Osteoarthritis Initiative Cohort Research Articles

Integrating Radiomics and Neural Networks for Knee Osteoarthritis Incidence Prediction.

Accurately predicting knee osteoarthritis (KOA) is essential for early detection and personalized treatment. We aimed to develop and test an MRI-based Joint Space Radiomic Model (JS-RM) to predict radiographic KOA incidence through neural networks by integrating meniscus and femorotibial cartilage radiomic features. In the Osteoarthritis Initiative cohort, knees without radiographic KOA at baseline but at high risk for radiographic KOA were included. Case knees developed radiographic KOA whereas control knees did not over 4-year. We randomly split the knees into development and test cohorts (D/T=8/2) and extracted features from baseline 3D-DESS-sequence MRI. Model performance was evaluated using an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity in both cohorts. Nine resident surgeons performed the reader experiment without/with the JS-RM aid. Our study included 549 knees in the development cohort (275 cases vs. 274 controls) and 137 knees in the test cohort (68 cases vs. 69 controls). In the test cohort, JS-RM had a favorable accuracy for predicting the radiographic KOA incidence with an AUC of 0.931 (95%CI: 0.876-0.963), a sensitivity of 84.4% (95%CI: 83.9%-84.9%), and a specificity of 85.6% (95%CI: 85.2%-86.0%). The mean specificity and sensitivity of resident surgeons through MRI reading in predicting radiographic KOA incidence were increased from 0.474 (95%CI: 0.333-0.614) and 0.586 (95%CI: 0.429-0.743) without the assistance of JS-RM to 0.874 (95%CI: 0.847-0.901) and 0.812 (95%CI: 0.742-0.881) with JS-RM assistance, respectively (p<.001). JS-RM integrating the features of the meniscus and cartilage showed improved predictive values in radiographic KOA incidence.

Considerations beyond spine pain: do different co-occurring lower body joint pains differentially influence physical function and quality of life ratings?

BackgroundPatients seeking medical care for back pain often have coexisting painful joints and the effects of different combinations and number of coexisting pain sites (hip, knee, foot/ankle) to back pain on physical function domains and quality of life rating are not yet established. The purpose of this study was to determine the differences in functional outcomes and QOL among individuals with back pain who have concurrent additional pain sites or no pain sites.MethodsData from the Osteoarthritis Initiative (OAI) cohort were used for this cross-sectional analysis. Men and women aged 45–79 years with back pain were binned into nine groups by presence or not of coexisting hip, knee, ankle/foot pain and combinations of these sites (N = 1,642). Healthy controls reported no joint pain. Main outcomes included Knee Injury and Osteoarthritis Outcome score (KOOS; quality of life and function-sports-and-recreation), Western Ontario McMaster Universities Osteoarthritis Index (WOMAC; Activities of Daily Living, Pain), Medical Outcomes Short Form-12 (SF-12) Physical Component score, and self-reported function in last 7–30 days (lifting 25-pound objects, housework). 20-m and 400-m walk times and gait speed and repeated chair rise test times were collected.ResultsCompared to back pain alone, pain at all five sites was associated with 39%—86% worse KOOS, WOMAC, and SF-12 scores (p < .0001). Back-Hip and Back-Knee did not produce worse scores than Back pain alone, but Back-Hip-Knee and Back-Knee-Ankle/Foot did. The 20-m, 400-m walk, and repeated chair times were worse among individuals with pain at all five sites. Additional hip and knee sites to back pain, but not ankle/foot, worsened performance-based walk times and chair rise scores.ConclusionsThe number and type of coexistent lower body musculoskeletal pain among patients with back pain may be associated with perceived and performance-based assessments. Management plans that efficiently simultaneously address back and additional coexistent pain sites may maximize treatment functional benefits, address patient functional goals in life and mitigate disability.

Dense Multi-Scale Graph Convolutional Network for Knee Joint Cartilage Segmentation.

In this paper, we propose a dense multi-scale adaptive graph convolutional network (DMA-GCN) method for automatic segmentation of the knee joint cartilage from MR images. Under the multi-atlas setting, the suggested approach exhibits several novelties, as described in the following. First, our models integrate both local-level and global-level learning simultaneously. The local learning task aggregates spatial contextual information from aligned spatial neighborhoods of nodes, at multiple scales, while global learning explores pairwise affinities between nodes, located globally at different positions in the image. We propose two different structures of building models, whereby the local and global convolutional units are combined by following an alternating or a sequential manner. Secondly, based on the previous models, we develop the DMA-GCN network, by utilizing a densely connected architecture with residual skip connections. This is a deeper GCN structure, expanded over different block layers, thus being capable of providing more expressive node feature representations. Third, all units pertaining to the overall network are equipped with their individual adaptive graph learning mechanism, which allows the graph structures to be automatically learned during training. The proposed cartilage segmentation method is evaluated on the entire publicly available Osteoarthritis Initiative (OAI) cohort. To this end, we have devised a thorough experimental setup, with the goal of investigating the effect of several factors of our approach on the classification rates. Furthermore, we present exhaustive comparative results, considering traditional existing methods, six deep learning segmentation methods, and seven graph-based convolution methods, including the currently most representative models from this field. The obtained results demonstrate that the DMA-GCN outperforms all competing methods across all evaluation measures, providing DSC=95.71% and DSC=94.02% for the segmentation of femoral and tibial cartilage, respectively.

Chondroitin Sulfate for Osteoarthritis – Is There a Risk for Cancer: an Analysis of Osteoarthritis Initiative Data

The aim of this study was to evaluate the association between chondroitin sulfate (CS) use and incidence of self-reported cancer during 6-year follow up in the publicly available Osteoarthritis Initiative (OAI) cohort participants.&#x0D; Materials and Methods: The current study included analysis of 6-year longitudinal data obtained from the OAI progression (n= 1390) and incidence (n = 3284) subcohorts that are publicly available at https://nda.nih.gov/oai/. The inclusion criteria for OAI were the following: age between 45 and 79 years for both subcohorts, symptomatic tibiofemoral knee osteoarthritis (OA) for the progression subcohort, and the presence of established or putative risk factors for incident knee OA for the incidence subcohort. The OAI participants were recruited and enrolled between February 2004 and May 2006 at four recruitment centres in the United States. This study received ethical approval from each recruitment centre. All participants provided written informed consent. To reduce the risk of bias, only participants who did not take CS at baseline were included in the analysis (a “new-user” design).&#x0D; Results: 570 (18%) new users of CS and 2597 (82%) CS non-users were compared. In the CS user group, 294 (51.6%) participants received CS for more than one year, 291 (33.5%) for more than 2 years, 123 (21.6%) for more than 3 years, and 60 (10.5%) for more than 4 years. None of the participants received CS for more than 5 years. CS users and non-users were of the same age, had similar male/female ratio, and similar body mass index. In the non-user group, there were more African-American participants and there were more current smokers. 160 (6.2%) and 37 (6.5%) cases of incident self-reported cancer in the non-users and user groups were identified. There was no association between the use of CS and incident self-reported cancer in the non-adjusted analyses. The adjustments for age, race and smoking status did not change the results.&#x0D; Conclusion: The results of the current study did not show an association between CS use and self-reported cancers. Considering the complex function of CS in the development and progression of malignant tumors, there is a need for further epidemiological studies evaluating CS effects on specific types of cancers and in different genetic backgrounds.

An interpretable knee replacement risk assessment system for osteoarthritis patients

ObjectiveKnee osteoarthritis (OA) is a complex disease with heterogeneous representations. Although it is modifiable to prevention and early treatment, there still lacks a reliable and accurate prognostic tool. Hence, we aim to develop a quantitative and self-administrable knee replacement (KR) risk stratification system for knee osteoarthritis (KOA) patients with clinical features. MethodA total of 14 baseline features were extracted from 9592 cases in the Osteoarthritis Initiative (OAI) cohort. A survival model was constructed using the Random Survival Forests algorithm. The prediction performance was evaluated with the concordance index (C-index) and average receiver operating characteristic curve (AUC). A three-class KR risk stratification system was built to differentiate three distinct KR-free survival groups. Thereafter, Shapley Additive Explanations (SHAP) was introduced for model explanation. ResultsKR incidence was accurately predicted by the model with a C-index of 0.770 (±0.0215) and an average AUC of 0.807 (±0.0181) with 14 clinical features. Three distinct survival groups were observed from the ten-point KR risk stratification system with a four-year KR rate of 0.79%, 5.78%, and 16.2% from the low, medium, and high-risk groups respectively. KR is mainly caused by pain medication use, age, surgery history, diabetes, and a high body mass index, as revealed by SHAP. ConclusionA self-administrable and interpretable KR survival model was developed, underscoring a KR risk scoring system to stratify KOA patients. It will encourage regular self-assessments within the community and facilitate personalised healthcare for both primary and secondary prevention of KOA.

Associations of inflammatory and metabolic biomarkers with incident erosive hand osteoarthritis in the osteoarthritis initiative cohort

Erosive hand osteoarthritis (eHOA) is a subtype of hand osteoarthritis (OA) that develops in finger joints with pre-existing OA and is differentiated by clinical characteristics (hand pain/disability, inflammation, and erosions) that suggest inflammatory or metabolic processes. This was a longitudinal nested case-cohort design among Osteoarthritis Initiative participants who had hand radiographs at baseline and 48-months, and biospecimens collected at baseline. We classified incident radiographic eHOA in individuals with ≥1 joint with Kellgren-Lawrence ≥2 and a central erosion present at 48-months but not at baseline. We used a random representative sample (n=1282) for comparison. We measured serum biomarkers of inflammation, insulin resistance and dysglycemia, and adipokines using immunoassays and enzymatic colorimetric procedures, blinded to case status. Eighty-six participants developed incident radiographic eHOA. In the multivariate analyses adjusted for age, gender, race, smoking, and body mass index, and after adjustment for multiple analyses, incident radiographic eHOA was associated with elevated levels of interleukin-7 (risk ratio (RR) per SD=1.30 [95% confidence interval (CI) 1.09, 1.55] p trend 0.01). This exploratory study suggests an association of elevated interleukin-7, an inflammatory cytokine, with incident eHOA, while other cytokines or biomarkers of metabolic inflammation were not associated. Interleukin-7 may mediate inflammation and tissue damage in susceptible osteoarthritic finger joints and participate in erosive progression.

Factors associated with trajectories of bone marrow lesions over 4years: data from the Osteoarthritis Initiative.

To identify bone marrow lesion (BML) trajectories over 4years and their demographic and structural predictors in middle-aged and older adults with or at increased risk of knee osteoarthritis (OA). A total of 614 participants (mean age 61years, 62% female) from the Osteoarthritis Initiative cohort (OAI) were included. BMLs in 15 anatomical locations of the knee were measured annually from baseline to 4years using the Magnetic Resonance Imaging Osteoarthritis Knee Score (MOAKS) method. BML trajectories were determined using latent class mixed models (LCMMs). Multinomial logistic regression was used to examine baseline characteristics that predicted BML trajectories. Three distinct BML trajectories were identified: "Mild-stable BMLs" (25.9%), "Moderate-stable BMLs" (66.4%), and "Rapid-rise BMLs" (7.7%). Compared to the "Mild-stable BMLs" trajectory, current smokers were more likely to be in the "Moderate-stable BMLs" (odds ratio [OR] 2.089, P < 0.001) and "Rapid-rise" (OR 2.462, P < 0.001) trajectories. Moreover, female sex and meniscal tears were associated with an increased risk of being in the "Rapid-rise BMLs" trajectory (OR 2.023 to 2.504, P < 0.05). Participants who had higher education levels and drank more alcohol were more likely to be in the "Rapid-rise BMLs" trajectory (OR 1.624 to 3.178, P < 0.05) and less likely to be in the "Moderate-stable BMLs" trajectory (OR 0.668 to 0.674, P < 0.05). During the 4-year follow-up, most participants had relatively stable BMLs, few had enlarged BMLs, and no trajectory of decreased BMLs was identified. Sociodemographic factors, lifestyle, and knee structural pathology play roles in predicting distinct BML trajectories.

Erosive hand osteoarthritis and sarcopenia: data from Osteoarthritis Initiative cohort

ObjectivesThere is no evidence linking specific osteoarthritis (OA) types, such as erosive hand OA (EHOA), with distant generalised changes in muscle composition (sarcopenia), which can potentially be modified. This study...

Thigh muscle and fat volumes are associated with knee cartilage abnormalities and bone marrow edema-like lesions: data from the osteoarthritis initiative.

To investigate the associations of thigh muscle and fat volumes with structural abnormalities on MRI related to knee osteoarthritis. MRI studies of the thighs and knees from 100 individuals were randomly selected from the Osteoarthritis Initiative Cohort. Whole Organ MR Scoring (WORMS) and effusion-synovitis scoring were performed in all knee MRI. Thigh muscles, intermuscular fat, and subcutaneous fat were manually segmented in 15 consecutive MR thigh images. Radiographic Kellgren-Lawrence grades (KLG) were also obtained in all knee radiographs. Independent t-tests were used to investigate the associations between thigh muscle and fat volumes, and sex. Mixed-effects analyses were obtained to investigate the associations between thigh muscle and fat volumes, KLG, WOMAC pain score, cartilage and bone marrow WORMS, as well as effusion-synovitis scores. Women had higher subcutaneous fat volume than men (616.82 vs. 229.13 cm3, p < 0.01) and men had higher muscle volumes than women (p < 0.01). Quadriceps (coef = -2.15, p = 0.01) and vastus medialis (coef = -1.84, p = 0.03) volumes were negatively associated with the WORMS cartilage scores. Intermuscular fat volume (coef = 0.48, p = 0.01) was positively associated with WORMS bone marrow edema-like lesion (BMEL) scores. The quadriceps (coef = -0.99, p < 0.01) and hamstring (coef = -0.59, p = 0.01) volumes were negatively associated with WORMS BMEL scores. No evidence of an association was found between thigh muscle and fat volumes with KLG and effusion-synovitis grading (p > 0.05). Increased quadriceps and hamstring volumes were negatively associated with cartilage lesion and BMEL scores while no evidence of an association was found between thigh muscle and fat volumes, and radiographic knee osteoarthritis or effusion-synovitis grading.

Association between niacin intake and knee osteoarthritis pain and function: a longitudinal cohort study.

This research investigates the relationship between niacin intake and knee osteoarthritis (OA) severity, focusing on pain and functional ability due to niacin's role as a NAD(P)+ precursor, promoting cellular energy, and offering anti-inflammatory, analgesic, and antioxidant effects. The population-based Osteoarthritis Initiative (OAI) cohort with radiographically confirmed knee OA was analyzed through a Food Frequency Questionnaire determining niacin intake and scores from the Knee Injury and Osteoarthritis Outcome Score (KOOS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), using generalized additive mixed models. A significant correlation was pinpointed in 2375 OA patients (1001 men and 1374 women; 55.96% aged between 45 and 65 and 44.04% aged ≥65) between niacin intake and reduced knee pain and functional degrees after a 48-month follow-up, evident in improved KOOS and WOMAC scores (P < 0.05). The fully adjusted models estimated a decrease of 0.26 points for every additional 1 unit of Ln-niacin intake of daily niacin intake on the WOMAC pain subscale, 0.83 points on the WOMAC function subscale, and an increase of 1.71 and 1.58 on the KOOS pain and quality of life score. Strikingly, subgroups including middle-aged individuals, women, white race, obese individuals, and those with specific dietary habits showed a more substantial improvement with increased niacin. The association between increased niacin intake and reduced pain and function scores, as well improved quality of life in knee OA patients, is significant. Certain cohorts, according to a stratified analysis, could see more considerable benefits with increased niacin consumption. • Increased niacin intake is linked to reduced knee pain and better function in OA patients. • Specific subgroups, such as middle-aged individuals, women, and those with certain dietary habits, benefit more from increased niacin consumption. • Niacin shows promise for enhancing the quality of life in knee OA patients by reducing pain and improving function.

Investigation of the Associations of Smoking With Hip Osteoarthritis: A Baseline Cross-Sectional and Four- to Five-Year Longitudinal Multicohort Study.

This study aimed to investigate the effect of smoking on the prevalence, incidence, and progression of hip osteoarthritis (OA). We used data from the Osteoarthritis Initiative (OAI) and the Cohort Hip and Cohort Knee (CHECK) studies. We analyzed 9,386 hips from 4,716 participants (OAI cohort) and 1,954 hips from 977 participants (CHECK cohort). The primary exposure was smoking status at baseline, categorized as current, former, or never smoker. Outcomes of radiographic hip OA (RHOA) and symptomatic hip OA were evaluated both cross-sectionally at baseline and longitudinally over a 4- to 5-year follow-up, with adjustments for major covariates. No significant differences were observed between current or former smokers and never smokers for any of the outcomes examined, either at baseline or at the 4- to 5-year follow-up. In the cross-sectional analysis, the odds ratios with 95% confidence intervals for the prevalence of RHOA for current and former smokers were 1.29 (0.68-2.46) and 0.99 (0.70-1.40) in the OAI cohort and 1.38 (0.78-2.44) and 0.85 (0.54-1.32) in the CHECK cohort, respectively. In the longitudinal analysis, odds ratio with 95% confidence intervals for the incidence of RHOA were 1.03 (0.23-4.50) and 0.92 (0.46-1.85) in the OAI cohort and 0.61 (0.34-1.11) and 1.00 (0.69-1.44) in the CHECK cohort, respectively. Our study found no clear association between smoking and the prevalence, incidence, or progression of RHOA or symptomatic hip OA, either at baseline or over a 4- to 5-year period.

Short-term variations in trabecular bone texture parameters associated to radio-clinical biomarkers improve the prediction of radiographic knee osteoarthritis progression

The present study aims to examine whether the short-term variations in trabecular bone texture (TBT) parameters, combined with a targeted set of clinical and radiographic data, would improve the prediction of long-term radiographic knee osteoarthritis (KOA) progression. Longitudinal (baseline, 24 and 48-month) data, obtained from the Osteoarthritis Initiative cohort, were available for 1352 individuals, with preexisting OA (1 < Kellgren–Lawrence < 4) at baseline. KOA progression was defined as an increase in the medial joint space narrowing score from the 24-months to the 48-months control point. 16 regions of interest were automatically selected from each radiographic knee and analyzed using fractal dimension. Variations from baseline to 24 months in TBT descriptors as well as selected radiographic and clinical readings were calculated. Different logistic regression models were developed to evaluate the progression prediction performance when associating TBT variations with the selected clinical and radiographic readings. The most predictive model was mainly determined using the area under the receiver operating characteristic curve (AUC). The proposed prediction model including short-term variations in TBT parameters, associated with clinical covariates and radiographic scores, improved the capacity of predicting long-term radiographic KOA progression (AUC of 0.739), compared to models based solely on baseline values (AUC of 0.676, p-value < 0.008).

Anterior knee pain as a potential risk factor for falls in older adults: insights from the osteoarthritis initiative data

BackgroundKnee joint pain has been demonstrated to be a separate risk factor for falling. A common pain site in the knee, anterior knee pain(AKP), is believed to be associated with early knee osteoarthritis (KOA).This study investigated the relationship between falls and AKP in people with or at risk for KOA.MethodsFour years of follow-up data from the Osteoarthritis Initiative cohort trial, a large-scale, multicenter observational investigation, were analyzed in this study. A patellar quadriceps tenderness/tendinitis knee exam was performed to evaluate AKP. Falls were self-reported. The associations between falls (recurrent falls: ≥2 falls/year; any falls: ≥1 fall(s)/year) and AKP were analyzed using the generalized estimation equation of repeated logistic regression and adjusted for confounding variables.ResultsThe study analyzed data from 3,318 participants, split into two groups: those with AKP (720 participants) and those without AKP (2,598 participants). The primary outcome of the study, which focused on repeated falls, revealed that participants with AKP were 1.27 times more likely to experience repeated falls compared to those without AKP (95% CI: 1.07–1.52, P = 0.007). However, when considering any falls experienced by an individual as an additional outcome, it is important to note that our findings did not indicate a significant predictive effect of AKP on any falls investigated. Sensitivity analyses, which excluded knee arthroplasty cases, yielded consistent results with the aforementioned findings.ConclusionsOlder adults with AKP experience a higher frequency of falls compared to those without AKP in individuals diagnosed with KOA or at a high risk of developing KOA.

Association of smoking with cartilage loss of knee osteoarthritis: data from two longitudinal cohorts

BackgroundPrevious studies have been inconsistent concerning the association between smoking and risk of osteoarthritis (OA). This study aimed to explore the associations of smoking status and change in cartilage volume of OA in two longitudinal cohorts.MethodsSubjects from the Osteoarthritis Initiative cohort (OAI, n = 593) and the Tasmanian Older Adult Cohort (TASOAC, n = 394) were included in this study. For both cohorts, participants were classified into three groups based on their smoking status, namely ‘never’, ‘former’, and ‘current’ smokers. The outcome measures were the annual rate of change of tibiofemoral cartilage volume over 2 years in OAI and of tibial cartilage volume over 2.6 years in TASOAC. Potential confounders were balanced using the inverse probability of treatment weighting (IPTW) method.ResultsOverall, 42.3% and 37.4% of participants were former smokers, and 5.7% and 9.3% were current smokers in the OAI and TASOAC cohorts, respectively. Compared to never smokers, neither former nor current smoking was associated with risk of the annual rate of change of tibiofemoral cartilage volume in OAI (former smoker: β=-0.068%/year, 95% confidence interval [CI] -0.824 to 0.688, p = 0.860; current smoker: β=-0.222%/year, 95% CI -0.565 to 0.120, p = 0.204) and tibial cartilage volume in TASOAC (former smoker: β = 0.001%/year, 95% CI -0.986 to 0.989, p = 0.998; current smoker: β=-0.839%/year, 95% CI -2.520 to 0.844, p = 0.329).ConclusionsOur findings from two independent cohorts consistently showed that smoking was not associated with knee cartilage loss in older adults.

Weight-cycling over 6 years is associated with pain, physical function and depression in the Osteoarthritis Initiative cohort

Body weight significantly impacts health and quality of life, and is a leading risk factor for the development of knee osteoarthritis (OA). Weight cycling may have more negative health consequences compared to steady high or low weight. Using the Osteoarthritis Initiative dataset, we investigated the effects of weight cycling on physical function, quality of life, and depression over 72-months compared to stable or unidirectional body weight trajectories. Participants (n = 731) had knee OA and were classified as: (1) stable-low (BMI < 25), (2) stable-overweight (BMI = 25–29.9), and (3) stable-obese (BMI ≥ 30); (4) steady-weight-loss; (5) steady-weight-gain (weight loss/gain ≥ 2.2 kg every 2-years); (6) gain–loss–gain weight cycling, and (7) loss–gain–loss weight cycling (weight loss/gain with return to baseline), based on bi-annual assessments. We compared Knee Injury and Osteoarthritis Outcome Knee-Related Quality of Life, Function in Sports and Recreation, Physical Activity in the Elderly, Short Form SF-12, repeated chair rise, 20-m gait speed, and Center for Epidemiological Studies Depression using repeated-measures ANOVA. The steady weight loss group demonstrated the worst pain, physical function, and depressive symptoms over time (p’s < 0.05). More research is needed to confirm these findings, and elucidate the mechanisms by which steady weight loss is associated with functional decline in knee OA.

Frailty predicts knee pain trajectory over 9 years: results from the Osteoarthritis Initiative.

Frailty is a multisystem syndrome and its relationship with symptomatic osteoarthritis has been reported. We aimed to identify trajectories of knee pain in a large prospective cohort and to describe the effect of frailty status at baseline on the pain trajectories over 9 years. We included 4419 participants (mean age 61.3 years, 58% female) from the Osteoarthritis Initiative cohort. Participants were classified as "no frailty," "pre-frailty," or "frailty" at baseline, based on 5 characteristics (ie, unintentional weight loss, exhaustion, weak energy, slow gait speed, and low physical activity). Knee pain was evaluated annually using the Western Ontario and McMaster Universities Osteoarthritis Index pain subscale (0-20) from baseline to 9 years. Of the participants included, 38.4%, 55.4%, and 6.3% were classified as "no frailty," "pre-frailty," and "frailty," respectively. Five pain trajectories were identified: "No pain" (n = 1010, 22.8%), "Mild pain" (n = 1656, 37.3%), "Moderate pain" (n = 1149, 26.0%), "Severe pain" (n = 477, 10.9%), and "Very Severe pain" (n = 127, 3.0%). Compared to participants with no frailty, those with pre-frailty and frailty were more likely to have more severe pain trajectories (pre-frailty: odds ratios [ORs] 1.5 to 2.1; frailty: ORs 1.5 to 5.0), after adjusting for potential confounders. Further analyses indicated that the associations between frailty and pain were mainly driven by exhaustion, slow gait speed, and weak energy. Approximately two-thirds of middle-aged and older adults were frail or pre-frail. The role of frailty in predicting pain trajectories suggests that frailty may be an important treatment target for knee pain.

Asymmetric Flexion Contracture is Associated With Leg Length Inequality in Patients With Knee Osteoarthritis: Data From the Osteoarthritis Initiative

ObjectiveTo evaluate whether knee flexion contracture (FC) was associated with leg length inequality (LLI) and/or morbidity in knee osteoarthritis (OA). DesignWe accessed 2 databases: (1) the Osteoarthritis Initiative (OAI) cohort, including participants with, or at-risk of OA, and (2) the Ottawa Knee Osteoarthritis cross-sectional database (OKOA), including participants with primary advanced knee OA. Both included demographics, radiographic data, knee range of motion, leg length, pain, and function scales. SettingTertiary care academic rheumatology and orthopedic clinics. ParticipantsPatients with or at-risk of primary OA. We included 881 OAI and 72 OKOA participants (N=953). InterventionNot applicable. Main Outcome MeasuresThe primary outcome tested the association between the difference in knee extensions of the OA and contralateral knees (the knee extension difference, or KExD) and LLI. This was evaluated using bivariate regression, followed by a multivariable linear regression model. ResultsOAI participants had less severe knee OA [Kellgren and Lawrence (KL) score 1.9±1.3] vs OKOA (KL score 3.4±0.6). The KExD correlated with LLI for both databases (OAI: R=0.167; P≤.001; OKOA: R=0.339; P=.004). Multivariable regression showed an effect of KExD on LLI in both databases (OAI: β=0.37[0.18,0.57]; P<.001, OKOA: β=0.73[0.20,1.26]; P=.007). When broken down by subgroup, the OAI moderate-severe OA group showed a significant effect of KExD on LLI (β=0.60 [0.34,0.85]; P<.001). ConclusionsOA-related loss of knee extension was associated with LLI for those with moderate-severe OA. Because LLI correlates with worse knee OA symptoms, discovering an FC should cue clinicians to evaluate for LLI, an easily-treatable finding that may help reduce OA-associated morbidity for those approaching the need for arthroplasty.

Association of Sleep Disturbance With Catastrophizing and Knee Pain: Data From the Osteoarthritis Initiative.

To investigate the relationship between sleep disturbance, catastrophizing, and knee pain in middle-aged and older individuals. Data from the Osteoarthritis Initiative cohort from months 48 to 96 were used, where month 48 was treated as baseline. Knee pain (Western Ontario and McMaster Universities Osteoarthritis Index pain scale score ≥5 [range 0-20]), catastrophizing (extracted from Coping Strategies Questionnaire score ≥3 [range 0-6]), and sleep quality (extracted from Center for Epidemiologic Studies Depression Scale [range 1-4]) were assessed annually. We described the association of sleep disturbance with the presence and risk of knee pain and catastrophizing. The mediation effect of knee pain and catastrophizing on the sleep-catastrophizing and sleep-pain association was evaluated, respectively. Catastrophizing and knee pain were reported in 346 (10%) and 917 (24%) of the 3,813 participants (mean 64.9 years, 58% female) at baseline. Participants with worse sleep disturbance were more likely to have knee pain (prevalence ratio [PR] 1.4-2.0, P for trend <0.001) and catastrophizing (PR 1.4-3.1, P for trend <0.001). Sleep disturbance at baseline predicted the risk of knee pain (risk ratio [RR] 1.1, P for trend <0.001) and catastrophizing (RR 1.2-1.7, P for trend <0.001) during follow-up. No statistically significant interactions between sleep disturbance and knee pain or catastrophizing were observed. Knee pain and catastrophizing mediated the sleep-catastrophizing and sleep-pain association, respectively, at baseline, and knee pain negatively mediated the sleep-catastrophizing association longitudinally. Sleep disturbance was associated with the presence and risk of catastrophizing and knee pain. Sleep interventions may have a universal and independent effect in preventing incident knee pain.

Socioeconomic status, mental health, and nutrition are the principal traits for low back pain phenotyping: Data from the osteoarthritis initiative.

Low back pain (LBP) is a heterogeneous disease with biological, physical, and psychosocial etiologies. Models for predicting LBP severity and chronicity have not made a clinical impact, perhaps due to difficulty deciphering multidimensional phenotypes. In this study, our objective was to develop a computational framework to comprehensively screen metrics related to LBP severity and chronicity and identify the most influential. We identified individuals from the observational, longitudinal Osteoarthritis Initiative cohort (N= 4796) who reported LBP at enrollment (N= 215). OAI descriptor variables (N= 1190) were used to cluster individuals via unsupervised learning and uncover latent LBP phenotypes. We also developed a dimensionality reduction algorithm to visualize clusters/phenotypes using Uniform Manifold Approximation and Projection (UMAP). Next, to predict chronicity, we identified those with acute LBP (N= 40) and persistent LBP over 8 years of follow-up (N= 66) and built logistic regression and supervised machine learning models. We identified three LBP phenotypes: a "high socioeconomic status, low pain severity group", a "low socioeconomic status, high pain severity group", and an intermediate group. Mental health and nutrition were also key clustering variables, while traditional biomedical factors (e.g., age, sex, BMI) were not. Those who developed chronic LBP were differentiated by higher pain interference and lower alcohol consumption (a correlate to poor physical fitness and lower soceioeconomic status). All models for predicting chronicity had satisfactory performance (accuracy 76%-78%). We developed a computational pipeline capable of screening hundreds of variables and visualizing LBP cohorts. We found that socioeconomic status, mental health, nutrition, and pain interference were more influential in LBP than traditional biomedical descriptors like age, sex, and BMI.

Risk factors for the long-term incidence and progression of knee osteoarthritis in older adults: role of nonsurgical injury.

For one of the most chronic medical conditions, osteoarthritis, uncertainties remain on the impact of injury chronology, the role of repeat injury on the incidence/progression of this disease and the need for knee arthroplasty. To explore, in an older adult population, how nonsurgical knee injuries relate to osteoarthritis incidence/progression and the weight of independent risk factors for arthroplasty. A cohort study design evaluates the long-term impact of injuries on knee osteoarthritis outcomes. Knees with no prior injury (n = 6358) and with at least one injury (n = 819) ⩽20 years before study inclusion were from the Osteoarthritis Initiative cohort. Sociodemographic, clinical and structural [X-ray, magnetic resonance imaging (MRI)] data at study inclusion and changes within 96 months were analysed. Statistics included a mixed model for repeated measurements, generalized estimating equations and multivariable Cox regression with covariates. At inclusion, knees with prior injury demonstrated greater incidence and severity of osteoarthritis (p ⩽ 0.001). At 96 months, there was a greater increase in symptoms [Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, p = 0.002], joint space width (JSW, p = 0.039) loss, medial cartilage volume loss (CVL, p ⩽ 0.001) and bone marrow lesion size (BML, p ⩽ 0.049). Knees with/without injury at inclusion but with new ones over time had a pronounced increase in symptoms (all WOMAC scores, p ⩽ 0.001), JSW loss, lateral (without) and medial CVL, lateral (without) and medial meniscal extrusion and medial BML (without; all p ⩽ 0.030). Levels of lateral and medial meniscal extrusion (without) and symptoms (with/without; all WOMAC scores, p ⩽ 0.001) were all accentuated with a repeated new injury. Risk factors associated with the highest knee arthroplasty occurrence are new meniscal extrusion and new injury (p ⩽ 0.001). This study highlights the importance of nonsurgical knee injury in older adults as an independent risk factor for knee osteoarthritis and arthroplasty. These data will be beneficial in clinical practice as they will help identify individuals at greater risk of significant disease progression and worst disease outcomes for a customized therapeutic approach.