Low bone mineral density is related to male gender and decreased functional capacity in early spondylarthropathies

The objective of this study was to determine the prevalence and risk factors of low bone mineral density (BMD) in patients with spondylarthropathies (SpA) at an early stage of disease. In this cross-sectional study, the BMD of lumbar spine and hips was measured in 130 consecutive early SpA patients. The outcome measure BMD was defined as (1) osteoporosis, (2) osteopenia, and (3) normal bone density. Logistic regression analyses were used to investigate relations between the following variables: age, gender, disease duration, diagnosis, HLA-B27, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Metrology Index (BASMI), extra-spinal manifestations and medication, with outcome measure low BMD (osteopenia and/or osteoporosis). The SpA population had a median time since diagnosis of 6.6 months and a disease duration of 6.3 years. In total, 9% of the early SpA patients had osteoporosis, 38% osteopenia, and 53% normal BMD. On univariate analyses, male gender, diagnosis of ankylosing spondylitis, increased CRP, high BASFI, and high BASMI were significantly associated with low BMD. Factors showing a relation with low BMD in the multivariate model were male gender (OR 4.18, 95% confidence interval (CI) 1.73–10.09), high BASMI (OR 1.54, 95% CI 1.14–2.07), and high BASFI (OR 1.18, 95% CI 1.00–1.39). In early SpA patients, a high frequency (47%) of low BMD in femur as well as in lumbar spine was found. Low BMD was associated with male gender and decreased functional capacity. These findings emphasize the need for more alertness for osteoporosis and osteopenia in spondylarthropathy patients at an early stage of the disease

Model-Based Therapeutic Correction of Hypothalamic-Pituitary-Adrenal Axis Dysfunction

The hypothalamic-pituitary-adrenal (HPA) axis is a major system maintaining body homeostasis by regulating the neuroendocrine and sympathetic nervous systems as well modulating immune function. Recent work has shown that the complex dynamics of this system accommodate several stable steady states, one of which corresponds to the hypocortisol state observed in patients with chronic fatigue syndrome (CFS). At present these dynamics are not formally considered in the development of treatment strategies. Here we use model-based predictive control (MPC) methodology to estimate robust treatment courses for displacing the HPA axis from an abnormal hypocortisol steady state back to a healthy cortisol level. This approach was applied to a recent model of HPA axis dynamics incorporating glucocorticoid receptor kinetics. A candidate treatment that displays robust properties in the face of significant biological variability and measurement uncertainty requires that cortisol be further suppressed for a short period until adrenocorticotropic hormone levels exceed 30% of baseline. Treatment may then be discontinued, and the HPA axis will naturally progress to a stable attractor defined by normal hormone levels. Suppression of biologically available cortisol may be achieved through the use of binding proteins such as CBG and certain metabolizing enzymes, thus offering possible avenues for deployment in a clinical setting. Treatment strategies can therefore be designed that maximally exploit system dynamics to provide a robust response to treatment and ensure a positive outcome over a wide range of conditions. Perhaps most importantly, a treatment course involving further reduction in cortisol, even transient, is quite counterintuitive and challenges the conventional strategy of supplementing cortisol levels, an approach based on steady-state reasoning