Machine learning-based bioimpedance assessment of knee osteoarthritis severity.

This study proposes a multiclass model to classify the severity of knee osteoarthritis (KOA) using bioimpedance measurements. The experimental setup considered three types of measurements using eight electrodes: global impedance with adjacent pattern, global impedance with opposite pattern, and direct impedance measurement, which were taken using an electronic device proposed by authors and based on the Analog Devices AD5933 impedance converter. The study comprised 37 participants, 25 with healthy knees and 13 with three different degrees of KOA. All participants performed 20 repetitions of each of the following five tasks: (i) sitting with the knee bent, (ii) sitting with the knee extended, (iii) sitting and performing successive extensions and flexions of the knee, (iv) standing, and (v) walking. Data from the 15 experimental setups (3 types of measurements×5 exercises) were used to train a multiclass random forest. The training and validation cycle was repeated 100 times using random undersampling. At each of the 100 cycles, 80% of the data were used for training and the rest for testing. The results showed that the proposed approach achieved average sensitivities and specificities of 100% for the four KOA severity grades in the extension, cyclic, and gait tasks. This suggests that the proposed method can serve as a screening tool to determine which individuals should undergo x-rays or magnetic resonance imaging for further evaluation of KOA.

Complexity Assessment of Chronic Pain in Elderly Knee Osteoarthritis Based on Neuroimaging Recognition Techniques.

The chronic pain of knee osteoarthritis in the elderly is investigated in detail in this paper, as well as the complexity of chronic pain utilising neuroimaging recognition techniques. Chronic pain in knee osteoarthritis (KOA) has a major effect on patients' quality of life and functional activities; therefore, understanding the causes of KOA pain and the analgesic advantages of different therapies is important. In recent years, neuroimaging techniques have become increasingly important in basic and clinical pain research. Thanks to the application and development of neuroimaging techniques in the study of chronic pain in KOA, researchers have found that chronic pain in KOA contains both injury-receptive and neuropathic pain components. The neuropathic pain mechanism that causes KOA pain is complicated, and it may be produced by peripheral or central sensitization, but it has not gotten enough attention in clinical practice, and there is no agreement on how to treat combination neuropathic pain KOA. As a result, using neuroimaging techniques such as magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS), this review examines the changes in brain pathophysiology-related regions caused by KOA pain, compares the latest results in pain assessment and prediction, and clarifies the central brain analgesic mechanistic. The capsule network model is introduced in this paper from the perspective of deep learning network structure to construct an information-complete and reversible image low-level feature bridge using isotropic representation, predict the corresponding capsule features from MRI voxel responses, and then, complete the accurate reconstruction of simple images using inverse transformation. The proposed model improves the structural similarity index by about 10%, improves the reconstruction performance of low-level feature content in simple images by about 10%, and achieves feature interpretation and analysis of low-level visual cortical fMRI voxels by visualising capsule features, according to the experimental results.

Interpretable and parameter optimized ensemble model for knee osteoarthritis assessment using radiographs.

Knee osteoarthritis (KOA) is an orthopedic disorder with a substantial impact on mobility and quality of life. An accurate assessment of the KOA levels is imperative in prioritizing meaningful patient care. Quantifying osteoarthritis features such as osteophytes and joint space narrowing (JSN) from low-resolution images (i.e., X-ray images) are mostly subjective. We implement an objective assessment and quantification of KOA to aid practitioners. In particular, we developed an interpretable ensemble of convolutional neural network (CNN) models consisting of three modules. First, we developed a scale-invariant and aspect ratio preserving model to localize Knee joints. Second, we created multiple instances of "hyperparameter optimized" CNN models with diversity and build an ensemble scoring system to assess the severity of KOA according to the Kellgren-Lawrence grading (KL) scale. Third, we provided visual explanations of the predictions by the ensemble model. We tested our models using a collection of 37,996 Knee joints from the Osteoarthritis Initiative (OAI) dataset. Our results show a superior (13-27%) performance improvement compared to the state-of-the-art methods.

Response Mapping Methods to Estimate the EQ-5D-5L From the Western Ontario McMaster Universities Osteoarthritis in Patients With Hip or Knee Osteoarthritis.

OBJECTIVES: The mapping technique can estimate generic preference-based measure scores through a specific measure that cannot be used in economic evaluations. This study compared 2 response mapping methods to estimate EQ-5D-5L scores using the Western Ontario McMaster Universities Osteoarthritis (WOMAC). METHODS: The sample consisted of 758 patients with the hip or knee osteoarthritis recruited in baseline. Bayesian networks (BN) and multinomial logistic regression (ML) were used as response mapping models. Predictions were obtained using the 6-month follow-up as a validation sample. The mean absolute error, mean squared error, deviation from the root mean squared error and intraclass correlation coefficient were calculated as precision measures. RESULTS: There was 5.5% of missing data, which was removed. The mean age was 69.6 years (standard deviation = 10.5), with 61.6% of women. The BN model presented lower mean absolute error, mean squared error, root mean squared error and higher intraclass correlation coefficient than the ML model. Only the WOMAC items pain and physical function items were related with the EQ-5D-5L dimensions. CONCLUSION: BN response mapping models are more robust methods, with better prediction results, than ML models. The BN model also provided a graphic representation of the dependency relationships between the EQ-5D-5L dimensions and the different WOMAC items that could be useful in the clinical investigation of patients with hip or knee osteoarthritis.

Accuracy of soft tissue balancing in total knee arthroplasty using surgeon-defined assessment versus a gap-balancer or electronic sensor.

BACKGROUND: Soft tissue balancing is essential for the success of total knee arthroplasty (TKA) and is mainly dependent on surgeon-defined assessment (SDA) or a gap-balancer (GB). However, an electronic sensor has been developed to objectively measure the gap pressure. This study aimed to evaluate the accuracy of soft tissue balancing using SDA and GB compared with a sensor. METHODS: Forty-eight patients undergoing TKA (60 knees) were prospectively enrolled. Soft tissue balancing was sequentially performed using SDA, a GB, and an electronic sensor. We compared the SDA, GB, and sensor data to calculate the sensitivity, specificity, and accuracy at 0°, 45°, 90°, and 120° flexion. Cumulative summation (CUSUM) analysis was performed to assess the surgeon's performance during the sensor introductory phase. RESULTS: The sensitivity of SDA was 63.3%, 68.3%, 80.0%, and 80.0% at 0°, 45°, 90°, and 120°, respectively. The accuracy of the GB compared with sensor data was 76.7% and 71.7% at 0° and 90°, respectively. Cohen's kappa coefficient for the accuracy of the GB was 0.406 at 0° (moderate agreement) and 0.227 at 90° (fair agreement). The CUSUM 0° line achieved good prior performance at case 45, CUSUM 90° and 120° showed a trend toward good prior performance, while CUSUM 45° reached poor prior performance at case 8. CONCLUSION: SDA was a poor predictor of knee balance. GB improved the accuracy of soft tissue balancing, but was still less accurate than the sensor, particularly for unbalanced knees. SDA improved with ongoing use of the sensor, except at 45° flexion.

Assessment of quantitative [18F]Sodium fluoride PET measures of knee subchondral bone perfusion and mineralization in osteoarthritic and healthy subjects.

OBJECTIVE: Molecular information derived from dynamic [18F]sodium fluoride ([18F]NaF) PET imaging holds promise as a quantitative marker of bone metabolism. The objective of this work was to evaluate physiological mechanisms of [18F]NaF uptake in subchondral bone of individuals with and without knee osteoarthritis (OA). METHODS: Eleven healthy volunteers and twenty OA subjects were included. Both knees of all subjects were scanned simultaneously using a 3T hybrid PET/MRI system. MRI MOAKS assessment was performed to score the presence and size of osteophytes, bone marrow lesions, and cartilage lesions. Subchondral bone kinetic parameters of bone perfusion (K1), tracer extraction fraction, and total tracer uptake into bone (Ki) were evaluated using the Hawkins 3-compartment model. Measures were compared between structurally normal-appearing bone regions and those with structural findings. RESULTS: Mean and maximum SUV and kinetic parameters Ki, K1, and extraction fraction were significantly different between Healthy subjects and subjects with OA. Between-group differences in metabolic parameters were observed both in regions where the OA group had degenerative changes as well as in regions that appeared structurally normal. CONCLUSIONS: Results suggest that bone metabolism is altered in OA subjects, including bone regions with and without structural findings, compared to healthy subjects. Kinetic parameters of [18F]NaF uptake in subchondral bone show potential to quantitatively evaluate the role of bone physiology in OA initiation and progression. Objective measures of bone metabolism from [18F]NaF PET imaging can complement assessments of structural abnormalities observed on MRI.

An algorithmic approach to reducing unexplained pain disparities in underserved populations.

Underserved populations experience higher levels of pain. These disparities persist even after controlling for the objective severity of diseases like osteoarthritis, as graded by human physicians using medical images, raising the possibility that underserved patients' pain stems from factors external to the knee, such as stress. Here we use a deep learning approach to measure the severity of osteoarthritis, by using knee X-rays to predict patients' experienced pain. We show that this approach dramatically reduces unexplained racial disparities in pain. Relative to standard measures of severity graded by radiologists, which accounted for only 9% (95% confidence interval (CI), 3-16%) of racial disparities in pain, algorithmic predictions accounted for 43% of disparities, or 4.7× more (95% CI, 3.2-11.8×), with similar results for lower-income and less-educated patients. This suggests that much of underserved patients' pain stems from factors within the knee not reflected in standard radiographic measures of severity. We show that the algorithm's ability to reduce unexplained disparities is rooted in the racial and socioeconomic diversity of the training set. Because algorithmic severity measures better capture underserved patients' pain, and severity measures influence treatment decisions, algorithmic predictions could potentially redress disparities in access to treatments like arthroplasty.

How Are Neighborhood Characteristics Associated With Mental and Physical Functioning Among Older Adults With Radiographic Knee Osteoarthritis?

OBJECTIVE: To examine how neighborhood characteristics are associated with health outcomes among older adults with osteoarthritis. METHODS: In multilevel, cross-sectional, and longitudinal analyses we examined whether 4 neighborhood characteristics were associated with depressive symptoms and reported knee impact scores, and whether the neighborhood characteristics interacted with race/ethnicity among older adults with radiographic knee osteoarthritis (n = 656 for cross-sectional analyses and n = 434 for longitudinal analyses). The data came from the Johnston County Osteoarthritis Project, a prospective cohort study in North Carolina designed to examine risk factors for osteoarthritis. RESULTS: Although few longitudinal associations were found, cross-sectional results suggested that greater perceived neighborhood social cohesion (B = -0.04, P < 0.001) and perceived neighborhood resources for physical activity and walking (B = -0.03, P < 0.001) were associated with fewer depressive symptoms, and that greater perceived neighborhood resources for physical activity and walking were associated with higher (better) knee impact scores (B = 0.48, P = 0.008). We also observed 2 significant interactions among neighborhood characteristics and race/ethnicity related to depressive symptoms (P < 0.01); for African American adults, greater perceived neighborhood resources for physical activity and walking were associated with fewer depressive symptoms (B = -0.03, P < 0.001), but for White adults, greater perceived neighborhood safety was associated with fewer depressive symptoms (B = -0.04, P = 0.003). CONCLUSION: In a sample of older adults with radiographic knee osteoarthritis, neighborhood context mattered, but in nuanced ways. Interventions aiming to improve mental and physical functioning of older adults with knee osteoarthritis can look to this study as evidence for the importance of neighborhood characteristics.

Impact of Diabetes Mellitus on Knee Osteoarthritis Pain and Physical and Mental Status: Data From the Osteoarthritis Initiative.

OBJECTIVE: Diabetes mellitus (DM) appears to increase osteoarthritic knee pain, which may be related to greater adiposity and more advanced disease status often observed in individuals with osteoarthritis (OA) and DM. We aimed to assess whether OA knee pain and health status are worse in individuals with OA and DM, independent of these potential confounders. METHODS: We included 202 OA participants with DM and 2,279 without DM from the Osteoarthritis Initiative. Knee pain was evaluated using the Knee Injury and Osteoarthritis Outcome Score (KOOS) and a numeric rating scale (NRS). Physical and mental status were assessed by the Medical Outcomes Study Short Form 12 (SF-12) questionnaire, physical component summary (PCS) score and mental component summary (MCS) score, and by the Center for Epidemiologic Studies Depression Scale (CES-D). Linear regression models assessed the influence of DM, adjusted for age, sex, body mass index (BMI), and radiographic severity. RESULTS: OA participants with DM reported worse knee pain and greater physical and mental issues compared with participants without DM. Individuals with DM had worse KOOS pain (ß = -4.72 [95% confidence interval (95% CI) -7.22, -2.23]) and worse NRS pain (ß = 0.42 [95% CI 0.04, 0.80]) independent of BMI, OA severity, age, and sex. The negative influence of DM was also apparent for SF-12 PCS (ß = -3.49 [95% CI -4.73, -2.25]), SF-12 MCS (ß = -1.42 [95% CI -2.57, -0.26]), and CES-D (ß = 1.08 [95% CI 0.08, 2.08]). CONCLUSION: Individuals with knee OA experience on average higher pain intensity and a worse physical and mental health status if they have DM. Linear regression models show that DM is a risk factor for higher pain, in addition to and independent of greater BMI and radiographic OA severity.

Cost-effectiveness of duloxetine for knee OA subjects: the role of pain severity.

OBJECTIVE: Establish the impact of pain severity on the cost-effectiveness of generic duloxetine for knee osteoarthritis (OA) in the United States. DESIGN: We used a validated computer simulation of knee OA to compare usual care (UC) - intra-articular injections, opioids, and total knee replacement (TKR) - to UC preceded by duloxetine in those no longer achieving pain relief from non-steroidal anti-inflammatory drugs (NSAIDs). Outcomes included quality-adjusted life years (QALYs), lifetime medical costs, and incremental cost-effectiveness ratios (ICERs). We considered cohorts with mean ages 57-75 years and Western Ontario and McMaster Osteoarthritis Index (WOMAC) pain 25-55 (0-100, 100-worst). We derived inputs from published data. We discounted costs and benefits 3% annually. We conducted sensitivity analyses of duloxetine efficacy, duration of pain relief, toxicity, and costs. RESULTS: Among younger subjects with severe pain (WOMAC pain = 55), duloxetine led to an additional 9.6 QALYs per 1,000 subjects (ICER = $88,500/QALY). The likelihood of duloxetine being cost-effective at willingness-to-pay (WTP) thresholds of $50,000/QALY and $100,000/QALY was 40% and 54%. Offering duloxetine to older patients with severe pain led to ICERs >$150,000/QALY. Offering duloxetine to subjects with moderate pain (pain = 25) led to ICERs <$50,000/QALY, regardless of age. Among knee OA subjects with severe pain (pain = 55) who are unwilling or unable to undergo TKR, ICERs were <$50,600/QALY, regardless of age. CONCLUSIONS: Duloxetine is a cost-effective addition to knee OA UC for subjects with moderate pain or those with severe pain unable or unwilling to undergo TKR. Among younger subjects with severe pain, duloxetine is cost-effective at WTP thresholds >$88,500/QALY.

Assessment of diagnostic criteria for the identification of central sensitization in patients with osteoarthritis pain: Results from a Delphi survey.

ABSTRACT: To assess diagnostic criteria and currently used tools for the identification of central sensitization (CS) in patients with joint pain due to osteoarthritis (OA).Qualitative, cross-sectional and multicenter study based on a 2-round Delphi surveyPublic and private medical centers attending patients with joint pain.A total of 113 specialists in traumatology, physical medicine and rehabilitation, pain management, rheumatology, primary care physicians and geriatrics were enrolled in the study.Participants completed an ad-hoc 26-item questionnaire available from a microsite in Internet.The questionnaire was divided into 6 sections with general data on CS, impact of CS in patients with knee osteoarthritis (KOA), diagnostic criteria for CS, non-pharmacological and pharmacological treatment of CS and usefulness of the concept of CS in the integral management of patients with KOA. Consensus was defined as 75% agreement.Diagnostic criteria included pain of disproportionate intensity to the radiological joint lesion (agreement 86.7%), poor response to usual analgesics (85.8%), progression of pain outside the site of the lesion (76.1%) and concurrent anxiety and depression (76.1%). Based on the opinion of the specialists, about 61% of patients with KOA present moderate-to-severe pain, 50% of them show poor response to conventional analgesics, and 40% poor clinical-radiological correlation. Patients with KOA and CS showed higher functional disability and impairment of quality of life than those without CS (88.5%) and have a poor prognosis of medical, rehabilitation and surgical treatment (86.7%). Early diagnosis and treatment of CS may preserve function and quality of life during all steps of the disease (90.3%).The management of patients with osteoarthritis pain and CS requires the consideration of the intensity of pain related to the joint lesion, response to analgesics, progression of pain to other areas and concurrent anxiety and depression to establish an adequate therapeutic approach based on diagnostic criteria of CS.

Adapted protocol of rate of force development and relaxation scaling factor for neuromuscular assessment in patients with knee osteoarthritis.

BACKGROUND: The linear relationship between muscle torque and rate of torque rise/relaxation during rapid muscle contractions has been recently introduced as a novel measure of muscle quickness, termed rate of torque development/relaxation scaling factor (RTD-SF/RTR-SF). Because the standard assessment protocol includes potentially painful muscle contractions, the first purpose of this study was to validate an adapted RTD-SF/RTR-SF protocol for knee extensor muscles that utilizes lower submaximal intensities and can be used in knee osteoarthritis patients. METHODS: A cross-sectional study was performed on a group of healthy controls (n = 24) who underwent the standard RTD-SF/RTR-SF protocol (20-80% of maximum) and the knee osteoarthritis group (n = 24) who underwent the adapted protocol (20-60% of maximum). We calculated the RTD-SF, RTR-SF and the linearity (r2) for both relationships, based on both protocols in controls. RESULTS: The validity of the adapted protocol was acceptable (intraclass correlation coefficient = 0.77-0.93), with low within-participant variation (coefficient of variability <10%) for both outcome measures. Compared with the control group, the knee osteoarthritis group had similar RTD-SF, but lower linearity of RTD-SF (0.90 vs. 0.82). The RTR-SF (8.0/s vs. 6.7/s) and its linearity (0.87 vs. 0.73) were significantly reduced. Comparing the affected and the unaffected leg in the knee osteoarthritis group, the unaffected leg had greater maximal torque (96.2 vs. 84.1 Nm) and higher linearity for RTD-SF (0.86 vs. 0.80) and RTR-SF (0.82 vs. 0.73). CONCLUSIONS: We confirmed the validity of the adapted RTD/RTR-SF protocol and its sensitivity to impairments associated with knee osteoarthritis.

Static balance assessment in patients with severe osteoarthritis of the knee.

BACKGROUND: Pain related to severe knee osteoarthritis may lead to static balance disorders. Patients with severe knee arthrosis with arthroplasty indication should be aware of the postoperative rehabilitation menu because their balance ability has decreased. METHODS: The study involved 33 patients with unilateral severe osteoarthritis (the study group) and 33 healthy subjects (the control group). We conducted the measurements of static balance with the CQStab2P platform. Functional disability was assessed using the Knee Society Score (KSS). RESULTS: In the study group, balance distribution asymmetry between lower limbs was higher. Patients unloaded the painful joints due to pain and knee instability. We observed statistically significant differences both with eyes open and with eyes closed only for balance symmetry. The study group had mean results of 53.9 (±19.1 SD) points in the KSS scales and 52.1 (±24.1) in the KSS function. There were statistically significant positive correlations regarding KSS and body height (0.270; P < 0.05), and negative correlations for body mass index (0.329; P < 0.01). In measurements with open eyes, patients' KSS correlated with mean amplitude of sways (-0,227; P < 0.01) and max anteroposterior (-0.279; P < 0.01). In measurements with eyes closed, KSS function correlated with number of sways in the sagittal plane (0.331; P < 0.01). CONCLUSIONS: Patients with severe osteoarthritis suffered from balance disorders regarding limbs' asymmetrical loading both under visual control and without visual control.

Evaluating the structural effects of intra-articular sprifermin on cartilage and non-cartilaginous tissue alterations, based on sqMRI assessment over 2 years.

OBJECTIVE: Sprifermin (recombinant human fibroblast growth factor-18), a potential disease-modifying osteoarthritis (OA) drug, demonstrated dose-dependent effects on femorotibial cartilage thickness (by quantitative magnetic resonance imaging [MRI]) in the phase II FORWARD study. This post-hoc analysis evaluated the potential effects of sprifermin on several articular structures in the whole joint over 24 months using semi-quantitative MRI assessment. DESIGN: Patients aged 40-85 years with symptomatic radiographic knee OA, Kellgren-Lawrence grade 2 or 3, and medial minimum joint space width ≥2.5 mm in the target knee were randomized (1:1:1:1:1) to receive three double-blinded, once-weekly, intra-articular injections of sprifermin 30 µg or 100 µg or placebo every 6 (q6mo) or 12 months. 1.5- or 3 T MRIs were read using the Whole-Organ Magnetic Resonance Imaging Score (WORMS) system at baseline and 24 months. Change from baseline at 24 months on compartment and/or whole knee level was assessed for cartilage morphology, bone marrow lesions (BMLs), and osteophytes by delta-subregional and delta-sum (DSM) approaches. Menisci, Hoffa-synovitis, and effusion-synovitis were also evaluated for worsening. RESULTS: 549 patients were included. Dose-dependent treatment effects from baseline to 24 months were observed on cartilage morphology (sprifermin 100 µg q6mo vs placebo; mean DSM (95% confidence interval [CI]) -0.6 (-1.5, 0.2); less cartilage worsening) in the entire knee and BMLs sprifermin 100 µg q6mo vs placebo; mean DSM (95% CI) -0.2 (-0.5, 0.1) in the patellofemoral compartment. No effects over 24 months were observed on osteophytes, menisci, Hoffa-synovitis or effusion-synovitis. CONCLUSIONS: Positive effects associated with sprifermin were observed for cartilage morphology changes, and BML improvement. There were no meaningful negative or positive effects associated with sprifermin in the other joint tissues examined.

Functional movement assessment by means of inertial sensor technology to discriminate between movement behaviour of healthy controls and persons with knee osteoarthritis.

BACKGROUND: Apart from biomechanical alterations in movement patterns, it is known that movement limitations in persons with knee osteoarthritis (PwKOA) are related to an individual's perception and belief regarding pain and disability. To gain more insights into the functional movement behaviour of PwKOA in a clinical setting, inertial sensor technology can be applied. This study first aims to evaluate the ability of inertial sensors to discriminate between healthy controls (HC) and PwKOA. Secondly, this study aims to determine the relationship between movement behaviour, pain-related factors and disability scores. METHODS: Twelve HC and 19 PwKOA were included. Five repetitions of six functional movement tasks (walking, forward lunge, sideward lunge, ascent and descent stairs, single leg squat and sit-to-stand) were simultaneously recorded by the inertial sensor system and a camera-based motion analysis system. Statistically significant differences in angular waveforms of the trunk, pelvis and lower limb joints between HC and PwKOA were determined using one-dimensional statistical parametric mapping (SPM1D). The Knee injury and Osteoarthritis Outcome Score and TAMPA scale for Kinesiophobia were used to evaluate the relationship between discriminating joint motion, pain-related factors and disability using spearman's correlation coefficients. RESULTS: PwKOA had significantly less trunk rotation, internal pelvis rotation and knee flexion ROM during walking. Additionally, the reduced knee flexion (i.e. at the end of the stance phase and swing phase) was related to increased level of perceived pain. During the sideward lunge, PwKOA had significantly less knee flexion, ankle plantarflexion and hip abduction. This decreased hip abduction (i.e. during stance) was related to higher fear of movement. Finally, PwKOA had significantly less knee flexion during the forward lunge, single leg squat and during ascent and descent stairs. No significant correlations were observed with disability. CONCLUSIONS: Inertial sensors were able to discriminate between movement characteristics of PwKOA and HC. Additionally, significant relationships were found between joint motion, perceived pain and fear of movement. Since inertial sensors can be used outside the laboratory setting, these results are promising as they indicate the ability to evaluate movement deviations. Further research is required to enable measurements of small movement deviations in clinically relevant tasks.

Neurophysiological assessment of joint nociceptors in the rat medial meniscus transection model of post-traumatic osteoarthritis.

OBJECTIVE: Meniscal injury is a common prelude to post-traumatic osteoarthritis (PTOA). Joint nerves can become damaged in arthritic joints leading to the manifestation of neuropathic pain. Both PTOA and neuropathic pain are more common in females; however, it is unknown whether the neural processing of joint pain is sex-specific. DESIGN: Male and female Wistar rats (230-286g) underwent unilateral medial meniscus transection (MMT) and allowed to recover for 28 days. Pain development was assessed over the time course by von Frey hair algesiometry and dynamic weight bearing. Recordings from joint primary afferents was carried out by electrophysiology at end-stage disease. Nerve damage and ß-endorphin levels were also compared between MMT and sham operated animals. RESULTS: Male MMT rats exhibited significant pain behaviour compared to sham control. Evoked afferent firing rate was heightened in male MMT animals. Female PTOA rats did not show signs of pain behaviour on each of the test days and the neurophysiological properties of their nociceptors was not different from control. Peripheral neuropathy was observed in about 30% of axons from male MMT animals compared to 15% in females. Systemic ß-endorphin levels in female PTOA rats was 91.0 ± 10.4 pg/mL and only 49.0 ± 5.0 pg/mL in males. CONCLUSIONS: Secondary allodynia and joint pain were observed in male but not female MMT rats. Joint nociceptors were sensitized in PTOA males but not in females. This lack of pain in females may be due to the absence of a peripheral neuropathy and greater endogenous opioid production.

Health Demands Moderate the Link Between Willpower Beliefs and Physical Activity in Patients with Knee Osteoarthritis.

BACKGROUND: Regular physical activity (PA) was found to alleviate pain and improve functioning among patients with osteoarthritis of the knee (OAK). Heightened health demands due to OAK severity, body mass index (BMI), and depressive symptoms may require self-regulatory strategies to engage in more PA. Research on willpower-the capacity to exert self-control-suggests that believing that willpower is a nonlimited rather than a limited resource predicts effective self-regulation specifically when demands are high. The present study examines the association of OAK patients' willpower beliefs with their daily PA as a function of health demands. METHODS: To identify the moderating role of OAK severity (WOMAC), BMI, and depressive symptoms (CES-D) on the link between willpower beliefs and objectively assessed PA over a 7-day period, baseline data of a registered randomized controlled trial with 243 patients (Mage = 65.47 years, SD = 0.49) were examined in secondary analyses. RESULTS: Moderation analyses revealed that overall positive associations of willpower beliefs with PA were further qualified by OAK severity, BMI, and depressive symptoms. When patients faced less health demands, believing that willpower is nonlimited was associated with more PA. When health demands were higher, willpower beliefs were not associated with PA. CONCLUSION: OAK patients' willpower beliefs were associated with PA. However, facing more health demands seemed to erase this beneficial link. Improving willpower beliefs by way of intervention may help to shed more light on predictive direction and ways to overcome barriers to regular physical activity.

A prospective double-blinded randomised control trial comparing robotic arm-assisted functionally aligned total knee arthroplasty versus robotic arm-assisted mechanically aligned total knee arthroplasty.

BACKGROUND: Total knee arthroplasty (TKA) with mechanical alignment (MA) aims to achieve neutral limb alignment in all patients, whereas TKA with functional alignment (FA) aims to restore native, patient-specific anatomy and knee kinematics by manipulating bone resections and fine-tuning implant positioning. The objective of this study is to determine the optimal alignment technique in TKA by comparing patient satisfaction, functional outcomes, implant survivorship, complications, and cost-effectiveness in MA TKA versus FA TKA. Robotic technology will be used to execute the planned implant positioning and limb alignment with high-levels of accuracy in all study patients. METHODS AND ANALYSIS: This prospective double-blinded randomised control trial will include 100 patients with symptomatic knee osteoarthritis undergoing primary robotic arm-assisted TKA. Following informed consent, patients will be randomised to MA TKA (the control group) or FA TKA (the investigation group) at a ratio of 1:1 using an online random number generator. Blinded observers will review patients at regular intervals for 2 years after surgery to record predefined study outcomes relating to postoperative rehabilitation, clinical progress, functional outcomes, accuracy of implant positioning and limb alignment, gait, implant stability, cost-effectiveness, and complications. A superiority study design will be used to evaluate whether FA TKA provides superior outcomes compared to MA TKA. Primary and secondary objectives will be used to quantify and draw inferences on differences in the efficacy of treatment between the two groups. Intention-to-treat and per-protocol population analysis will be undertaken. The following statistical methods will be employed to analyse the data: descriptive statistics, independent t test, paired t test, analysis of variance, Fisher exact test, chi-square test, and graphical displays. Ethical approval was obtained from the London-Surrey Research Ethics Committee, UK. The study is sponsored by University College London, UK. DISCUSSION: This is the first study to describe the use of robotic technology to achieve FA TKA, and the only existing clinical trial comparing robotic MA TKA versus robotic FA TKA. The findings of this study will enable an improved understanding of the optimal alignment technique in TKA for achieving high-levels of patient satisfaction, improving functional outcomes, increasing implant survivorship, improving cost-effectiveness, and reducing complications. REGISTRATION: Clinical Trials.gov, NCT04092153. Registered on 17 September 2019.

Deep learning risk assessment models for predicting progression of radiographic medial joint space loss over a 48-MONTH follow-up period.

OBJECTIVE: To develop and evaluate deep learning (DL) risk assessment models for predicting the progression of radiographic medial joint space loss using baseline knee X-rays. METHODS: Knees from the Osteoarthritis Initiative without and with progression of radiographic joint space loss (defined as ≥ 0.7 mm decrease in medial joint space width measurement between baseline and 48-month follow-up X-rays) were randomly stratified into training (1400 knees) and hold-out testing (400 knees) datasets. A DL network was trained to predict the progression of radiographic joint space loss using the baseline knee X-rays. An artificial neural network was used to develop a traditional model for predicting progression utilizing demographic and radiographic risk factors. A combined joint training model was developed using a DL network to extract information from baseline knee X-rays as a feature vector, which was further concatenated with the risk factor data vector. Area under the curve (AUC) analysis was performed using the hold-out test dataset to evaluate model performance. RESULTS: The traditional model had an AUC of 0.660 (61.5% sensitivity and 64.0% specificity) for predicting progression. The DL model had an AUC of 0.799 (78.0% sensitivity and 75.5% specificity), which was significantly higher (P < 0.001) than the traditional model. The combined model had an AUC of 0.863 (80.5% sensitivity and specificity), which was significantly higher than the DL (P = 0.015) and traditional (P < 0.001) models. CONCLUSION: DL models using baseline knee X-rays had higher diagnostic performance for predicting the progression of radiographic joint space loss than the traditional model using demographic and radiographic risk factors.