Multicenter Osteoarthritis Study Research Articles

Deep Learning for Predicting Progression of Patellofemoral Osteoarthritis Based on Lateral Knee Radiographs, Demographic Data, and Symptomatic Assessments.

In this study, we propose a novel framework that utilizes deep learning and attention mechanisms to predict the radiographic progression of patellofemoral osteoarthritis (PFOA) over a period of 7 years. This study included subjects (1,832 subjects, 3,276 knees) from the baseline of the Multicenter Osteoarthritis Study (MOST). Patellofemoral joint regions of interest were identified using an automated landmark detection tool (BoneFinder) on lateral knee X-rays. An end-to-end deep learning method was developed for predicting PFOA progression based on imaging data in a five-fold cross-validation setting. To evaluate the performance of the models, a set of baselines based on known risk factors were developed and analyzed using gradient boosting machine (GBM). Risk factors included age, sex, body mass index, and Western Ontario and McMaster Universities Arthritis Index score, and the radiographic osteoarthritis stage of the tibiofemoral joint (Kellgren and Lawrence [KL] score). Finally, to increase predictive power, we trained an ensemble model using both imaging and clinical data. Among the individual models, the performance of our deep convolutional neural network attention model achieved the best performance with an area under the receiver operating characteristic curve (AUC) of 0.856 and average precision (AP) of 0.431, slightly outperforming the deep learning approach without attention (AUC = 0.832, AP = 0.4) and the best performing reference GBM model (AUC = 0.767, AP = 0.334). The inclusion of imaging data and clinical variables in an ensemble model allowed statistically more powerful prediction of PFOA progression (AUC = 0.865, AP = 0.447), although the clinical significance of this minor performance gain remains unknown. The spatial attention module improved the predictive performance of the backbone model, and the visual interpretation of attention maps focused on the joint space and the regions where osteophytes typically occur. This study demonstrated the potential of machine learning models to predict the progression of PFOA using imaging and clinical variables. These models could be used to identify patients who are at high risk of progression and prioritize them for new treatments. However, even though the accuracy of the models were excellent in this study using the MOST dataset, they should be still validated using external patient cohorts in the future.

Head-to-head comparison of appropriate use criteria for knee arthroplasty: A multicenter cohort study

ObjectiveTo determine, in a head-to-head comparison, which of two RAND-based knee replacement appropriateness criteria is optimal based on comparison to an externally validated method of judging good versus poor outcome. DesignLongitudinal data from the Osteoarthritis Initiative (OAI) and the Multicenter Osteoarthritis Study (MOST) were combined to produce a dataset of 922 persons with knee arthroplasty, 602 of which had adequate data for RAND classification and had their surgery within one year prior to a study visit. Data were used to determine appropriateness classification (i.e., Appropriate, Inconclusive, Rarely Appropriate) using modified versions of the first-generation and second-generation Escobar system. Growth curve analyses and multivariable regression were used to compare the two systems. ResultsNeither system associated with the gold standard measure of good versus poor outcome. Distributions of appropriateness categories for the second-generation system were inconsistent with current evidence for knee arthroplasty outcome. For example, 16% of participants were classified as Appropriate and 64% as Rarely Appropriate for pain outcome. Distributions for the first-generation system aligned with current evidence. ConclusionThe first-generation modified version of the Escobar appropriateness system is superior to the newer version but neither version associated with our gold standard growth curve analyses. Both systems only differentiate between patient classification groups preoperatively and up to ten months following surgery. Reliance on appropriateness criteria to inform long-term outcome is not warranted.

Associations of pain sensitivity and conditioned pain modulation with physical activity: findings from the Multicenter Osteoarthritis Study (MOST)

ObjectiveIndividuals with chronic pain due to knee osteoarthritis (OA) are insufficiently physically active, and alterations of facilitatory and inhibitory nociceptive signaling are common in this population. Our objective was to examine the association of these alterations in nociceptive signaling with objective accelerometer-based measures of physical activity in a large observational cohort. DesignWe used data from the Multicenter Osteoarthritis Study (MOST). Measures of peripheral and central pain sensitivity included pressure pain threshold (PPT) at the knee and mechanical temporal summation (TS) at the wrist, respectively. The presence of descending pain inhibition was assessed by conditioned pain modulation (CPM). Physical activity was quantitatively assessed over 7-days using a lower back-worn activity monitor. Summary metrics included steps/day, activity intensity, and sedentary time. Linear regression analyses were used to evaluate the association of pain sensitivity and the presence of descending pain inhibition with physical activity measures. ResultsData from 1,873 participants was analyzed (55.9% female, age = 62.8±10.0 years). People having greater peripheral and central sensitivity showed lower step counts. CPM was not significantly related to any of the physical activity measures, and none of the exposures were significantly related to sedentary time. ConclusionsIn this cohort, greater peripheral and central sensitivity were associated with reduced levels of objectively-assessed daily step counts. Further research may investigate ways to modify or treat heightened pain sensitivity as a means to increase physical activity in older adults with knee OA.

Intra-Articular Mineralization on Computerized Tomography of the Knee and Risk of Cartilage Damage: The Multicenter Osteoarthritis Study.

Intra-articular (IA) mineralization may contribute to osteoarthritis (OA) structural progression. We studied the association of IA mineralization on knee computed tomography (CT) with cartilage damage worsening on knee magnetic resonance imaging (MRI), with a focus on location- and tissue-specific effects. Participants from the Multicenter Osteoarthritis Study with knee CT and MRI scans were included. Presence of IA mineralization on CT was defined as a Boston University Calcium Knee Score >0 anywhere in the knee. Cartilage worsening on MRI was defined as any increase in the MRI OA Knee Score, including incident damage. We evaluated the association of whole-knee, compartment-specific (ie, medial or lateral), and subregion-specific (ie, location-matched) IA mineralization at baseline with cartilage worsening at two years' follow-up in the corresponding locations using binomial regression with generalized estimating equations, adjusting for age, sex, and body mass index (BMI). We included 1,673 participants (mean age 60 years, 56% female, mean BMI 29). Nine percent had any IA mineralization in the knee, and 47.4% had any cartilage worsening on follow-up. Mineralization of any tissue in the knee, regardless of location, was not associated with MRI cartilage worsening. However, cartilage mineralization was associated with 1.39 (95% confidence interval 1.04-1.88) times higher risk of cartilage worsening in the same compartment, with similar results in subregion-specific analysis. CT-detected IA mineralization in the cartilage was associated with higher risk of MRI cartilage worsening in the same compartment and subregion over two years. These findings suggest potential localized, tissue-specific effects of IA mineralization on cartilage pathology in knee OA.

Gait alterations associated with worsening knee pain and physical function: a machine-learning approach with wearable sensors in the Multicenter Osteoarthritis Study.

The objective of this study is to identify gait alterations related to worsening knee pain, and to worsening physical function, using machine learning approaches applied to wearable-sensor derived data from a large observational cohort. Participants in the Multicenter Osteoarthritis Study (MOST) completed a 20-meter walk test wearing inertial sensors on their lower back and ankles. Parameters describing spatiotemporal features of gait were extracted from this data. We used an ensemble machine learning technique ("super learning") to optimally discriminate between those with and without worsening physical function and, separately, those with and without worsening pain over 2 years. We then used log-binomial regression to evaluate associations of the top ten influential variables selected with super-learning with each outcome. We also assessed whether the relation of altered gait with worsening function was mediated by changes in pain. Of 2324 participants, 29% and 24% had worsening knee pain and function over 2-years, respectively. From the super-learner, several gait parameters were found to be influential for worsening pain and for worsening function. After adjusting for confounders, greater gait asymmetry, longer average step length, and lower dominant frequency were associated with worsening pain, and lower cadence was associated with worsening function. Worsening pain partially mediated the association of cadence with function. We identified gait alterations associated with worsening knee pain and those associated with worsening physical function. These alterations could be assessed with wearable sensors in clinical settings. Further research should determine whether they might be therapeutic targets to prevent worsening pain and worsening function.

Association of long-term use of non-steroidal anti-inflammatory drugs with knee osteoarthritis: a prospective multi-cohort study over 4-to-5 years

This study examines the long-term impact of non-steroidal anti-inflammatory drugs (NSAIDs) on the progression of symptoms and structural deterioration of the joint in knee osteoarthritis. The study analyzes data from 4197 participants (8394 knees) across the Osteoarthritis Initiative (OAI), Multicenter Osteoarthritis Study (MOST), and Cohort Hip and Cohort Knee (CHECK) over 4-to-5 years. Adjustments were made for major covariates. We focussed on binary outcomes to assess the presence or absence of significant changes. We found that, relative to non-users, individuals using NSAIDs long-term were significantly more likely to experience aggravated symptoms exceeding the minimally clinically important difference, specifically, pain (OR: 2.04, 95% CI: 1.66–2.49), disability (OR: 2.21, 95% CI: 1.74–2.80), and stiffness (OR: 1.58, 95% CI: 1.29–1.93). Long-term users also faced a higher probability than non-users of having total knee replacement (OR: 3.13, 95% CI: 2.08–4.70), although no significant difference between long-term users and non-users was observed for structural deterioration in the knee joint (OR: 1.25, 95% CI: 0.94–1.65). While acknowledging the limitations of this study due to its observational design and the potential for bidirectional causality, these findings suggest that long-term NSAID use could accelerate the progression to total knee replacement by markedly exacerbating symptoms.

Radiomics analysis of patellofemoral joint improves knee replacement risk prediction: Data from the Multicenter Osteoarthritis Study (MOST)

ObjectiveKnee replacement (KR) is the last-resort treatment for knee osteoarthritis. Although radiographic evidence of tibiofemoral joint has been widely adopted for prognostication, patellofemoral joint has gained little attention and may hold additional value for further improvements. We aimed to quantitatively analyse patellofemoral joint through radiomics analysis of lateral view radiographs for improved KR risk prediction. DesignFrom the Multicenter Osteoarthritis Study dataset, we retrospectively retrieved the initial-visit lateral left knee radiographs of 2943 patients aged 50 to 79. They were split into training and test cohorts at a 2:1 ratio. A comprehensive set of radiomic features were extracted within the best-performing subregion of patellofemoral joint and combined into a radiomics score (RadScore). A KR risk score, derived from Kellgren-Lawrence grade (KLG) of tibiofemoral joint and RadScore of patellofemoral joint, was developed by multivariate Cox regression and assessed using time-dependent area under receiver operating characteristic curve (AUC). ResultsWhile patellofemoral osteoarthritis (PFOA) was insignificant during multivariate analysis, RadScore was identified as an independent risk factor (multivariate Cox p-value < 0.001) for KR. The subgroup analysis revealed that RadScore was particularly effective in predicting rapid progressor (KR occurrence before 30 months) among early- (KLG < 2) and mid-stage (KLG ​= ​2) patients. Combining two joints radiographic information, the AUC reached 0.89/0.87 for predicting 60-month KR occurrence. ConclusionsThe RadScore of the patellofemoral joint on lateral radiographs emerges as an independent prognostic factor for improving KR prognosis prediction. The KR risk score could be instrumental in managing progressive knee osteoarthritis interventions.

Essential Fatty Acids and Osteoarthritis.

Inflammation worsens joint destruction in osteoarthritis (OA) and aggravates pain. Although n-3 fatty acids reduce inflammation, different n-3 fatty acids have different effects on inflammation and clinical outcomes, with eicosapentaenoic acid (EPA) having the strongest effect. We examined whether specific essential fatty acid levels affected the development of OA. We studied participants from the Multicenter Osteoarthritis Study (MOST) at risk of developing knee OA. As part of MOST, participants were asked repeatedly about knee pain, and knee radiographs and magnetic resonance images (MRIs) were obtained. Using baseline fasting samples, we analyzed serum fatty acids with standard assays. After excluding participants with baseline OA, we defined two sets of cases based on their status through 60 months' follow-up: those developing incident radiographic OA and those developing incident symptomatic OA (knee pain and radiographic OA). Controls did not develop these outcomes. Additionally, we examined worsening of MRI cartilage damage and synovitis and worsening knee pain and evaluated the number of hand joints affected by nodules. In regression models, we tested the association of each OA outcome with levels of specific n-3 and n-6 fatty acids, adjusting for age, sex, body mass index, education, physical activity, race, baseline pain, smoking, statin use, and depressive symptoms. We studied 363 cases with incident symptomatic knee OA and 295 with incident radiographic knee OA. The mean age was 62 years (59% women). We found no associations of specific n-3 fatty acid levels, including EPA, or of n-6 fatty acid levels with incident OA (eg, for incident symptomatic knee OA, the odds ratio per SD increase in EPA was 1.0 [95% confidence interval 0.87-1.17]). Results for other OA outcomes also failed to suggest a protective effect of specific n-3 fatty acids with OA outcomes. We found no association of serum levels of EPA or of other specific n-3 fatty acids or n-6 fatty acids with risk of incident knee OA or other OA outcomes.

Assessing the association of epigenetic age acceleration with osteoarthritis in the Multicenter Osteoarthritis Study (MOST)

PurposeAdvancing age is one of the strongest risk factors for osteoarthritis (OA). DNA methylation-based measures of epigenetic age acceleration may provide insights into mechanisms underlying OA. MethodsWe analyzed data from the Multicenter Osteoarthritis Study (MOST) in a subset of 671 participants ages 45-69 years with no or mild radiographic knee OA. DNA methylation was assessed with the Illumina Infinium MethylationEPIC 850K array. We calculated predicted epigenetic age according to Hannum, Horvath, PhenoAge, and GrimAge epigenetic clocks, then regressed epigenetic age on chronological age to obtain the residuals. Associations between the residuals and knee, hand, and multi-joint OA were assessed using logistic regression, adjusted for chronological age, sex, clinical site, smoking status, and race. ResultsTwenty three percent met criteria for radiographic hand OA, 25% met criteria for radiographic knee OA, and 8% met criteria for multi-joint OA. Mean chronological age (SD) was 58.4 (6.7) years. Mean predicted epigenetic age (SD) according to Horvath, Hannum, PhenoAge, and GrimAge epigenetic clocks was 64.9 (6.4), 68.6 (5.9), 50.5 (7.7), and 67.0 (6.2), respectively. Horvath epigenetic age acceleration was not associated with an increased odds of hand OA, OR (95% CI)=1.03 (0.99-1.08), with similar findings for knee and multi-joint OA. We found similar magnitudes of associations for Hannum epigenetic age, PhenoAge, and GrimAge acceleration compared to Horvath epigenetic age acceleration. ConclusionsEpigenetic age acceleration as measured by various well-validated epigenetic clocks based on DNA methylation was not associated with increased risk of knee, hand, or multi-joint OA independent of chronological age.

Evaluation of a measure of end-stage knee osteoarthritis compared to total knee replacement: An observational study using multicohort data

ObjectivesTo determine if an end-stage knee osteoarthritis (esKOA) measure, based on symptomatic and radiographic criteria, can indicate progression to severe KOA earlier and with fewer research participants than total knee replacement (TKR). We employed both interventional and observational study designs as examples to estimate the required sample sizes. EsKOA in a knee was declared if either of the following two conditions were met: 1) moderate, intense, or severe symptoms of KOA indicated by pain and disability measurement and severe KOA indicated by radiographically-assessed knee structure; 2) intense or severe symptoms of KOA indicated by pain and disability measurement and frequent knee pain with mild or moderate KOA as indicated by radiographically-assessed knee structure. MethodsWe examined the association between weight loss from baseline to 2-to-2.5-year and 4-to-5-year follow-ups and the odds of esKOA and TKR in 5,593 participants (10,357 knees) from the Osteoarthritis Initiative (OAI) and the Multicenter Osteoarthritis Study (MOST). We also estimated the sample sizes needed for interventional and observational study designs to detect a 10, 20, or 50% reduction in the incidence of esKOA and TKR. ResultsThe association of weight loss with both esKOA and TKR was detected at the 4-to-5-year follow-up. However, at the 2-to-2.5-year follow-up, the association was detected for esKOA but not TKR. The required sample sizes for detecting associations of weight loss with the incidence of esKOA were 85% to 93% smaller than those for TKR at the 4-to-5-year and 2-to-2.5-year follow-ups, respectively. ConclusionThe esKOA measure enables shorter and smaller studies compared to using TKR as an outcome.

Relation of Intra-Articular Mineralization to Knee Pain in Knee Osteoarthritis: A Longitudinal Analysis in the MOST Study.

Intra-articular (IA) calcium crystal deposition is common in knee osteoarthritis (OA), but of unclear significance. It is possible that low-grade, crystal-related inflammation may contribute to knee pain. We examined the longitudinal relation of computed tomography (CT)-detected IA mineralization to the development of knee pain. We used data from the National Institutes of Health-funded longitudinal Multicenter Osteoarthritis Study. Participants had knee radiographs and bilateral knee CTs at baseline, and pain assessments every 8 months for 2 years. CT images were scored using the Boston University Calcium Knee Score. We longitudinally examined the relation of CT-detected IA mineralization to the risk of frequent knee pain (FKP), intermittent or constant knee pain worsening, and pain severity worsening using generalized linear mixed-effects models. We included 2,093 participants (mean age 61 years, 57% women, mean body mass index 28.8 kg/m2 ). Overall, 10.2% of knees had IA mineralization. The presence of any IA mineralization in the cartilage was associated with 2.0 times higher odds of having FKP (95% confidence interval [CI] 1.38-2.78) and 1.86 times more frequent intermittent or constant pain (95% CI 1.20-2.78), with similar results seen for the presence of any IA mineralization in the meniscus or joint capsule. A higher burden of IA mineralization anywhere within the knee was associated with a higher odds of all pain outcomes (odds ratio ranged from 2.14 to 2.21). CT-detected IA mineralization was associated with risk of having more frequent, persistent, and worsening knee pain over 2 years. Targeting IA mineralization may have therapeutic potential for pain improvement in knee OA.

Associations between anterior knee pain and 2-year patellofemoral cartilage worsening: The MOST study

Anterior knee pain (AKP) is associated with patellofemoral osteoarthritis (PFOA), but longitudinal studies are lacking. If AKP precedes PFOA, it may create an opportunity to identify and intervene earlier in the disease process. The purpose of this study was to examine the longitudinal relation of AKP to worsening patellofemoral (PF) cartilage over two years. Participants were recruited from the Multicenter Osteoarthritis Study, a longitudinal study of individuals with or at risk for knee osteoarthritis (OA). Exclusion criteria included bilateral knee replacements, arthritis other than OA, and radiographic PFOA. At baseline, participants completed a knee pain map questionnaire and underwent knee magnetic resonance imaging (MRI). Imaging was repeated at 2-year follow-up. Exposure was presence of frequent AKP. Outcome was worsening cartilage damage in the PF joint defined as increase in MRI Osteoarthritis Knee Score from baseline to 2 years. Log-binomial models were used to calculate risk ratios (RR). One knee from 1083 participants (age 56.7±6.6 years; body mass index 28.0±4.9kg/m2) was included. Frequent AKP and frequent isolated AKP were present at baseline in 14.5% and 3.6%, respectively. Frequent AKP was associated with an increased risk (RR: 1.78, 95% confidence interval: 1.21, 2.62) of 2-year worsening cartilage damage in the lateral PF compartment. No association was found between frequent AKP and worsening in the medial PF joint. Frequent AKP at baseline was associated with worsening cartilage damage in the lateral PF joint over 2 years.

Exploring different models of pain phenotypes and their association with pain worsening in people with early knee osteoarthritis: The MOST cohort study

To determine i) pain phenotypes (PP) in people with early-stage knee osteoarthritis (EKOA); ii) the longitudinal association between the phenotypes and pain worsening at two years. We studied participants with EKOA from the Multicenter Osteoarthritis Study defined as pain intensity ≤3/10, Kellgren and Lawrence grade ≤2, intermittent pain none to sometimes, and no constant pain. Two models of PP were explored. Model A included pressure pain thresholds, temporal summation, conditioned pain modulation, pain catastrophizing, sleep quality, depression, and widespread pain (WSP). In Model B, gait characteristics, quadriceps strength, comorbidities, and magnetic resonance imaging features were added to Model A. Latent Class Analysis was used to create phenotypes, and logistic regression was used to determine their association with pain worsening. 750 individuals (60% females), mean age [standard deviation (SD)]: 60.3 (9.4) were included in Model A and 333 individuals (60% females), mean age (SD): 59.4 (8.1) in Model B. 3-class and 4-class solutions were chosen for Model A and Model B. In Model A, the most "severe" phenotype was dominated by psychosocial factors, WSP, and measures of nervous system sensitization. Similarly in Model B, the Model A phenotype plus gait variables, quadriceps strength, and comorbidities were dominant. Surprisingly, none of the phenotypes in either model had a significant relationship with pain worsening. Phenotypes based upon various factors thought to be important for the pain experience were identified in those with EKOA but were not significantly related to pain worsening. These phenotypes require validation with clinically relevant endpoints.

A discriminative shape-texture convolutional neural network for early diagnosis of knee osteoarthritis from X-ray images.

Knee Osteoarthritis (OA) is one of the most common causes of physical disability worldwide associated with a significant personal and socioeconomic burden. Deep Learning approaches based on Convolutional Neural Networks (CNNs) achieved remarkable improvements in knee OA detection. Despite this success, the problem of early knee OA diagnosis from plain radiographs remains a challenging task. This is due to the high similarity between the X-ray images of OA and non-OA subjects and the disappearance of texture information regarding bone microarchitecture changes in the top layers during the learning process of the CNN models. To address these issues, we propose a Discriminative Shape-Texture Convolutional Neural Network (DST-CNN), which automatically diagnoses early knee OA from X-ray images. The proposed model incorporates a discriminative loss to improve class separability and deal with high inter-class similarities. In addition, a new Gram Matrix Descriptor (GMD) block is embedded in the CNN architecture to compute texture features from several intermediate layers and combine them with the shape features in the top layers. We show that merging texture features with deep ones leads to better prediction of the early stages of OA. Comprehensive experimental results on two large public databases, Osteoarthritis Initiative (OAI) and Multicenter Osteoarthritis Study (MOST) demonstrate the potential of the proposed network. Ablation studies and visualizations are provided for a detailed understanding of our proposed approach.

Exploring pain phenotypes in people with early knee osteoarthritis:the multicenter osteoarthritis study (most)

Exploring pain phenotypes in people with early knee osteoarthritis:the multicenter osteoarthritis study (most)

Prevalence of intra-articular mineralization on knee computed tomography: the multicenter osteoarthritis study

The aim of this work was to report the prevalence of computed tomography (CT)-detected intra-articular mineralization. We included participants from the Multicenter Osteoarthritis (MOST) Study. At the 12th year visit of the MOST study, bilateral knee CTs were first obtained. All participants also had posteroanterior and lateral radiographs of bilateral knees and completed standard questionnaires. Knee radiographs were assessed for Kellgren & Lawrence grade (KLG) and radiographic evidence of intra-articular mineralization. CT images were scored using the Boston University Calcium Knee Score (BUCKS) for cartilage, menisci, ligaments, capsule, and vasculature. Prevalence of intra-articular mineralization was computed for the total sample, and stratified by age, sex, race, BMI, presence of frequent knee pain, and KLG. We also determined distribution of mineralization in the cartilage and meniscus, and co-localization. 4140 bilateral knees from 2070 participants were included (56.7% female, mean age 61.1 years, mean BMI: 28.8 kg/m2). On radiographs 240 knees (5.8%) had intraarticular mineralization, while CT-detected mineralization was present in 9.8% of knees. Prevalence of hyaline articular and meniscus mineralization increased with age and KL grade, and was similar by sex, BMI categories, and comparable in subjects with and without frequent knee pain. Mineralization tended to be ubiquitous in the joint, most commonly involving all three (medial/lateral tibiofemoral and patellofemoral) compartments (3.1%), while the patellofemoral compartment was the most involved compartment in isolation (1.4%). CT of the knee provides greater visualization of intra-articular mineralization than radiographs and allows better localization of the crystal deposition within the joint. Further studies should focus on the co-localization of intra-articular crystal deposition and corresponding MRI-features of knee OA.

Relation of pain sensitization to self-reported and performance-based measures of physical functioning: the Multicenter Osteoarthritis (MOST) study

It is unclear if alterations in nociceptive signaling contribute to poor physical functioning in persons with knee osteoarthritis (OA). We aimed to characterize the relation of pain sensitization to physical functioning in persons with or at risk for knee OA, and determine if knee pain severity mediates these relationships. We used cross-sectional data from the Multicenter Osteoarthritis Study, a cohort study of persons with or at risk for knee OA. Pressure pain thresholds (PPTs) and temporal summation (TS) were assessed with quantitative sensory testing. Self-reported function was quantified with the Western Ontario and McMaster Universities Arthritis Index function subscale (WOMAC-F). Walking speed was determined during a 20-mwalk. Knee extension strength was assessed with dynamometry. Relations of PPTs and TS to functional outcomes were examined with linear regression. The mediating role of knee pain severity was assessed with mediation analyses. Among 1560 participants (60.5% female, mean age (SD) 67 (8), body mass index (BMI) 30.2 (5.5) kg/m2), lower PPTs and the presence of TS were associated with worse WOMAC-F scores, slower walking speeds, and weaker knee extension. The extent of mediation by knee pain severity was mixed, with the greatest mediation observed for self-report function and only minimally for performance-based function. Heightened pain sensitivity appears to be meaningfully associated with weaker knee extension in individuals with or at risk for knee OA. Relations to self-reported physical function and walking speed do not seem clinically meaningful. Knee pain severity differentially mediated these relationships.

Gait, physical activity and tibiofemoral cartilage damage: a longitudinal machine learning analysis in the Multicenter Osteoarthritis Study

ObjectiveTo (1) develop and evaluate a machine learning model incorporating gait and physical activity to predict medial tibiofemoral cartilage worsening over 2 years in individuals without advanced knee osteoarthritis and...

Post-surgical contributors to persistent knee pain following knee replacement: The Multicenter Osteoarthritis Study (MOST)

ObjectivePain persistence following knee replacement (KR) occurs in ∼20–30% of patients. Although several studies have identified preoperative risk factors for persistent post-KR pain, few have focused on post-KR contributing factors. We sought to determine whether altered nociceptive signaling and other peripheral nociceptive drivers present post-operatively contribute to post-KR pain. DesignWe included participants from the Multicenter Osteoarthritis Study who were evaluated ∼12 months after KR. We evaluated the relation of measures of pain sensitivity [pressure pain threshold (PPT), temporal summation (TS), and conditioned pain modulation (CPM)] and the number of painful body sites to post-KR WOMAC knee pain, and of the number of painful sites to altered nociceptive signaling using linear or logistic regression models, as appropriate. Results171 participants (mean age 69 years, 62% female) were included. TS was associated with worse WOMAC pain post-KR (β ​= ​0.77 95% CI:0.19–1.35) and reduced odds of achieving patient acceptable symptom state (aOR ​= ​0.54 95%CI:0.34–0.88). Inefficient CPM was also associated with worse WOMAC pain post-KR (β ​= ​1.43 95% CI:0.15–2.71). In contrast, PPT was not associated with these outcomes. The number of painful body sites present post-KR was associated with TS (β ​= ​0.05, 95% CI:0.01, 0.05). ConclusionsPost-KR presence of central sensitization and inefficient descending pain modulation was associated with post-KR pain. We also noted that presence of other painful body sites contributes to altered nociceptive signaling, and this may thus also contribute to the experience of knee pain post-KR. Our findings provide novel insights into central pain mechanisms and other peripheral pain sources contributing to post-KR persistent knee pain.

THE RELATIONSHIP BETWEEN KNEE JOINT ALIGNMENT, 3-D JOINT SPACE WIDTH AND SUBCHONDRAL BONE PARAMETERS IN INVIDUALS WITH RADIOGRAPHIC OSTEOARTHRITIS: A MOST INVESTIGATION

Joint alignment is an important factor in OA affecting how forces pass through the knee. The increasing use of weight bearing computed tomography (WBCT) in OA research has made the weight bearing stance an important consideration in 3-D imaging analysis, but its influence through biomechanics on the joint and subchondral bone is not fully understood. To investigate the relationship between knee joint alignment and 3-D joint parameters derived from joint space mapping of WBCT imaging in individuals with radiographic OA. WBCT of both knees was acquired at the 144-month visit of the Multicenter Osteoarthritis Study (MOST). Knees with a KLG ≥2 were included in the analysis, taking the side with higher KLG or averaging subsequent results from both sides if equal. Joint space mapping was performed to obtain the 3-D JSW distribution along with femoral (f) and tibial (t) subchondral bone thickness (ST) and trabecular attenuation (TA). Everyone's knee parameter maps were then transferred to a canonical joint surface. Alignment of the knee joint was measured as the angle between the central axis of the distal femur and proximal tibia in a coronal multiplanar reformat slab of the WBCT data: neutral alignment was set as zero with varus signed positive (figure part (a)). Statistical parametric mapping (SPM) was performed using a general linear model to test the dependence of each 3-D parameter distribution on alignment controlling for age, sex, mass, height, and joint space shape modes. SPM results were plotted on the canonical joint surface with unmasked regions representing a significance level of P<0.05. 136 knees were included in the analysis, 84 of which were females. Mean ± SD age was 66.4 ± 9.8 yrs; mass 85.3 ± 17.8 kg; height 1.69 ± 0.1 m. The distribution of radiographic grading was KL2 = 103; KL3 = 32; KL4 = 1. Mean alignment was 0.38 ± 3.80°. For each degree from valgus to varus, JSW was significantly narrower in the medial compartment and wider in the lateral compartment by up to 0.1 mm (figure part (d)). While TA was significantly greater by up to 10 AU in the medial femur (figure part (b)) and medial tibia (figure part (f)), there was up to 0.05 mm significantly thinner ST in the lateral femur (figure part (c)) and lateral tibia (figure part (e)). The opposite effects can be inferred for each degree towards valgus. The same analysis on KLG 0 and 1 knees in the same cohort (mean ± SD alignment 0.66 ± 2.94°) revealed no significant relationships. Subchondral bone plate and trabecular bone appear to behave differently in the medial and lateral compartments when considering knee joint alignment in individuals with OA. Greater subchondral trabecular bone attenuation was seen in the medial compartment with varus alignment, while greater subchondral bone plate thickness was seen in the lateral compartment with valgus alignment. Whether alignment is the cause or effect of OA and any altered biomechanics that may influence bone and joint space behaviour requires further investigation, but this study does establish that the forces associated with alignment appear to have different effects on subchondral bone in different compartments. National Institutes of Health, University of Kansas (R01AR071648), University of Iowa (U01AG18832) and University of California-San Francisco (U01AG19069). NS is a consultant for Integra BioLife, Trice Medical and Pacira Biosciences. TT has been a consultant for Curvebeam AI. The authors would like to thank participants and staff of the MOST study. CORRESPONDENCE ADDRESS: [email protected]