation in relation to reinfection risk, and to compare results of permanent and frozen sections.

Methods

We retrospectively collected data from 226 patients (90 hips, 136 knees) with periprosthetic joint infection who underwent two-stage revision between August 2011 and September 2021, with a minimum follow-up of one year. Histology was assessed via the SLIM classification. First, we analyzed whether patients with positive permanent sections at reimplantation had higher reinfection rates than patients with negative histology. Further, we compared permanent and frozen section results, and assessed the influence of anatomical regions (knee versus hip), low- versus high-grade infections, as well as first revision versus multiple prior revisions on the histological result at reimplantation. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), chi-squared tests, and Kaplan-Meier estimates were calculated.


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 360
Vol. 12, Issue 5 | Pages 34 - 36
1 Oct 2023

The October 2023 Spine Roundup360 looks at: Cutting through surgical smoke: the science of cleaner air in spinal operations; Unlocking success: key factors in thoracic spine decompression and fusion for ossification of the posterior longitudinal ligament; Deep learning algorithm for identifying cervical cord compression due to degenerative canal stenosis on radiography; Surgeon experience influences robotics learning curve for minimally invasive lumbar fusion; Decision-making algorithm for the surgical treatment of degenerative lumbar spondylolisthesis of L4/L5; Response to preoperative steroid injections predicts surgical outcomes in patients undergoing fusion for isthmic spondylolisthesis.


The Bone & Joint Journal
Vol. 105-B, Issue 4 | Pages 431 - 438
15 Mar 2023
Vendeuvre T Tabard-Fougère A Armand S Dayer R

Aims

This study aimed to evaluate rasterstereography of the spine as a diagnostic test for adolescent idiopathic soliosis (AIS), and to compare its results with those obtained using a scoliometer.

Methods

Adolescents suspected of AIS and scheduled for radiographs were included. Rasterstereographic scoliosis angle (SA), maximal vertebral surface rotation (ROT), and angle of trunk rotation (ATR) with a scoliometer were evaluated. The area under the curve (AUC) from receiver operating characteristic (ROC) plots were used to describe the discriminative ability of the SA, ROT, and ATR for scoliosis, defined as a Cobb angle > 10°. Test characteristics (sensitivity and specificity) were reported for the best threshold identified using the Youden method. AUC of SA, ATR, and ROT were compared using the bootstrap test for two correlated ROC curves method.


The Bone & Joint Journal
Vol. 105-B, Issue 4 | Pages 373 - 381
15 Mar 2023
Jandl NM Kleiss S Mussawy H Beil FT Hubert J Rolvien T

Aims

The aim of this study was to evaluate the diagnostic accuracy of the absolute synovial polymorphonuclear neutrophil cell (PMN) count for the diagnosis or exclusion of periprosthetic joint infection (PJI) after total hip (THA) or knee arthroplasty (TKA).

Methods

In this retrospective cohort study, 147 consecutive patients with acute or chronic complaints following THA and TKA were included. Diagnosis of PJI was established based on the 2018 International Consensus Meeting criteria. A total of 39 patients diagnosed with PJI (32 chronic and seven acute) and 108 patients with aseptic complications were surgically revised.


The Bone & Joint Journal
Vol. 105-B, Issue 1 | Pages 56 - 63
1 Jan 2023
de Klerk HH Oosterhoff JHF Schoolmeesters B Nieboer P Eygendaal D Jaarsma RL IJpma FFA van den Bekerom MPJ Doornberg JN

Aims

This study aimed to answer the following questions: do 3D-printed models lead to a more accurate recognition of the pattern of complex fractures of the elbow?; do 3D-printed models lead to a more reliable recognition of the pattern of these injuries?; and do junior surgeons benefit more from 3D-printed models than senior surgeons?

Methods

A total of 15 orthopaedic trauma surgeons (seven juniors, eight seniors) evaluated 20 complex elbow fractures for their overall pattern (i.e. varus posterior medial rotational injury, terrible triad injury, radial head fracture with posterolateral dislocation, anterior (trans-)olecranon fracture-dislocation, posterior (trans-)olecranon fracture-dislocation) and their specific characteristics. First, fractures were assessed based on radiographs and 2D and 3D CT scans; and in a subsequent round, one month later, with additional 3D-printed models. Diagnostic accuracy (acc) and inter-surgeon reliability (κ) were determined for each assessment.


Bone & Joint Research
Vol. 11, Issue 9 | Pages 608 - 618
7 Sep 2022
Sigmund IK Luger M Windhager R McNally MA

Aims

This study evaluated the definitions developed by the European Bone and Joint Infection Society (EBJIS) 2021, the International Consensus Meeting (ICM) 2018, and the Infectious Diseases Society of America (IDSA) 2013, for the diagnosis of periprosthetic joint infection (PJI).

Methods

In this single-centre, retrospective analysis of prospectively collected data, patients with an indicated revision surgery after a total hip or knee arthroplasty were included between 2015 and 2020. A standardized diagnostic workup was performed, identifying the components of the EBJIS, ICM, and IDSA criteria in each patient.


Bone & Joint Research
Vol. 11, Issue 6 | Pages 398 - 408
22 Jun 2022
Xu T Zeng Y Yang X Liu G Lv T Yang H Jiang F Chen Y

Aims

We aimed to evaluate the utility of 68Ga-citrate positron emission tomography (PET)/CT in the differentiation of periprosthetic joint infection (PJI) and aseptic loosening (AL), and compare it with 99mTc-methylene bisphosphonates (99mTc-MDP) bone scan.

Methods

We studied 39 patients with suspected PJI or AL. These patients underwent 68Ga-citrate PET/CT, 99mTc-MDP three-phase bone scan and single-photon emission CT (SPECT)/CT. PET/CT was performed at ten minutes and 60 minutes after injection, respectively. Images were evaluated by three nuclear medicine doctors based on: 1) visual analysis of the three methods based on tracer uptake model, and PET images attenuation-corrected with CT and those not attenuation-corrected with CT were analyzed, respectively; and 2) semi-quantitative analysis of PET/CT: maximum standardized uptake value (SUVmax) of lesions, SUVmax of the lesion/SUVmean of the normal bone, and SUVmax of the lesion/SUVmean of the normal muscle. The final diagnosis was based on the clinical and intraoperative findings, and histopathological and microbiological examinations.


Bone & Joint Open
Vol. 3, Issue 1 | Pages 93 - 97
10 Jan 2022
Kunze KN Orr M Krebs V Bhandari M Piuzzi NS

Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.


The Bone & Joint Journal
Vol. 104-B, Issue 1 | Pages 97 - 102
1 Jan 2022
Hijikata Y Kamitani T Nakahara M Kumamoto S Sakai T Itaya T Yamazaki H Ogawa Y Kusumegi A Inoue T Yoshida T Furue N Fukuhara S Yamamoto Y

Aims. To develop and internally validate a preoperative clinical prediction model for acute adjacent vertebral fracture (AVF) after vertebral augmentation to support preoperative decision-making, named the after vertebral augmentation (AVA) score. Methods. In this prognostic study, a multicentre, retrospective single-level vertebral augmentation cohort of 377 patients from six Japanese hospitals was used to derive an AVF prediction model. Backward stepwise selection (p < 0.05) was used to select preoperative clinical and imaging predictors for acute AVF after vertebral augmentation for up to one month, from 14 predictors. We assigned a score to each selected variable based on the regression coefficient and developed the AVA scoring system. We evaluated sensitivity and specificity for each cut-off, area under the curve (AUC), and calibration as diagnostic performance. Internal validation was conducted using bootstrapping to correct the optimism. Results. Of the 377 patients used for model derivation, 58 (15%) had an acute AVF postoperatively. The following preoperative measures on multivariable analysis were summarized in the five-point AVA score: intravertebral instability (≥ 5 mm), focal kyphosis (≥ 10°), duration of symptoms (≥ 30 days), intravertebral cleft, and previous history of vertebral fracture. Internal validation showed a mean optimism of 0.019 with a corrected AUC of 0.77. A cut-off of ≤ one point was chosen to classify a low risk of AVF, for which only four of 137 patients (3%) had AVF with 92.5% sensitivity and 45.6% specificity. A cut-off of ≥ four points was chosen to classify a high risk of AVF, for which 22 of 38 (58%) had AVF with 41.5% sensitivity and 94.5% specificity. Conclusion. In this study, the AVA score was found to be a simple preoperative method for the identification of patients at low and high risk of postoperative acute AVF. This model could be applied to individual patients and could aid in the decision-making before vertebral augmentation. Cite this article: Bone Joint J 2022;104-B(1):97–102


The Bone & Joint Journal
Vol. 104-B, Issue 1 | Pages 120 - 126
1 Jan 2022
Kafle G Garg B Mehta N Sharma R Singh U Kandasamy D Das P Chowdhury B

Aims

The aims of this study were to determine the diagnostic yield of image-guided biopsy in providing a final diagnosis in patients with suspected infectious spondylodiscitis, to report the diagnostic accuracy of various microbiological tests and histological examinations in these patients, and to report the epidemiology of infectious spondylodiscitis from a country where tuberculosis (TB) is endemic, including the incidence of drug-resistant TB.

Methods

A total of 284 patients with clinically and radiologically suspected infectious spondylodiscitis were prospectively recruited into the study. Image-guided biopsy of the vertebral lesion was performed and specimens were sent for various microbiological tests and histological examinations. The final diagnosis was determined using a composite reference standard based on clinical, radiological, serological, microbiological, and histological findings. The overall diagnostic yield of the biopsy, and that for each test, was calculated in light of the final diagnosis.


The Bone & Joint Journal
Vol. 104-B, Issue 1 | Pages 53 - 58
1 Jan 2022
Tai DBG Wengenack NL Patel R Berbari EF Abdel MP Tande AJ

Aims

Fungal and mycobacterial periprosthetic joint infections (PJI) are rare events. Clinicians are wary of missing these diagnoses, often leading to the routine ordering of fungal and mycobacterial cultures on periprosthetic specimens. Our goal was to examine the utility of these cultures and explore a modern bacterial culture technique using bacterial blood culture bottles (BCBs) as an alternative.

Methods

We performed a retrospective review of patients diagnosed with hip or knee PJI between 1 January 2010 and 31 December 2019, at the Mayo Clinic in Rochester, Minnesota, USA. We included patients aged 18 years or older who had fungal, mycobacterial, or both cultures performed together with bacterial cultures. Cases with positive fungal or mycobacterial cultures were reviewed using the electronic medical record to classify the microbiological findings as representing true infection or not.


The Bone & Joint Journal
Vol. 103-B, Issue 12 | Pages 1745 - 1753
1 Dec 2021
Walinga AB Stornebrink T Langerhuizen DWG Struijs PAA Kerkhoffs GMMJ Janssen SJ

Aims

This study aimed to answer two questions: what are the best diagnostic methods for diagnosing bacterial arthritis of a native joint?; and what are the most commonly used definitions for bacterial arthritis of a native joint?

Methods

We performed a search of PubMed, Embase, and Cochrane libraries for relevant studies published between January 1980 and April 2020. Of 3,209 identified studies, we included 27 after full screening. Sensitivity, specificity, area under the curve, and Youden index of diagnostic tests were extracted from included studies. We grouped test characteristics per diagnostic modality. We extracted the definitions used to establish a definitive diagnosis of bacterial arthritis of a native joint per study.


Bone & Joint Open
Vol. 2, Issue 10 | Pages 879 - 885
20 Oct 2021
Oliveira e Carmo L van den Merkhof A Olczak J Gordon M Jutte PC Jaarsma RL IJpma FFA Doornberg JN Prijs J

Aims. The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizability of the CNN before application to clinical practice in other institutions. We aimed to answer the following questions: are current CNNs for fracture recognition externally valid?; which methods are applied for external validation (EV)?; and, what are reported performances of the EV sets compared to the internal validation (IV) sets of these CNNs?. Methods. The PubMed and Embase databases were systematically searched from January 2010 to October 2020 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The type of EV, characteristics of the external dataset, and diagnostic performance characteristics on the IV and EV datasets were collected and compared. Quality assessment was conducted using a seven-item checklist based on a modified Methodologic Index for NOn-Randomized Studies instrument (MINORS). Results. Out of 1,349 studies, 36 reported development of a CNN for fracture detection and/or classification. Of these, only four (11%) reported a form of EV. One study used temporal EV, one conducted both temporal and geographical EV, and two used geographical EV. When comparing the CNN’s performance on the IV set versus the EV set, the following were found: AUCs of 0.967 (IV) versus 0.975 (EV), 0.976 (IV) versus 0.985 to 0.992 (EV), 0.93 to 0.96 (IV) versus 0.80 to 0.89 (EV), and F1-scores of 0.856 to 0.863 (IV) versus 0.757 to 0.840 (EV). Conclusion. The number of externally validated CNNs in orthopaedic trauma for fracture recognition is still scarce. This greatly limits the potential for transfer of these CNNs from the developing institute to another hospital to achieve similar diagnostic performance. We recommend the use of geographical EV and statements such as the Consolidated Standards of Reporting Trials–Artificial Intelligence (CONSORT-AI), the Standard Protocol Items: Recommendations for Interventional Trials–Artificial Intelligence (SPIRIT-AI) and the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis–Machine Learning (TRIPOD-ML) to critically appraise performance of CNNs and improve methodological rigor, quality of future models, and facilitate eventual implementation in clinical practice. Cite this article: Bone Jt Open 2021;2(10):879–885


Aims. Monocyte-lymphocyte ratio (MLR) or neutrophil-lymphocyte ratio (NLR) are useful for diagnosing periprosthetic joint infection (PJI), but their diagnostic values are unclear for screening fixation-related infection (FRI) in patients for whom conversion total hip arthroplasty (THA) is planned after failed internal fixation for femoral neck fracture. Methods. We retrospectively included 340 patients who underwent conversion THA after internal fixation for femoral neck fracture from January 2008 to September 2020. Those patients constituted two groups: noninfected patients and patients diagnosed with FRI according to the 2013 International Consensus Meeting Criteria. Receiver operating characteristic (ROC) curves were used to determine maximum sensitivity and specificity of these two preoperative ratios. The diagnostic performance of the two ratios combined with preoperative CRP or ESR was also evaluated. Results. The numbers of patients with and without FRI were 19 (5.6%) and 321 (94.4%), respectively. Areas under the ROC curve for diagnosing FRI were 0.763 for MLR, 0.686 for NLR, 0.905 for CRP, and 0.769 for ESR. Based on the Youden index, the optimal predictive cutoffs were 0.25 for MLR and 2.38 for NLR. Sensitivity and specificity were 78.9% and 71.0% for MLR, and 78.9% and 56.4% for NLR, respectively. The combination of CRP with MLR showed a sensitivity of 84.2% and specificity of 94.6%, while the corresponding values for the combination of CRP with NLR were 89.5% and 91.5%, respectively. Conclusion. The presence of preoperative FRI among patients undergoing conversion THA after internal fixation for femoral neck fracture should be determined. The combination of preoperative CRP with NLR is sensitive tool for screening FRI in those patients. Cite this article: Bone Joint J 2021;103-B(9):1534–1540


The Bone & Joint Journal
Vol. 103-B, Issue 8 | Pages 1358 - 1366
2 Aug 2021
Wei C Quan T Wang KY Gu A Fassihi SC Kahlenberg CA Malahias M Liu J Thakkar S Gonzalez Della Valle A Sculco PK

Aims

This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA).

Methods

Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay.


The Bone & Joint Journal
Vol. 103-B, Issue 5 | Pages 923 - 930
1 May 2021
He R Wang Q Wang J Tang J Shen H Zhang X

Aims

As a proven and comprehensive molecular technique, metagenomic next-generation sequencing (mNGS) has shown its potential in the diagnosis of pathogens in patients with periprosthetic joint infection (PJI), using a single type of specimen. However, the optimal use of mNGS in the management of PJI has not been explored. In this study, we evaluated the diagnostic value of mNGS using three types of specimen with the aim of achieving a better choice of specimen for mNGS in these patients.

Methods

In this prospective study, 177 specimens were collected from 59 revision arthroplasties, including periprosthetic tissues, synovial fluid, and prosthetic sonicate fluid. Each specimen was divided into two, one for mNGS and one for culture. The criteria of the Musculoskeletal Infection Society were used to define PJI (40 cases) and aseptic failure (19 cases).


The Bone & Joint Journal
Vol. 103-B, Issue 3 | Pages 578 - 583
1 Mar 2021
Coulin B Demarco G Spyropoulou V Juchler C Vendeuvre T Habre C Tabard-Fougère A Dayer R Steiger C Ceroni D

Aims

We aimed to describe the epidemiological, biological, and bacteriological characteristics of osteoarticular infections (OAIs) caused by Kingella kingae.

Methods

The medical charts of all children presenting with OAIs to our institution over a 13-year period (January 2007 to December 2019) were reviewed. Among these patients, we extracted those which presented an OAI caused by K. kingae and their epidemiological data, biological results, and bacteriological aetiologies were assessed.