Introduction: Pain and disability are two parameters used to indicate and evaluate treatment in lumbar degenerative spine (LDS). Visual Analogue Scales (VAS) and Verbal Rating Scales (VRS) are frequently used to assess pain intensity. Both scales are validated and they have good psychometric properties. Aim: To evaluate
Introduction: Prostheses radiolucent lines are currently used to evaluate the components fixation. The objective of this study is to determine
Background. Although there are predictive equations that estimate the total fat mass obtained from multiple-site ultrasound (US) measurements, the predictive equation of total fat mass has not been investigated solely from abdominal subcutaneous fat thickness. Therefore, the aims of this study were; (1) to develop regression-based prediction equations based on abdominal subcutaneous fat thickness for predicting fat mass in young- and middle-aged adults, and (2) to investigate the validity of these equations to be developed. Methods. The study was approved by the Local Research Ethics Committee (Decision number: GO 19/788). Twenty-seven males (30.3 ± 8.7 years) and eighteen females (32.4 ± 9.5 years) were randomly divided into two groups as the model prediction group (19 males and 12 females) and the validation group (8 males and 6 females). Total body fat mass was determined by dual-energy X-ray absorptiometry (DXA). Abdominal subcutaneous fat thickness was measured by US. The predictive equations for total fat mass from US were determined as fat thickness (in mm) × standing height (in m). Statistical analyses were performed using R version 4.0.0. The association between the total fat mass and the abdominal subcutaneous fat thickness was interpreted using the Pearson test. The linear regression analysis was used to predict equations for total body fat mass from the abdominal subcutaneous fat thickness acquired by US. Then these predictive equations were applied to the validation group. The paired t-test was used to examine the difference between the measured and the predicted fat masses, and Lin's
Aims. The preoperative grading of chondrosarcomas of bone that accurately predicts surgical management is difficult for surgeons, radiologists, and pathologists. There are often discrepancies in grade between the initial biopsy and the final histology. Recent advances in the use of imaging methods have shown promise in the ability to predict the final grade. The most important clinical distinction is between grade 1 chondrosarcomas, which are amenable to curettage, and resection-grade chondrosarcomas (grade 2 and 3) which require en bloc resection. The aim of this study was to evaluate the use of a Radiological Aggressiveness Score (RAS) to predict the grade of primary chondrosarcomas in long bones and thus to guide management. Methods. A total of 113 patients with a primary chondrosarcoma of a long bone presenting between January 2001 and December 2021 were identified on retrospective review of a single oncology centre’s prospectively collected database. The nine-parameter RAS included variables from radiographs and MRI scans. The best cut-off of parameters to predict the final grade of chondrosarcoma after resection was determined using a receiver operating characteristic curve (ROC), and this was correlated with the biopsy grade. Results. A RAS of ≥ four parameters was 97.9% sensitive and 90.5% specific in predicting resection-grade chondrosarcoma based on a ROC cut-off derived using the Youden index. Cronbach’s α of 0.897 was derived as the interclass correlation for scoring the lesions by four blinded reviewers who were surgeons.
When treating periprosthetic femur fractures (PPFFs) around total hip arthroplasty (THA)], determining implant fixation status preoperatively is important, since this guides treatment regarding ORIF versus revision. The purpose of this study was to determine the accuracy of preoperative implant fixation status determination utilizing plain films and CT scans. Twenty-four patients who underwent surgery for Vancouver B type PPFF were included in the study. Two joint surgeons and two traumatologists reviewed plain films alone and made a judgment on fixation status. They then reviewed CT scans and fixation status was reassessed.
Acute spinal cord injury (SCI) is most often secondary to trauma, and frequently presents with associated injuries. A neurological examination is routinely performed during trauma assessment, including through Advanced Trauma Life Support (ATLS). However, there is no standard neurological assessment tool specifically used for trauma patients to detect and characterize SCI during the initial evaluation. The International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) is the most comprehensive and popular tool for assessing SCI, but it is not adapted to the acute trauma patients such that it is not routinely used in that setting. Therefore, the objective is to develop a new tool that can be used routinely in the initial evaluation of trauma patients to detect and characterize acute SCI, while preserving basic principles of the ISNCSCI. The completion rate of the ISCNSCI during the initial evaluation after an acute traumatic SCI was first estimated. Using a modified Delphi technique, we designed the Montreal Acute Classification of Spinal Cord Injuries (MAC-SCI), a new tool to detect and characterize the completeness (grade) and level of SCI in the polytrauma patient. The ability of the MAC-SCI to detect and characterize SCI was validated in a cohort of 35 individuals who have sustained an acute traumatic SCI. The completeness and neurological level of injury (NLI) were assessed by two independent assessors using the MAC-SCI, and compared to those obtained with the ISNCSCI. Only 33% of patients admitted after an acute traumatic SCI had a complete ISNCSCI performed at initial presentation. The MAC-SCI includes 53 of the 134 original elements of the ISNCSCI which is 60% less. There was a 100%
Acute spinal cord injury (SCI) is most often secondary to trauma, and frequently presents with associated injuries. A neurological examination is routinely performed during trauma assessment, including through Advanced Trauma Life Support (ATLS). However, there is no standard neurological assessment tool specifically used for trauma patients to detect and characterize SCI during the initial evaluation. The International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) is the most comprehensive and popular tool for assessing SCI, but it is not adapted to the acute trauma patients such that it is not routinely used in that setting. Therefore, the objective is to develop a new tool that can be used routinely in the initial evaluation of trauma patients to detect and characterize acute SCI, while preserving basic principles of the ISNCSCI. The completion rate of the ISCNSCI during the initial evaluation after an acute traumatic SCI was first estimated. Using a modified Delphi technique, we designed the Montreal Acute Classification of Spinal Cord Injuries (MAC-SCI), a new tool to detect and characterize the completeness (grade) and level of SCI in the polytrauma patient. The ability of the MAC-SCI to detect and characterize SCI was validated in a cohort of 35 individuals who have sustained an acute traumatic SCI. The completeness and neurological level of injury (NLI) were assessed by two independent assessors using the MAC-SCI, and compared to those obtained with the ISNCSCI. Only 33% of patients admitted after an acute traumatic SCI had a complete ISNCSCI performed at initial presentation. The MAC-SCI includes 53 of the 134 original elements of the ISNCSCI which is 60% less. There was a 100%
Acute spinal cord injury (SCI) is most often secondary to trauma, and frequently presents with associated injuries. A neurological examination is routinely performed during trauma assessment, including through Advanced Trauma Life Support (ATLS). However, there is no standard neurological assessment tool specifically used for trauma patients to detect and characterize SCI during the initial evaluation. The International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) is the most comprehensive and popular tool for assessing SCI, but it is not adapted to the acute trauma patients such that it is not routinely used in that setting. Therefore, the objective is to develop a new tool that can be used routinely in the initial evaluation of trauma patients to detect and characterize acute SCI, while preserving basic principles of the ISNCSCI. The completion rate of the ISCNSCI during the initial evaluation after an acute traumatic SCI was first estimated. Using a modified Delphi technique, we designed the Montreal Acute Classification of Spinal Cord Injuries (MAC-SCI), a new tool to detect and characterize the completeness (grade) and level of SCI in the polytrauma patient. The ability of the MAC-SCI to detect and characterize SCI was validated in a cohort of 35 individuals who have sustained an acute traumatic SCI. The completeness and neurological level of injury (NLI) were assessed by two independent assessors using the MAC-SCI, and compared to those obtained with the ISNCSCI. Only 33% of patients admitted after an acute traumatic SCI had a complete ISNCSCI performed at initial presentation. The MAC-SCI includes 53 of the 134 original elements of the ISNCSCI which is 60% less. There was a 100%
Magnetic resonance imaging (MRI) is the gold standard for the diagnosis of the pathologies affecting the glenohumeral joint and the rotator cuff diseases. MRI allows to highlight anatomic discontinuities of both muscles and tendons. However, MRI diagnostic accuracy has not proven to be highly sensitive in distinguishing between a partial-thickness tear and a full-thickness rotator cuff tear. The purpose of this study was to determine if MRI under axial traction can be helpful in increasing MRI sensitivity to identify partial-thickness rotator cuff tears. The study included 10 patients (4 males and 6 females) who had clinical examination and MRI suggesting a partial-thickness rotator cuff tear. They were candidates for shoulder arthroscopy because of persistent symptoms after at least three months of conservative treatment. The patients underwent a new MRI (under axial traction: MRI-AT) with a 4-kg weight applied to the affected arm. Then the patients underwent arthroscopy to confirm the diagnosis. Patients with a suspected full-thickness rotator cuff tear were excluded from the study. Patients’ average age was 52.4 years, and the dominant side was affected in 77.7% of the cases. Preoperative Constant-Murley Score was 57. MRI-AT showed that 3 patients were affected by a complete tear of the rotator cuff, 3 patients by a partial-thickness rotator cuff tear and 4 patients had no lesion. The analysis of data showed that: under axial traction the subacromial space increased by 0,2 mm (P value = 0,001075), the superior glenohumeral space decreased by 2.4 mm (P value = 0,07414), the inferior glenohumeral space increased by 0.3 mm (P value = 0,02942), the acromial angle decreased by 1.9° (P value = 0,0002104) and the acromion-glenohumeral angle decreased by 0.3° (P-value = 0,01974). Two experienced evaluators analyzed previous standard MRI and MRI-AT scans in a double-blinded fashion, with inter-rater evaluation of all the images and measures. Intraclass correlation coefficient (ICC) has been utilized to assess the reliability of the measures performed by different operators. ICC always resulted in more than 0.7, showing a high
Untreated clubfoot results in serious disability, but mild to moderate residual deformities can still cause functional limitations and pain. Measuring the impact of clubfoot deformities on children's wellbeing is challenging. There is little literature discussing the variability in outcomes and implications of clubfoot based on where geographically the child resides. Although the use of patient reported outcome measures (PROMs) is steadily growing in pediatric orthopaedics, few studies on clubfoot have incorporated them. The most widely used PROM for pediatric foot and ankle pathology is the Oxford Foot and Ankle Questionnaire for Children (OXFAQ-C) that include a physical, school and play, emotional and shoe wear domains. The aim of this study is to evaluate the validity and regional differences in scores of the OXFAQ-C questionnaire to identify functional disability in children with clubfoot in India and Canada. This is a retrospective cohort study of children in Indian and Canadian clubfoot registries aged 5-16 years who completed >1 parent or child OXFAQ-C. The OXFAQ-C was administered once in 01/2020 to all patients in the Indian registry, and prospectively between 06/2019 and 03/2021 at initial visit, 3, 6, 12 months post-intervention, then annually for the Canadian patients. Demographic, clubfoot, and treatment data were compared to OXFAQ-C domain scores. Descriptive statistics and regression analysis were performed. Parent-child
Aims. Accurate diagnosis of chronic periprosthetic joint infection (PJI) presents a significant challenge for hip surgeons. Preoperative diagnosis is not always easy to establish, making the intraoperative decision-making process crucial in deciding between one- and two-stage revision total hip arthroplasty (THA). Calprotectin is a promising point-of-care novel biomarker that has displayed high accuracy in detecting PJI. We aimed to evaluate the utility of intraoperative calprotectin lateral flow immunoassay (LFI) in THA patients with suspected chronic PJI. Methods. The study included 48 THAs in 48 patients with a clinical suspicion of PJI, but who did not meet European Bone and Joint Infection Society (EBJIS) PJI criteria preoperatively, out of 105 patients undergoing revision THA at our institution for possible PJI between November 2020 and December 2022. Intraoperatively, synovial fluid calprotectin was measured with LFI. Cases with calprotectin levels ≥ 50 mg/l were considered infected and treated with two-stage revision THA; in negative cases, one-stage revision was performed. At least five tissue cultures were obtained; the implants removed were sent for sonication. Results. Calprotectin was positive (≥ 50 mg/l) in 27 cases; out of these, 25 had positive tissue cultures and/or sonication. Calprotectin was negative in 21 cases. There was one false negative case, which had positive tissue cultures. Calprotectin showed an area under the curve of 0.917, sensitivity of 96.2%, specificity of 90.9%, positive predictive value of 92.6%, negative predictive value of 95.2%, positive likelihood ratio of 10.6, and negative likelihood ratio of 0.04. Overall, 45/48 patients were correctly diagnosed and treated by our algorithm, which included intraoperative calprotectin measurement. This yielded a 93.8%
Aim. Bone and joint infections (BJIs) are serious infections requiring early optimized antimicrobial therapy. BJIs can be polymicrobial or caused by fastidious bacteria, and the patient may have received antibiotics prior to sampling, which may decrease the sensitivity of culture-based diagnosis. Furthermore, culture-based diagnosis can take up to 14 days. Molecular approaches can be useful to overcome these concerns. The BioFire® system performs syndromic multiplex PCR in 1 hour, with only a few minutes of sample preparation. The BioFire® Joint Infection (JI) panel (BF-JI), recently FDA-cleared, detects both Gram-positive (n=15) and Gram-negative bacteria (n=14), Candida, and eight antibiotic resistance genes directly from synovial fluids. The aim of this study was to evaluate its performance in acute JIs in real-life conditions. Method. BF-JI was performed on synovial fluid from patients with clinical suspicion of acute JI, either septic arthritis or periprosthetic JI, in 6 French centers. The results of BF-JI were compared with the results of culture of synovial fluid and other concomitantly collected osteoarticular samples obtained in routine testing in the clinical microbiology laboratory. Results. From July 2021 to May 2022, 319 patients (including 10 children < 5y and 136 periprosthetic infections) had been included in the study. The BF-JI test was invalid for one patient (not retested). Among the 318 remaining patients, overall
External validation of machine learning predictive models is achieved through evaluation of model performance on different groups of patients than were used for algorithm development. This important step is uncommonly performed, inhibiting clinical translation of newly developed models. Recently, machine learning was used to develop a tool that can quantify revision risk for a patient undergoing primary anterior cruciate ligament (ACL) reconstruction (https://swastvedt.shinyapps.io/calculator_rev/). The source of data included nearly 25,000 patients with primary ACL reconstruction recorded in the Norwegian Knee Ligament Register (NKLR). The result was a well-calibrated tool capable of predicting revision risk one, two, and five years after primary ACL reconstruction with moderate accuracy. The purpose of this study was to determine the external validity of the NKLR model by assessing algorithm performance when applied to patients from the Danish Knee Ligament Registry (DKLR). The primary outcome measure of the NKLR model was probability of revision ACL reconstruction within 1, 2, and/or 5 years. For the index study, 24 total predictor variables in the NKLR were included and the models eliminated variables which did not significantly improve prediction ability - without sacrificing accuracy. The result was a well calibrated algorithm developed using the Cox Lasso model that only required five variables (out of the original 24) for outcome prediction. For this external validation study, all DKLR patients with complete data for the five variables required for NKLR prediction were included. The five variables were: graft choice, femur fixation device, Knee Injury and Osteoarthritis Outcome Score (KOOS) Quality of Life subscale score at surgery, years from injury to surgery, and age at surgery. Predicted revision probabilities were calculated for all DKLR patients. The model performance was assessed using the same metrics as the NKLR study:
Aims. Our aim was to examine the Elixhauser and Charlson comorbidity indices, based on administrative data available before surgery, and to establish their predictive value for mortality for patients who underwent hip arthroplasty in the management of a femoral neck fracture. Patients and Methods. We analyzed data from 42 354 patients from the Swedish Hip Arthroplasty Register between 2005 and 2012. Only the first operated hip was included for patients with bilateral arthroplasty. We obtained comorbidity data by linkage from the Swedish National Patient Register, as well as death dates from the national population register. We used univariable Cox regression models to predict mortality based on the comorbidity indices, as well as multivariable regression with age and gender. Predictive power was evaluated by a
Aims. Despite numerous studies focusing on periprosthetic joint infections (PJIs), there are no robust data on the risk factors and timing of metachronous infections. Metachronous PJIs are PJIs that can arise in the same or other artificial joints after a period of time, in patients who have previously had PJI. Methods. Between January 2010 and December 2018, 661 patients with multiple joint prostheses in situ were treated for PJI at our institution. Of these, 73 patients (11%) developed a metachronous PJI (periprosthetic infection in patients who have previously had PJI in another joint, after a lag period) after a mean time interval of 49.5 months (SD 30.24; 7 to 82.9). To identify patient-related risk factors for a metachronous PJI, the following parameters were analyzed: sex; age; BMI; and pre-existing comorbidity. Metachronous infections were divided into three groups: Group 1, metachronous infections in ipsilateral joints; Group 2, metachronous infections of the contralateral lower limb; and Group 3, metachronous infections of the lower and upper limb. Results. We identified a total of 73 metachronous PJIs: 32 PJIs in Group 1, 38 in Group 2, and one in Group 3. The rate of metachronous infection was 11% (73 out 661 cases) at a mean of four years following first infection. Diabetes mellitus incidence was found significantly more frequently in the metachronous infection group than in non-metachronous infection group. The rate of infection in Group 1 (21.1%) was significantly higher (p = 0.049) compared to Groups 2 (6.2%) and 3 (3%). The time interval of metachronous infection development was shorter in adjacent joint infections.
Introduction. The application of artificial intelligence (A.I) using patient reported outcomes (PROs) to predict benefits, risks, benefits and likelihood of improvement following surgery presents a new frontier in shared decision-making. The purpose of this study was to assess the impact of an A.I-enabled decision aid versus patient education alone on decision quality in patients with knee OA considering total knee replacement (TKR). Secondarily we assess impact on shared decision-making, patient satisfaction, functional outcomes, consultation time, TKR rates and treatment
Aims. We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Methods. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s
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
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
Aims. Use of molecular sequencing methods in periprosthetic joint infection (PJI) diagnosis and organism identification have gained popularity. Next-generation sequencing (NGS) is a potentially powerful tool that is now commercially available. The purpose of this study was to compare the diagnostic accuracy of NGS, polymerase chain reaction (PCR), conventional culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al in the diagnosis of PJI. Methods. In this retrospective study, aspirates or tissue samples were collected in 30 revision and 86 primary arthroplasties for routine diagnostic investigation for PJI and sent to the laboratory for NGS and PCR.
