In a clinical setting, there is a need for simple gait kinematic measurements to facilitate objective unobtrusive patient monitoring. The objective of this study is to determine if a learned classification model's output can be used to monitor a person's recovery status post-TKA. The gait kinematics of 20 asymptomatic and 17 people with TKA were measured using a full-body Xsens model1. The experimental group was measured at 6 weeks, 3, 6, and 12 months post-surgery. Joint angles of the ankle, knee, hip, and spine per stride (10 strides) were extracted from the Xsens software (MVN Awinda studio 4.4)1. Statistical features for each subject at each evaluation moment were derived from the kinematic time-series data. We normalised the features using standard scaling2. We trained a logistic regression (LR) model using L1-regularisation on the 6 weeks post-surgery data2–4. After training, we applied the trained LR- model to the normalised features computed for the subsequent timepoints. The model returns a score between 0 (100% confident the person is an asymptomatic control) and 1 (100% confident this person is a patient). The decision boundary is set at 0.5. The classification accuracy of our LR-model was 94.58%. Our population's probability of belonging to the patient class decreases over time. At 12 months post-TKA, 38% of our patients were classified as asymptomatic.
The accurate positioning of the total knee arthroplasty affects the survival of the implants(1). Alignment of the femoral component in relation to the native knee is best determined using pre- and post-operative 3D-CT reconstruction(2). Currently, the scans are visualised on separate displays. There is a high inter- and intra-observer variability in measurements of implant rotation and translation(3). Correct alignment is required to allow a direct comparison of the pre- and post-operative surfaces. This is prevented by the presence of the prostheses, the bone shape alteration around the implant, associated metal artefacts, and possibly a segmentation noise. The aim is to create a novel method to automatically register pre- and post-operative femora for the direct comparison of the implant and the native bone. The concept is to use post-operative femoral shaft segments free of metal noise and of surgical alteration for alignment with the pre-operative scan. It involves three steps. Firstly, using principal component analysis, the femoral shafts are re-oriented to match the X axis. Secondly, variants of the post-operative scan are created by subtracting 1mm increments from the distal femoral end. Thirdly, an iterative closest point algorithm is applied to align the variants with the pre-operative scan. For exploratory validation, this algorithm was applied to a mesh representing the distal half of a 3D scanned femur. The mesh of a prosthesis was blended with the femur to create a post-operative model. To simulate a realistic environment, segmentation and metal artefact noise were added. For segmentation noise, each femoral vertex was translated randomly within +−1mm,+−2mm,+−3mm along its normal vector. To create metal artefact random noise was added within 50 mm of the implant points in the planes orthogonal to the shaft. The alignment error was considered as the average distance between corresponding points which are identical in pre- and post-operative femora. These preliminary results obtained within a simulated environment show that by using only the native parts of the femur, the algorithm was able to automatically register the pre- and post-operative scans even in presence of the implant. Its application will allow visualisation of the scans on the same display for the direct comparison of the perioperative scans. This method requires further validation with more realistic noise models and with patient data. Future studies will have to determine if correct alignment has any effect on inter- and intra-observer variability.
Patients ≤ 55 years have a high primary TKA revision rate compared to patients >55 years. Guided motion knee devices are commonly used in younger patients yet outcomes remain unknown. In this sub-group analysis of a large multicenter study, 254 TKAs with a second-generation guided motion knee implant were performed between 2011–2017 in 202 patients ≤ 55 years at seven US and three European sites. Revision rates were compared with Australian Joint Registry (AOANJRR) 2017 data. Average age 49.7 (range 18–54); 56.4% females; average BMI 34 kg/m2; 67.1% obese; patellae resurfaced in 98.4%. Average follow-up 4.2 years; longest follow-up six years; 27.5% followed-up for ≥ five years. Of eight revisions: total revision (one), tibial plate replacements (three), tibial insert exchanges (four). One tibial plate revision re-revised to total revision. Revision indications were mechanical loosening (n=2), infection (n=3), peri-prosthetic fracture (n=1), and instability (n=2). The Kaplan-Meier revision estimate was 3.4% (95% C.I. 1.7% to 6.7%) at five years compared to AOANJRR rate of 6.9%. There was no differential risk by sex. The revision rate of the second-generation guided motion knee system is lower in younger patients compared to registry controls.
Outcomes for guided motion primary total knee arthroplasty (TKA) in obese patients are unknown. 1,684 consecutive patients underwent 2,059 primary TKAs with a second-generation guided motion implant between 2011–2017 at three European and seven US sites. Of 2,003 (97.3%) TKAs in 1,644 patients with BMI data: average age 64.5 years; 58.4% females; average BMI 32.5 kg/m2; 13.4% had BMI ≥ 40 kg/m2. Subjects with BMI ≥ 40 kg/m2 had longest length of hospital stay (LOS) at European sites; LOS similar at US sites. Subjects with BMI ≥ 40 kg/m2 (P=0.0349) had longest surgery duration. BMI ≥ 40 kg/m2 had more re-hospitalizations or post-TKA reoperations than BMI < 40 kg/m2 (12.7% and 9.2% at five-year post-TKA, P<0.0495). Surgery duration and long-term complication rates are higher in patients with BMI ≥ 40 kg/m2, but device revision risk is not elevated.
Fractures of the prosthetic components after
Patients with Paget's Disease of Bone (PDB) more frequently require total hip arthroplasty (THA) and
The Severity Scoring System (SSS) is a guide to interpreting findings across clinical, functional, and radiological findings, used by qualified, specially trained physiotherapists in the advanced practice role in order to provide consistency in determining the severity of the patient's condition and need for surgical consultation. The system has been utilized for over 14 years as a part of standardized assessment and management care and was incorporated into virtual care in 2020 following the pandemic restrictions. The present study examined the validity of the modified SSS in virtual care. Patients who were referred to the Rapid Access Clinic (RAC), were contacted via phone by two experienced advanced practice practitioners (APPs) from May to July 2020, when in-person care was halted due to the pandemic. The virtual interview included taking history, completing self-reported measures for pain and functional ability and reviewing the radiological reports. A total of 63 patients were interviewed (mean age 68, SD=9), 34 (54%) females. Of 63 patients, 33 (52%) were considered a candidate for
The study compared thigh-shank and shank-foot coordination during gait before and after
Unicompartmental knee arthroplasty (UKA) is associated with a higher risk of revision compared with
To determine risk factors of infection in total knee arthroplasty. This descriptive study was conducted in the Department of Orthopedics for a duration of three years from January 2016 to January 2019. All patients undergoing primary total knee replacement were included in the study. Exclusion criteria were all patients operated in another hospital and revision total knee replacement. All patients were followed up at 2, 4, 8, 12 and 24 weeks post-operatively. Signs of inflammation and inflammatory markers such as total leukocyte count (TLC), C-reactive protein (CRP) and ESR were measured. Risk factors like age, body mass index (BMI), ASA, co-morbid conditions were also noted. A total of 78 patients underwent primary unilateral Total Knee Replacement (TKR) during the study period. Of these, 30 (34.09%) were male and 48 (61.54%) female patients. Mean age of patients was 68.32 ± 8.54 years. Average BMI 25.89 Kg/m2 .Osteoarthritis was the pre-dominant cause of total knee replacement (94.87%). Among co-morbid factors 33.33% were diabetic, 28.20% having ischemic heart disease and 12.82% with chronic lung disease. Upon anaesthesia fitness pre-operatively, 91.02% patients had an American society of anaesthesiologist score (ASA) between 0–2 while 07 (8.97%) between 3- 5. Average duration of surgery was 85.62± 4.11 minutes. 6.41% cases got infected. In majority of the infected cases (60%), Staphylococcus aureus was the infective organism. Diabetes Mellitus (p=0.01) and Obesity (p=0.02) had a significant relation to post-operative infection. Pre-operative risk evaluation and prevention strategies along with early recognition of infection and control can greatly reduce the risk of joint infection post-TKR which will not only improve the mobility of patient but also its morbidity and mortality as well. Key Words:. C-reactive protein (CRP), Erythrocyte Sedimentation Rate (ESR), Staphylococcus aureus,
Numerous papers present in-vivo knee kinematics data following
Introduction. Distal femur fractures around a
Purpose. To compare postoperative clinical outcomes between posterior cruciate ligament (PCL) retaining and resecting
This study examined pre-operative measures to predict post-operative biomechanical outcomes in
7–20 % of the patients with a
Introduction. There is a lack of evidence-based treatments for patients with chronic pain after
Introduction. This study aimed to evaluate the effectiveness of a novel intraoperative navigation platform for
Mechanical alignment (MA) in