Ultrasonography and color Doppler of proximal gluteal enthesitis in juvenile idiopathic arthritis: a descriptive study

Background: The presence of enthesitis (insertional inflammation) in patients with juvenile idiopathic arthritis (JIA) is difficult to establish clinically and may influence classification and treatment of the disease. We used ultrasonography (US) and color Doppler (CD) imaging to detect enthesitis at the small and deep-seated proximal insertion of the gluteus medius fascia on the posterior iliac crest where clinical diagnosis is difficult. The findings in JIA patients were compared with those obtained in healthy controls and with the patients' MRI results. Methods: Seventy-six proximal gluteus medius insertions were studied clinically (tenderness to palpation of the posterior iliac crest) and by US and CD (echogenicity, thickness, hyperemia) in 38 patients with JIA and in 38 healthy controls, respectively (median age 13 years, range 7-18 years). In addition, an additional MRI examination of the sacroiliac joints and iliac crests was performed in all patients. Results: In patients with focal, palpable tenderness, US detected decreased echogenicity of the entheses in 53% of the iliac crests (bilateral in 37% and unilateral in 32%). US also revealed significantly thicker entheses in JIA patients compared to healthy controls (p < 0.003 left side, p < 0.001 right side). There was no significant difference in thickness between the left and right sides in individual subjects. Hyperemia was detected by CD in 37% (28/76) of the iliac crests and by contrast-enhanced MRI in 12% (6/50). Conclusions: According to US, the gluteus medius insertion was thicker in JIA patients than in controls, and it was hypoechoic (enthesitis) in about half of the patients. These findings may represent chronic, inactive disease in some of the patients, because there was only limited Doppler flow and MRI contrast enhancement. The present study indicates that US can be useful as an adjunct to clinical examination for improved assessment of enthesitis in JIA. This may influence disease classification, ambition to treat, and choice of treatment regimen

Prognostic factors for the disease course and 8-year outcome in Nordic children with oligoarticular-onset juvenile idiopathic arthritis

Peer reviewe

The Danish version of the Juvenile Arthritis Multidimensional Assessment Report (JAMAR)

The Juvenile Arthritis Multidimensional Assessment Report (JAMAR) is a new parent/patient-reported outcome measure that enables a thorough assessment of the disease status in children with juvenile idiopathic arthritis (JIA). We report the results of the cross-cultural adaptation and validation of the parent and patient versions of the JAMAR in the Danish language. The reading comprehension of the questionnaire was tested in ten JIA parents and patients. Each participating centre was asked to collect demographic, clinical data and the JAMAR in 100 consecutive JIA patients or all consecutive patients seen in a 6-month period and to administer the JAMAR to 100 healthy children and their parents. The statistical validation phase explored descriptive statistics and the psychometric issues of the JAMAR: the three Likert assumptions, floor/ceiling effects, internal consistency, Cronbach's alpha, interscale correlations, test-retest reliability and construct validity (convergent and discriminant validity). A total of 303 JIA patients (7.9% systemic, 35% oligoarticular, 22.1% RF negative polyarthritis, 35% other categories) and 99 healthy children, were enrolled in three centres. The JAMAR components discriminated well healthy subjects from JIA patients. All JAMAR components revealed good psychometric performances. In conclusion, the Danish version of the JAMAR is a valid tool for the assessment of children with JIA and is suitable for use both in routine clinical practice and clinical research

Analyse mathématique et modélisation

Henri Berestycki, directeur d’études Méthodes d’EDP et numériques en finance de marchés (avec Olivier Pironneau, professeur à l’Université Paris-VI) Différents aspects de la modélisation mathématique des marchés financiers ont été présentés. On s’est attaché en particulier à la formulation en termes d’équations aux dérivées partielles (EDP) des problèmes d’évaluation de produits dérivés (options, contrats futurs, etc.) et de techniques de gestion du risque. Les outils d’analyse mathématique d..

Psoriasis and associated variables in classification and outcome of juvenile idiopathic arthritis - an eight-year follow-up study

Background: To study the impact of psoriasis and features associated with psoriasis on classification and outcome in a population-based follow-up cohort of children with juvenile idiopathic arthritis (JIA). Methods: In all, 440 children with JIA were followed for a median of 8 years in a prospective Nordic population-based cohort study. Data for remission was available for 427 of these children. The presence of psoriasis, psoriasis-like rash, dactylitis, nail pitting, enthesitis, tenosynovitis and heredity was assessed in relation to ILAR classification and remission. Results: Clinical findings associated with psoriasis developed consecutively during the 8-year period. Six of 14 children with psoriasis were not classified as juvenile psoriatic arthritis according to the ILAR criteria at 8 year follow-up. Dactylitis was more common in children with early onset of JIA. After 8 years we found a cumulative median number of eleven arthritic joints in children with psoriasis or psoriasis- like rash compared with six in the rest of the cohort (p = 0.02). Also, the chance for not being in remission after 8 years increased significantly in patients with psoriasis, psoriasis-like rash or at least two of: 1) first-degree heredity for psoriasis or psoriatic arthritis, 2) dactylitis or 3) nail pitting, compared with the rest of the group (OR 3.32, p = 0.010). Conclusions: Our results indicate a more severe disease over time in psoriasis- associated JIA, as features of psoriasis develop during the disease course. This group is a major challenge to encompass in a future JIA classification in order to facilitate early tailored treatment.Peer reviewe

Assessing cognitive presence using automated learning analytics methods

With the increasing pace of technological changes in the modern society, there has been a growing interest from educators, business leaders, and policymakers in teaching important higher-order skills which were identified as necessary for thriving in the present-day globalized economy. In this regard, one of the most widely discussed higher order skills is critical thinking, whose importance in shaping problem solving, decision making, and logical thinking has been recognized. Within the domain of distance and online education, the Community of Inquiry (CoI) model provides a pedagogical framework for understanding the critical dimensions of student learning and factors which impact the development of student critical thinking. The CoI model follows the social-constructivist perspective on learning in which learning is seen as happening in both individual minds of learners and through the discourse within the group of learners. Central to the CoI model is the construct of cognitive presence, which captures the student cognitive engagement and the development of critical thinking and deep thinking skills. However, the assessment of cognitive presence is challenging task, particularly given its latent nature and the inherent physical and time separation between students and instructors in distance education settings. One way to address this problem is to make use of the vast amounts of learning data being collected by learning systems. This thesis presents novel methods for understanding and assessing the levels of cognitive presence based on learning analytics techniques and the data collected by learning environments. We first outline a comprehensive model for cognitive presence assessment which builds on the well-established evidence-cantered design (ECD) assessment framework. The proposed assessment model provides a foundation of the thesis, showing how the developed analytical models and their components fit together and how they can be adjusted for new learning contexts. The thesis shows two distinct and complementary analytical methods for assessing students’ cognitive presence and its development. The first method is based on the automated classification of student discussion messages and captures learning as it is observed in the student dialogue. The second analytics method relies on the analysis of log data of students’ use of the learning platform and captures the individual dimension of the learning process. The developed analytics also extend current theoretical understanding of the cognitive presence construct through data-informed operationalization of cognitive presence with different quantitative measures extracted from the student use of online discussions. We also examine methodological challenges of assessing cognitive presence and other forms of cognitive engagement through the analysis of trace data. Finally, with the intent of enabling for the wider adoption of the CoI model for new online learning modalities, the last two chapters examine the use of developed analytics within the context of Massive Open Online Courses (MOOCs). Given the substantial differences between traditional online and MOOC contexts, we first evaluate the suitability of the CoI model for MOOC settings and then assess students’ cognitive presence using the data collected by the MOOC platform. We conclude the thesis with the discussion of practical application and impact of the present work and the directions for the future research

Predicting unfavorable long-term outcome in juvenile idiopathic arthritis: results from the Nordic cohort study

Abstract Background The aim was to develop prediction rules that may guide early treatment decisions based on baseline clinical predictors of long-term unfavorable outcome in juvenile idiopathic arthritis (JIA). Methods In the Nordic JIA cohort, we assessed baseline disease characteristics as predictors of the following outcomes 8 years after disease onset. Non-achievement of remission off medication according to the preliminary Wallace criteria, functional disability assessed by Childhood Health Assessment Questionnaire (CHAQ) and Physical Summary Score (PhS) of the Child Health Questionnaire, and articular damage assessed by the Juvenile Arthritis Damage Index-Articular (JADI-A). Multivariable models were constructed, and cross-validations were performed by repeated partitioning of the cohort into training sets for developing prediction models and validation sets to test predictive ability. Results The total cohort constituted 423 children. Remission status was available in 410 children: 244 (59.5%) of these did not achieve remission off medication at the final study visit. Functional disability was present in 111/340 (32.7%) children assessed by CHAQ and 40/199 (20.1%) by PhS, and joint damage was found in 29/216 (13.4%). Model performance was acceptable for making predictions of long-term outcome. In validation sets, the area under the curves (AUCs) in the receiver operating characteristic (ROC) curves were 0.78 (IQR 0.72–0.82) for non-achievement of remission off medication, 0.73 (IQR 0.67–0.76) for functional disability assessed by CHAQ, 0.74 (IQR 0.65–0.80) for functional disability assessed by PhS, and 0.73 (IQR 0.63–0.76) for joint damage using JADI-A. Conclusion The feasibility of making long-term predictions of JIA outcome based on early clinical assessment is demonstrated. The prediction models have acceptable precision and require only readily available baseline variables. Further testing in other cohorts is warranted