1,092 research outputs found

    Analysis of Published Criteria for Clinically Inactive Disease in a Large Juvenile Dermatomyositis Cohort Shows That Skin Disease Is Underestimated

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    The Pediatric Rheumatology International Trials Organisation (PRINTO) recently published criteria for classification of patients with juvenile dermatomyositis (DM) as having clinically inactive disease. The criteria require that at least 3 of 4 conditions be met, i.e., creatine kinase level ≤150 units/liter, Childhood Myositis Assessment Scale score ≥48, Manual Muscle Testing in 8 muscles score ≥78, and physician's global assessment of overall disease activity (PGA) ≤0.2. The present study was undertaken to test these criteria in a UK cohort of patients with juvenile DM

    Juvenile Dermatomyositis: what comes next? Long-term outcomes in childhood myositis from a patient perspective

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    BACKGROUND: To describe long-term outcomes in JDM using patient questionnaires and link to longitudinal, prospectively collected data for each patient within the Juvenile Dermatomyositis Cohort and Biomarker Study, UK and Ireland (JDCBS) to determine outcome predictors.  METHODS: JDCBS participants aged ≥ 16y completed the SF36, HAQ and a questionnaire regarding current disease features, medications, education and employment. Data collected from the JDCBS included disease subtype, demographics, clinical and laboratory features. Intensity indices were calculated for physician VAS, modified skin DAS, CMAS and MMT8 by dividing area under the curve (AUC) from longitudinal score trajectories by duration of study follow-up (y). Relationships between questionnaire and JDCBS clinical / laboratory data were investigated fitting statistical models appropriate for cross sectional and longitudinal data. RESULTS: Of 190 questionnaires sent, 84 (44%) were returned. Average age of respondents was 20.6 years (SD 3.9), time since diagnosis was 12.4 years (SD 5.0), age at onset was 9.2 years (SD 4.3), female to male ratio 4.25:1. Forty-nine (59%) self-reported persistently active disease, 54 (65%) were still taking immunosuppressive medication. 14/32 at school/higher education reported myositis adversely affecting academic results. 18–24 year-olds were twice as likely to be unemployed compared the UK population (OR = 0.456, 95% CI 0.24, 0.84, p = 0.001). Participants ≥ 18 years were three times as likely to be living with a parent/guardian (OR = 3.39, p < 0.001). SF36 MCS and MMT8 intensity index scores were significantly correlated (ρ = 0.328, p = 0.007). CONCLUSIONS: After 12.4 years, questionnaire responders reported self-perceived high rates of persistently active disease and medication use, reduced rates of employment and were more likely to live with a parent/guardian. Perceived persistently active muscle disease appeared to affect quality of life in these patients and was the most significant contributor to long-term outcomes. Our findings highlight the importance of including the patient perspective in the assessment of long term outcomes, so that that we can start to target initial management strategies more effectively based on a combination of clinical and patient-reported data

    Evaluation of magnetic resonance imaging abnormalities in juvenile onset neuropsychiatric systemic lupus erythematosus.

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    The aim of this study was to describe the abnormalities identified with conventional MRI in children with neuropsychiatric systemic lupus erythematosus (NPSLE). This was single-centre (Great Ormond Street Hospital, London) retrospective case series of patients with juvenile NPSLE seen in 2003-2013. Brain MR images of the first episode of active NPSLE were reviewed. All patients fulfilled the 1999 ACR case definitions for NPSLE syndromes. Presenting neuropsychiatric manifestations, immunological findings and treatment are reported. Results are expressed as median and ranges or percentages. Fisher's exact test was used to identify clinical predictors of abnormal MRI. A total of 27 patients (22 females), median age 11 years (4-15), were identified. Presenting clinical symptoms included the following: headaches (85.1 %), mood disorder/depression (62.9 %), seizures (22.2 %), acute psychosis (18.5 %), cognitive dysfunction (14.8 %), movement disorder (14.8 %), acute confusional state (14.8 %), aseptic meningitis (7.4 %), demyelinating syndrome (3.7 %), myelopathy (3.7 %), dysautonomia (3.7 %) and cranial neuropathy (3.7 %). The principal MR findings were as follows: (1) absence of MRI abnormalities despite signs and symptoms of active NPSLE (59 %); (2) basilar artery territory infarction (3 %); (3) focal white matter hyperintensities on T2-weighted imaging (33 %); (4) cortical grey matter lesions (3 %); and (5) brain atrophy (18.5 %). The presence of an anxiety disorder strongly associated with abnormal MRI findings (p = 0.008). In over half the children with NPSLE, no conventional MRI abnormalities were observed; white matter hyperintensities were the most commonly described abnormalities. Improved MR techniques coupled with other alternative diagnostic imaging modalities may improve the detection rate of brain involvement in juvenile NPSLE

    Comparison of the Utility and Validity of Three Scoring Tools to Measure Skin Involvement in Patients With Juvenile Dermatomyositis

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    OBJECTIVE: To compare the abbreviated Cutaneous Assessment Tool (CAT), Disease Activity Score (DAS), and Myositis Intention to Treat Activity Index (MITAX) and correlate them with the physician's 10-cm skin visual analog scale (VAS) in order to define which tool best assesses skin disease in patients with juvenile dermatomyositis. METHODS: A total of 71 patients recruited to the UK Juvenile Dermatomyositis Cohort and Biomarker Study were included and assessed for skin disease using the CAT, DAS, MITAX, and skin VAS. The Childhood Myositis Assessment Scale (CMAS), manual muscle testing of 8 groups (MMT8), muscle enzymes, inflammatory markers, and physician's global VAS were recorded. Relationships were evaluated using Spearman's correlations and predictors with linear regression. Interrater reliability was assessed using intraclass correlation coefficients. RESULTS: All 3 tools showed correlation with the physician's global VAS and skin VAS, with DAS skin showing the strongest correlation with skin VAS. DAS skin and CAT activity were inversely correlated with CMAS and MMT8, but these correlations were moderate. No correlations were found between the skin tools and inflammatory markers or muscle enzymes. DAS skin and CAT were the quickest to complete (mean ± SD 0.68 ± 0.1 minutes and 0.63 ± 0.1 minutes, respectively). CONCLUSION: The 3 skin tools were quick and easy to use. The DAS skin correlated best with the skin VAS. The addition of CAT in a bivariate model containing the physician's global VAS was a statistically significant estimator of skin VAS score. We propose that there is scope for a new skin tool to be devised and tested, which takes into account the strengths of the 3 existing tools

    Effect of Silicon Content on Carbide Precipitation and Low-Temperature Toughness of Pressure Vessel Steels

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    Cr – Mn – Mo – Ni pressure vessel steels containing 0.54 and 1.55% Si are studied. Metallographic and fractographic analyses of the steels after tempering at 650 and 700°C are performed. The impact toughness at – 30°C and the hardness of the steels are determined. The mass fraction of the carbide phase in the steels is computed with the help of the J-MatPro 4.0 software

    Identification and prediction of novel classes of long-term disease trajectories for patients with juvenile dermatomyositis using growth mixture models

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    OBJECTIVES: Uncertainty around clinical heterogeneity and outcomes for patients with JDM represents a major burden of disease and a challenge for clinical management. We sought to identify novel classes of patients having similar temporal patterns in disease activity and relate them to baseline clinical features. METHODS: Data were obtained for n = 519 patients, including baseline demographic and clinical features, baseline and follow-up records of physician's global assessment of disease (PGA), and skin disease activity (modified DAS). Growth mixture models (GMMs) were fitted to identify classes of patients with similar trajectories of these variables. Baseline predictors of class membership were identified using Lasso regression. RESULTS: GMM analysis of PGA identified two classes of patients. Patients in class 1 (89%) tended to improve, while patients in class 2 (11%) had more persistent disease. Lasso regression identified abnormal respiration, lipodystrophy and time since diagnosis as baseline predictors of class 2 membership, with estimated odds ratios, controlling for the other two variables, of 1.91 for presence of abnormal respiration, 1.92 for lipodystrophy and 1.32 for time since diagnosis. GMM analysis of modified DAS identified three classes of patients. Patients in classes 1 (16%) and 2 (12%) had higher levels of modified DAS at diagnosis that improved or remained high, respectively. Patients in class 3 (72%) began with lower DAS levels that improved more quickly. Higher proportions of patients in PGA class 2 were in DAS class 2 (19%, compared with 16 and 10%). CONCLUSION: GMM analysis identified novel JDM phenotypes based on longitudinal PGA and modified DAS

    International validation of a urinary biomarker panel for identification of active lupus nephritis in children.

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    Conventional markers of juvenile-onset systemic lupus erythematosus (JSLE) disease activity fail to adequately identify lupus nephritis (LN). While individual novel urine biomarkers are good at detecting LN flares, biomarker panels may improve diagnostic accuracy. The aim of this study was to assess the performance of a biomarker panel to identify active LN in two international JSLE cohorts.Novel urinary biomarkers, namely vascular cell adhesion molecule-1 (VCAM-1), monocyte chemoattractant protein 1 (MCP-1), lipocalin-like prostaglandin D synthase (LPGDS), transferrin (TF), ceruloplasmin, alpha-1-acid glycoprotein (AGP) and neutrophil gelatinase-associated lipocalin (NGAL), were quantified in a cross-sectional study that included participants of the UK JSLE Cohort Study (Cohort 1) and validated within the Einstein Lupus Cohort (Cohort 2). Binary logistic regression modelling and receiver operating characteristic curve analysis [area under the curve (AUC)] were used to identify and assess combinations of biomarkers for diagnostic accuracy.A total of 91 JSLE patients were recruited across both cohorts, of whom 31 (34 %) had active LN and 60 (66 %) had no LN. Urinary AGP, ceruloplasmin, VCAM-1, MCP-1 and LPGDS levels were significantly higher in those patients with active LN than in non-LN patients [all corrected p values (p c) < 0.05] across both cohorts. Urinary TF also differed between patient groups in Cohort 2 (p c = 0.001). Within Cohort 1, the optimal biomarker panel included AGP, ceruloplasmin, LPGDS and TF (AUC 0.920 for active LN identification). These results were validated in Cohort 2, with the same markers resulting in the optimal urine biomarker panel (AUC 0.991).In two international JSLE cohorts, urinary AGP, ceruloplasmin, LPGDS and TF demonstrate an 'excellent' ability for accurately identifying active LN in children

    Developing a provisional, international Minimal Dataset for Juvenile Dermatomyositis: for use in clinical practice to inform research.

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    Juvenile dermatomyositis (JDM) is a rare but severe autoimmune inflammatory myositis of childhood. International collaboration is essential in order to undertake clinical trials, understand the disease and improve long-term outcome. The aim of this study was to propose from existing collaborative initiatives a preliminary minimal dataset for JDM. This will form the basis of the future development of an international consensus-approved minimum core dataset to be used both in clinical care and inform research, allowing integration of data between centres
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