Predictors of Lumbar Spine Degeneration and Low Back Pain in the Community: The Johnston County Osteoarthritis Project

Objective: To determine the incidence and worsening of lumbar spine structure and low back pain (LBP) and whether they are predicted by demographic characteristics or clinical characteristics or appendicular joint osteoarthritis (OA). Methods: Paired baseline (2003–2004) and follow-up (2006–2010) lumbar spine radiographs from the Johnston County Osteoarthritis Project were graded for osteophytes (OST), disc space narrowing (DSN), spondylolisthesis, and presence of facet joint OA (FOA). Spine OA was defined as at least mild OST and mild DSN at the same level for any level of the lumbar spine. LBP, comorbidities, and back injury were self-reported. Weibull models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of spine phenotypes accounting for potential predictors including demographic characteristics, clinical characteristics, comorbidities, obesity, and appendicular OA. Results: Obesity was a consistent and strong predictor of incidence of DSN (HR 1.80 [95% CI 1.09–2.98]), spine OA (HR 1.56 [95% CI 1.01–2.41]), FOA (HR 4.99 [95% CI 1.46–17.10]), spondylolisthesis (HR 1.87 [95% CI 1.02–3.43]), and LBP (HR 1.75 [95% CI 1.19–2.56]), and worsening of DSN (HR 1.51 [95% CI 1.09–2.09]) and LBP (HR 1.51 [95% CI 1.12–2.06]). Knee OA was a predictor of incident FOA (HR 4.18 [95% CI 1.44–12.2]). Spine OA (HR 1.80 [95% CI 1.24–2.63]) and OST (HR 1.85 [95% CI 1.02–3.36]) were predictors of incidence of LBP. Hip OA (HR 1.39 [95% CI 1.04–1.85]) and OST (HR 1.58 [95% CI 1.00–2.49]) were predictors of LBP worsening. Conclusion: Among the multiple predictors of spine phenotypes, obesity was a common predictor for both incidence and worsening of lumbar spine degeneration and LBP

Inflammatory, Structural, and Pain Biochemical Biomarkers May Reflect Radiographic Disc Space Narrowing: The Johnston County Osteoarthritis Project

The purpose of this work is to determine the relationship between biomarkers of inflammation, structure, and pain with radiographic disc space narrowing (DSN) in community-based participants. A total of 74 participants (37 cases and 37 controls) enrolled in the Johnston County Osteoarthritis Project during 2006–2010 were selected. The cases had at least mild radiographic DSN and low back pain (LBP). The controls had neither radiographic evidence of DSN nor LBP. The measured analytes from human serum included N-cadherin, Keratin-19, Lumican, CXCL6, RANTES, IL-17, IL-6, BDNF, OPG, and NPY. A standard dolorimeter measured pressure-pain threshold. The coefficients of variation were used to evaluate inter- and intra-assay reliability. Participants with similar biomarker profiles were grouped together using cluster analysis. The binomial regression models were used to estimate risk ratios (RR) and 95% confidence intervals (CI) in propensity score-matched models. Significant associations were found between radiographic DSN and OPG (RR = 3.90; 95% CI: 1.83, 8.31), IL-6 (RR = 2.54; 95% CI: 1.92, 3.36), and NPY (RR = 2.06 95% CI: 1.62, 2.63). Relative to a cluster with low levels of biomarkers, a cluster representing elevated levels of OPG, RANTES, Lumican, Keratin-19, and NPY (RR = 3.04; 95% CI: 1.22, 7.54) and a cluster representing elevated levels of NPY (RR = 2.91; 95% CI: 1.15, 7.39) were significantly associated with radiographic DSN. Clinical Significance: These findings suggest that individual and combinations of biochemical biomarkers may reflect radiographic DSN. This is just one step toward understanding the relationships between biochemical biomarkers and DSN that may lead to improved intervention delivery

Modeling of the condyle elements within a biomechanical knee model

The development of a computational multibody knee model able to capture some of the fundamental properties of the human knee articulation is presented. This desideratum is reached by including the kinetics of the real knee articulation. The research question is whether an accurate modeling of the condyle contact in the knee will lead to reproduction of the complex combination of flexion/extension, abduction/adduction and tibial rotation ob-served in the real knee? The model is composed by two anatomic segments, the tibia and the femur, whose characteristics are functions of the geometric and anatomic properties of the real bones. The biomechanical model characterization is developed under the framework of multibody systems methodologies using Cartesian coordinates. The type of approach used in the proposed knee model is the joint surface contact conditions between ellipsoids, represent-ing the two femoral condyles, and points, representing the tibial plateau and the menisci. These elements are closely fitted to the actual knee geometry. This task is undertaken by con-sidering a parameter optimization process to replicate experimental data published in the lit-erature, namely that by Lafortune and his co-workers in 1992. Then, kinematic data in the form of flexion/extension patterns are imposed on the model corresponding to the stance phase of the human gait. From the results obtained, by performing several computational simulations, it can be observed that the knee model approximates the average secondary mo-tion patterns observed in the literature. Because the literature reports considerable inter-individual differences in the secondary motion patterns, the knee model presented here is also used to check whether it is possible to reproduce the observed differences with reasonable variations of bone shape parameters. This task is accomplished by a parameter study, in which the main variables that define the geometry of condyles are taken into account. It was observed that the data reveal a difference in secondary kinematics of the knee in flexion ver-sus extension. The likely explanation for this fact is the elastic component of the secondary motions created by the combination of joint forces and soft tissue deformations. The proposed knee model is, therefore, used to investigate whether this observed behavior can be explained by reasonable elastic deformations of the points representing the menisci in the model.Fundação para a Ciência e a Tecnologia (FCT) - PROPAFE – Design and Development of a Patello-Femoral Prosthesis (PTDC/EME-PME/67687/2006), DACHOR - Multibody Dynamics and Control of Hybrid Active Orthoses MIT-Pt/BSHHMS/0042/2008, BIOJOINTS - Development of advanced biological joint models for human locomotion biomechanics (PTDC/EME-PME/099764/2008)