The influence of partners on successful lifestyle modification in patients with coronary artery disease

Background: Marital status is associated with prognosis in patients with cardiovascular disease (CVD). However, the influence of partners on successful modification of lifestyle-related risk factors (LRFs) in secondary CVD prevention is unclear. Therefore, we studied the association between the presence of a partner, partner participation in lifestyle interventions and LRF modification in patients with coronary artery disease (CAD). Methods: In a secondary analysis of the RESPONSE-2 trial (n = 711), which compared nurse-coordinated referral to community-based lifestyle programs (smoking cessation, weight reduction and/or physical activity) to usual care in patients with CAD, we investigated the association between the presence of a partner and the level of partner participation on improvement in >1 LRF (urinary cotinine <200 ng/l, ≥5% weight reduction, ≥10% increased 6-min walking distance) without deterioration in other LRFs at 12 months follow-up. Results: The proportion of patients with a partner was 80% (571/711); 19% women (108/571). In the intervention group, 48% (141/293) had a participating partner in ≥1 lifestyle program. Overall, the presence of a partner was associated with patients' successful LRF modification (adjusted risk ratio (aRR) 1.93, 95% confidence interval (CI) 1.40-2.51). A participating partner was associated with successful weight reduction (aRR 1.73, 95% CI 1.15-2.35). Conclusion: The presence of a partner is associated with LRF improvement in patients with CAD. Moreover, patients with partners participating in lifestyle programs are more successful in reducing weight. Involving partners of CAD patients in weight reduction interventions should be considered in routine practice. Keywords: (Mesh): Secondary prevention; Coronary artery disease; Risk reduction behaviour; Social support; Spouses

Physical and Cognitive Functioning After 3 Years Can Be Predicted Using Information From the Diagnostic Process in Recently Diagnosed Multiple Sclerosis

Objective\ud To predict functioning after 3 years in patients with recently diagnosed multiple sclerosis (MS).\ud \ud Design\ud Inception cohort with 3 years of follow-up. At baseline, predictors were obtained from medical history taking, neurologic examination, and magnetic resonance imaging (MRI).\ud \ud Setting\ud Neurology outpatient clinic.\ud \ud Participants\ud Patients with MS (N=156); 146 with complete follow-up.\ud \ud Interventions\ud Not applicable.\ud \ud Main Outcome Measures\ud Inability to walk at least 500m, impaired dexterity, cognitive impairments, incontinence, inability to drive a car or use public transportation, social dysfunction, and reliance on a disability pension.\ud \ud Results\ud Clinical prediction rules were constructed for the models that were well calibrated (sufficient agreement between predicted and observed outcomes, based on visual inspection of calibration curves) and that showed sufficient discrimination (area under the receiver operation characteristic curve >.70) after internal bootstrap validation. The models for the inability to walk at least 500m, impaired dexterity, and cognitive impairments were well calibrated. Discrimination was sufficient for all 7 models, except the one predicting social dysfunction (.67). The inability to walk at least 500m was predicted by the perceived ability to walk, impairment of the cerebellar tract, and the number of MRI lesions in the spinal cord. Impaired dexterity was predicted by the perceived ability to use the hands, impairments of the pyramidal, cerebellar, and sensory tracts, and the T2-weighted infratentorial lesion load. Cognitive impairment was predicted by age, gender, the perceived ability to concentrate, and the T2-weighted supratentorial lesion load.\ud \ud Conclusions\ud Inability to walk at least 500m, impaired dexterity, and cognitive impairments can be predicted with predictors that are derived from medical history taking, neurologic examination, and MRI shortly after a definite diagnosis of MS has been made.\ud \u

Peroxicretion: a novel secretion pathway in the eukaryotic cell

Background: Enzyme production in microbial cells has been limited to secreted enzymes or intracellular enzymes followed by expensive down stream processing. Extracellular enzymes consists mainly of hydrolases while intracellular enzymes exhibit a much broader diversity. If these intracellular enzymes could be secreted by the cell the potential of industrial applications of enzymes would be enlarged. Therefore a novel secretion pathway for intracellular proteins was developed, using peroxisomes as secretion vesicles. Results: Peroxisomes were decorated with a Golgi derived v-SNARE using a peroxisomal membrane protein as an anchor. This allowed the peroxisomes to fuse with the plasma membrane. Intracellular proteins were transported into the peroxisomes by adding a peroxisomal import signal (SKL tag). The proteins which were imported in the peroxisomes, were released into the extracellular space through this artificial secretion pathway which was designated peroxicretion. This concept was supported by electron microscopy studies. Conclusion: Our results demonstrate that it is possible to reroute the intracellular trafficking of vesicles by changing the localisation of SNARE molecules, this approach can be used in in vivo biological studies to clarify the different control mechanisms regulating intracellular membrane trafficking. In addition we demonstrate peroxicretion of a diverse set of intracellular proteins. Therefore, we anticipate that the concept of peroxicretion may revolutionize the production of intracellular proteins from fungi and other microbial cells, as well as from mammalian cells.

Clinically Isolated Syndromes Suggestive of Multiple Sclerosis: An Optical Coherence Tomography Study

Background: Optical coherence tomography (OCT) is a simple, high-resolution technique to quantify the thickness of retinal nerve fiber layer (RNFL), which provides an indirect measurement of axonal damage in multiple sclerosis (MS). This study aimed to evaluate RNFL thickness in patients at presentation with clinically isolated syndromes (CIS) suggestive of MS. Methodology: This was a cross-sectional study. Twenty-four patients with CIS suggestive of MS (8 optic neuritis [ON], 6 spinal cord syndromes, 5 brainstem symptoms and 5 with sensory and other syndromes) were prospectively studied. The main outcome evaluated was RNFL thickness at CIS onset. Secondary objectives were to study the relationship between RNFL thickness and MRI criteria for disease dissemination in space (DIS) as well as the presence of oligoclonal bands in the cerebrospinal fluid. Principal Findings: Thirteen patients had decreased RNFL thickness in at least one quadrant. Mean RNFL thickness was 101.67±10.72 μm in retrobulbar ON eyes and 96.93±10.54 in unaffected eyes. Three of the 6 patients with myelitis had at least one abnormal quadrant in one of the two eyes. Eight CIS patients fulfilled DIS MRI criteria. The presence of at least one quadrant of an optic nerve with a RNFL thickness at a P<5% cut-off value had a sensitivity of 75% and a specificity of 56% for predicting DIS MRI. Conclusions: The findings from this study show that axonal damage measured by OCT is present in any type of CIS; even in myelitis forms, not only in ON as seen up to now. OCT can detect axonal damage in very early stages of disease and seems to have high sensitivity and moderate specificity for predicting DIS MRI. Studies with prospective long-term follow-up would be needed to establish the prognostic value of baseline OCT finding

Computational classifiers for predicting the short-term course of Multiple sclerosis

The aim of this study was to assess the diagnostic accuracy (sensitivity and specificity) of clinical, imaging and motor evoked potentials (MEP) for predicting the short-term prognosis of multiple sclerosis (MS). METHODS: We obtained clinical data, MRI and MEP from a prospective cohort of 51 patients and 20 matched controls followed for two years. Clinical end-points recorded were: 1) expanded disability status scale (EDSS), 2) disability progression, and 3) new relapses. We constructed computational classifiers (Bayesian, random decision-trees, simple logistic-linear regression-and neural networks) and calculated their accuracy by means of a 10-fold cross-validation method. We also validated our findings with a second cohort of 96 MS patients from a second center. RESULTS: We found that disability at baseline, grey matter volume and MEP were the variables that better correlated with clinical end-points, although their diagnostic accuracy was low. However, classifiers combining the most informative variables, namely baseline disability (EDSS), MRI lesion load and central motor conduction time (CMCT), were much more accurate in predicting future disability. Using the most informative variables (especially EDSS and CMCT) we developed a neural network (NNet) that attained a good performance for predicting the EDSS change. The predictive ability of the neural network was validated in an independent cohort obtaining similar accuracy (80%) for predicting the change in the EDSS two years later. CONCLUSIONS: The usefulness of clinical variables for predicting the course of MS on an individual basis is limited, despite being associated with the disease course. By training a NNet with the most informative variables we achieved a good accuracy for predicting short-term disability

Differential diagnosis of suspected multiple sclerosis: a consensus approach

BACKGROUND AND OBJECTIVES: Diagnosis of multiple sclerosis (MS) requires exclusion of diseases that could better explain the clinical and paraclinical findings. A systematic process for exclusion of alternative diagnoses has not been defined. An International Panel of MS experts developed consensus perspectives on MS differential diagnosis. METHODS: Using available literature and consensus, we developed guidelines for MS differential diagnosis, focusing on exclusion of potential MS mimics, diagnosis of common initial isolated clinical syndromes, and differentiating between MS and non-MS idiopathic inflammatory demyelinating diseases. RESULTS: We present recommendations for 1) clinical and paraclinical red flags suggesting alternative diagnoses to MS; 2) more precise definition of "clinically isolated syndromes" (CIS), often the first presentations of MS or its alternatives; 3) algorithms for diagnosis of three common CISs related to MS in the optic nerves, brainstem, and spinal cord; and 4) a classification scheme and diagnosis criteria for idiopathic inflammatory demyelinating disorders of the central nervous system. CONCLUSIONS: Differential diagnosis leading to MS or alternatives is complex and a strong evidence base is lacking. Consensus-determined guidelines provide a practical path for diagnosis and will be useful for the non-MS specialist neurologist. Recommendations are made for future research to validate and support these guidelines. Guidance on the differential diagnosis process when MS is under consideration will enhance diagnostic accuracy and precision