Absence of pain in subjects with advanced radiographic knee osteoarthritis

Background To investigate the frequency of pain among subjects with advanced radiographic knee osteoarthritis (OA) defined as Kellgren–Lawrence (KL) grade 4 and clinical features associated with pain. Methods Subjects from the Hallym Aging Study (HAS), the Korean National Health and Nutrition Examination Survey (KNHANES), and the Osteoarthritis Initiative (OAI) were included. Participants were asked knee-specific questions regarding the presence of knee pain. Clinical characteristics associated with the presence of pain were evaluated with multivariable logistic regression analysis. Results The study population consisted of 504, 10,152 and 4796 subjects from HAS, KNHANES, and OAI, respectively. KL grade 4 OA was identified in 9.3, 7.6, and 11.5% of subjects, while pain was absent in 23.5, 31.2, and 5.9% of subjects in KL grade 4 knee OA, respectively. After multivariable analysis, female gender showed a significant association with pain in the KNHANES group, while in the OAI group, younger age did. Advanced knee OA patients without pain did not differ from non-OA subjects in most items of SF-12 in both Korean and OAI subjects. Total WOMAC score was not significantly different between non-OA and advanced knee OA subjects without pain in the OAI. Conclusions Our study showed that a considerable number of subjects with KL grade 4 OA did not report pain. In patients whose pain arises from causes other than structural damage of the joint, therapeutic decision based on knee X-ray would lead to suboptimal result. In addition, treatment options focusing solely on cartilage engineering, should be viewed with caution.This work was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI16C0287), a grant of the Basic Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Education (2017R1A2B2001881), and Hallym University research fun

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Advances in Imaging of Osteoarthritis and Cartilage

Osteoarthritis (OA) is the most frequent form of arthritis, with major implications for individual and public health care without effective treatment available. The field of joint imaging, and particularly magnetic resonance (MR) imaging, has evolved rapidly owing to technical advances and the application of these to the field of clinical research. Cartilage imaging certainly is at the forefront of these developments. In this review, the different aspects of OA imaging and cartilage assessment, with an emphasis on recent advances, will be presented. The current role of radiography, including advances in the technology for joint space width assessment, will be discussed. The development of various MR imaging techniques capable of facilitating assessment of cartilage morphology and the methods for evaluating the biochemical composition of cartilage will be presented. Advances in quantitative morphologic cartilage assessment and semiquantitative whole-organ assessment will be reviewed. Although MR imaging is the most important modality in imaging of OA and cartilage, others such as ultrasonography play a complementary role that will be discussed briefly.Facet SolutionsGenzymeStrykerMerck SeronoGE Healthcar

Magnetic Resonance Imaging Assessment of Subchondral Bone and Soft Tissues in Knee Osteoarthritis

Knee osteoarthritis (OA) has to be considered a whole joint disease. Magnetic resonance imaging (MRI) allows superior assessment of all joint tissues that may be involved in OA, such as the subchondral bone, synovium, ligaments, and periarticular soft tissues. Reliable MRI-based scoring systems are available to assess and quantify these structures and associated pathology. Cross-sectional and longitudinal evaluation has enabled practitioners to understand their relevance in explaining pain and structural progression

Strategic application of imaging in DMOAD clinical trials: focus on eligibility, drug delivery, and semiquantitative assessment of structural progression

Despite decades of research efforts and multiple clinical trials aimed at discovering efficacious disease-modifying osteoarthritis (OA) drugs (DMOAD), we still do not have a drug that shows convincing scientific evidence to be approved as an effective DMOAD. It has been suggested these DMOAD clinical trials were in part unsuccessful since eligibility criteria and imaging-based outcome evaluation were solely based on conventional radiography. The OA research community has been aware of the limitations of conventional radiography being used as a primary imaging modality for eligibility and efficacy assessment in DMOAD trials. An imaging modality for DMOAD trials should be able to depict soft tissue and osseous pathologies that are relevant to OA disease progression and clinical manifestations of OA. Magnetic resonance imaging (MRI) fulfills these criteria and advances in technology and increasing knowledge regarding imaging outcomes likely should play a more prominent role in DMOAD clinical trials. In this perspective article, we will describe MRI-based tools and analytic methods that can be applied to DMOAD clinical trials with a particular emphasis on knee OA. MRI should be the modality of choice for eligibility screening and outcome assessment. Optimal MRI pulse sequences must be chosen to visualize specific features of OA

Imaging of Muscle Injuries in Sports Medicine: Sports Imaging Series

In sports-related muscle injuries, the main goal of the sports medicine physician is to return the athlete to competition-balanced against the need to prevent the injury from worsening or recurring. Prognosis based on the available clinical and imaging information is crucial. Imaging is crucial to confirm and assess the extent of sports-related muscle injuries and may help to guide management, which directly affects the prognosis. This is especially important when the diagnosis or grade of injury is unclear, when recovery is taking longer than expected, and when interventional or surgical management may be necessary. Several imaging techniques are widely available, with ultrasonography and magnetic resonance imaging currently the most frequently applied in sports medicine. This state of the art review will discuss the main imaging modalities for the assessment of sports-related muscle injuries, including advanced imaging techniques, with the focus on the clinical relevance of imaging features of muscle injuries. (C) RSNA, 201