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      Comorbidity and metabolic syndrome in patients with multiple sclerosis from Asturias and Catalonia, Spain

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          Abstract

          Background

          The impact of comorbidity on multiple sclerosis (MS) is a new area of interest. Limited data on the risk factors of metabolic syndrome (MetS) is currently available. The aim of this study was to estimate the presence of comorbid conditions and MetS in a sample of adult patients with MS.

          Methods

          A retrospective, cohort study was conducted using electronic medical records from 19 primary care centres in Catalonia and Asturias, Spain. The number of chronic diseases (diagnoses), the Charlson Comorbidity Index and the individual Case-mix Index were used to assess general comorbidity variables. MetS was defined using the National Cholesterol Education Program Adult Treatment Panel III. Patients were distributed into two groups according to the Expanded Disability Status Scale (EDSS) score: 0–3.5 and 4–10.

          Results

          A total of 222 patients were studied (mean age = 45.5 (SD 12.5) years, 64.4% were female and 62.2% presented a diagnosis of relapsing-remitting MS). Mean EDSS score was 3.2 (SD 2.0). Depression (32.4%), dyslipidaemia (31.1%), hypertension (23.0%) and obesity (22.5%) were the most common comorbidities. Overall MetS prevalence was 31.1% (95% CI: 25.0–37.2%). Patients with an EDSS ≥ 4.0 showed a significantly higher number of comorbidities (OR=2.2; 95% CI: 1.7–3.0; p<0.001).

          Conclusion

          MS patients had a high prevalence of MetS. Screening for comorbidity should be part of standard MS care. Further studies are necessary to confirm this association and the underlying mechanisms of MS and its comorbidities.

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          Most cited references22

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          Obesity in autoimmune diseases: not a passive bystander.

          In the last decades, autoimmune diseases have experienced a dramatic increase in Western countries. The involvement of environmental factors is strongly suspected to explain this rise. Particularly, over the same period, obesity has followed the same outbreak. Since the exciting discovery of the secretory properties of adipose tissue, the relationship between obesity and autoimmunity and the understanding of the underlying mechanisms have become of major interest. Indeed, the fat tissue has been found to produce a wide variety of "adipokines", involved in the regulation of numerous physiological functions, including the immune response. By conducting a systematic literature review, we extracted 329 articles regarding clinical, experimental and pathophysiological data on the relationship between obesity, adipokines - namely leptin, adiponectin, resistin, visfatin - and various immune-mediated conditions, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), inflammatory bowel disease (IBD), multiple sclerosis (MS), type-1 diabetes (T1D), psoriasis and psoriatic arthritis (PsA), and thyroid autoimmunity (TAI), especially Hashimoto thyroiditis (HT). The strongest levels of evidence support an increased risk of RA (OR=1.2-3.4), MS (OR=2), psoriasis and PsA (OR=1.48-6.46) in obese subjects. A higher risk of IBD, T1D and TAI is also suggested. Moreover, obesity worsens the course of RA, SLE, IBD, psoriasis and PsA, and impairs the treatment response of RA, IBD, psoriasis and PsA. Extensive clinical data and experimental models demonstrate the involvement of adipokines in the pathogenesis of these autoimmune diseases. Obesity appears to be a major environmental factor contributing to the onset and progression of autoimmune diseases.
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            Metabolic syndrome with and without C-reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study.

            The National Cholesterol Education Program (NCEP) recently proposed a simple definition for metabolic syndrome. Information on the prospective association of this definition for coronary heart disease (CHD) and type 2 diabetes is currently limited. We used a modified NCEP definition with body mass index in place of waist circumference. Baseline assessments in the West of Scotland Coronary Prevention Study were available for 6447 men to predict CHD risk and for 5974 men to predict incident diabetes over 4.9 years of follow-up. Mean LDL cholesterol was similar but C-reactive protein was higher (P<0.0001) in the 26% of men with the syndrome compared with those without. Metabolic syndrome increased the risk for a CHD event [univariate hazard ratio (HR)=1.76 (95% CI, 1.44 to 2.15)] and for diabetes [univariate HR=3.50 (95% CI 2.51 to 4.90)]. Metabolic syndrome continued to predict CHD events (HR=1.30, 95% CI, 1.00 to 1.67, P=0.045) in a multivariate model incorporating conventional risk factors. Men with 4 or 5 features of the syndrome had a 3.7-fold increase in risk for CHD and a 24.5-fold increase for diabetes compared with men with none (both P<0.0001). C-reactive protein enhanced prognostic information for both outcomes. With pravastatin, men with the syndrome had similar risk reduction for CHD as compared with those without (HR, 0.73 and 0.69; pravastatin versus placebo). A modified NCEP metabolic syndrome definition predicts CHD events, and, more strikingly, new-onset diabetes, and thus helps identify individuals who may receive particular benefit from lifestyle measures to prevent these diseases.
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              Development and application of a population-oriented measure of ambulatory care case-mix.

              This article describes a new case-mix methodology applicable primarily to the ambulatory care sector. The Ambulatory Care Group (ACG) system provides a conceptually simple, statistically valid, and clinically relevant measure useful in predicting the utilization of ambulatory health services within a particular population group. ACGs are based on a person's demographic characteristics and their pattern of disease over an extended period of time, such as a year. Specifically, the ACG system is driven by a person's age, sex, and ICD-9-CM diagnoses assigned during patient-provider encounters; it does not require any special data beyond those collected routinely by insurance claims systems or encounter forms. The categorization scheme does not depend on the presence of specific diagnoses that may change over time; rather it is based on broad clusters of diagnoses and conditions. The presence or absence of each disease cluster, along with age and sex, are used to classify a person into one of 51 ACG categories. The ACG system has been developed and tested using computerized encounter and claims data from more than 160,000 continuous enrollees at four large HMOs and a state's Medicaid program. The ACG system can explain more than 50% of the variance in ambulatory resource use if used retrospectively and more than 20% if applied prospectively. This compares with 6% when age and sex alone are used. In addition to describing ACG development and validation, this article also explores some potential applications of the system for provider payment, quality assurance, utilization review, and health services research, particularly as it relates to capitated settings.
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                Author and article information

                Contributors
                asicras@bsa.cat
                elena.ruiz-beato@roche.com
                rnavarro.germanstrias@gencat.cat
                +34 661404771 , jorge.maurino@roche.com
                Journal
                BMC Neurol
                BMC Neurol
                BMC Neurology
                BioMed Central (London )
                1471-2377
                17 July 2017
                17 July 2017
                2017
                : 17
                : 134
                Affiliations
                [1 ]Fundación Rediss (Red de Investigación en servicios Sanitarios), Barcelona, Spain
                [2 ]ISNI 0000 0004 1768 8390, GRID grid.476717.4, Health Economics and Outcomes Research Unit, , Roche Farma S.A., ; Madrid, Spain
                [3 ]ISNI 0000 0004 1767 6330, GRID grid.411438.b, Department of Medical Information, , Hospital Universitari Germans Trias i Pujol, ; Badalona, Barcelona, Spain
                [4 ]ISNI 0000 0004 1768 8390, GRID grid.476717.4, Medical Department, , Roche Farma S.A., ; Madrid, Spain
                Article
                914
                10.1186/s12883-017-0914-2
                5512748
                28716070
                51f7a122-3ccd-4fd1-a752-c1e95f89fa97
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 15 March 2017
                : 9 July 2017
                Funding
                Funded by: Roche Farma Spain
                Award ID: Not applicable
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Neurology
                comorbidity,metabolic syndrome,multiple sclerosis,electronic medical records
                Neurology
                comorbidity, metabolic syndrome, multiple sclerosis, electronic medical records

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