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BackgroundInflammatory rheumatic diseases are a debilitating disease affecting the joints and periarticular structures and leading, more or less rapidly, to cartilage and bone destruction. It is a major source of chronic pain and physical, psychological, and social disability, it affect approximately 1% of the world's population [1]. For more than 20 years, biotherapies have revolutionized the treatment of these inflammatory diseases and have largely contributed to the improvement of their prognosis [2]. Adherence to biologic therapies conditions the effectiveness of the treatments then the improvement of patients' quality of life [3].ObjectivesTo evaluate and compare adherence to biologic disease-modifying antirheumatic drugs (bDMARDs) according to the route of administration and the molecule used (Infliximab, Tocilizumab, Etanercept, Adalimumab, Certolizumab, and Golimumab) in patients with inflammatory rheumatic diseases.MethodsThis is a descriptive cross-sectional study with repeated data collection, bi-centric carried out in the rheumatology departments and outpatient clinics at Charles Nicolle Hospital and Rabta Hospital in Tunis and conducted over a period of 01 year and 02 months between 02/02/2021 and 30/04/2022. 71 adult patients with rheumatoid arthritis, spondyloarthritis or juvenile idiopathic arthritis were recruited, their adherence rate in the last 3 months before inclusion should be ≥80%. The collection of socio-demographic, clinical and therapeutic data was established with the help of a pre-established form, from medical files completed by questioning the patients during a direct interview or through a telephone communication. Adherence rate was calculated by determining the ratio of treatments cures (number of biologic injections taken during a year divided by the number of annual biologic injections prescribed).ResultsWithin the study population, adherence was estimated at 85.9%;in the group of patients using intravenous biotherapy was 82.1% (Infliximab 86%, Tocilizumab 75% p=0.04) and in the group of patients using subcutaneous treatment was 89.9% (Golimumab 94%, Etanercept 92%, Certolizumab 89%, Adalimumab 87% p=0.3). Adherence to biologic therapy was significantly higher in the subcutaneous group than in the intravenous group (p=0.01). The causes of poor adherence presented by the patients in this study were: stock-outs of biological treatment and delay in renewal by the national health insurance (CNAM) in thirty-eight cases (54%p<0.001), intercurrent infections in thirty-three cases (46% p=0.005) and the COVID 19 pandemic and its consequences in thirty patients (42%,p=0.28).ConclusionAdherence to biologic treatment is influenced by the route of administration, drugs type, intercurrent infections and drugs availability. All this factors must be treated to improve therapeutic adherence then the efficiency of the biologic therapy which conditions the preservation of physical capacities and an improvement in the quality of life.References[1]Adhésion médicamenteuse et représentations des patients atteints de rhumatisme inflammatoire chronique sous biothérapie: étude ADREP'RI.: 84. Betegnie AL.[2]2015 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis. Arthritis Rheumatol. Singh JA, Saag KG, Bridges SL, Akl EA et al. janv 2016;68(1):1‑26.[3]Adherence to biologic DMARD therapies in rheumatoid arthritis. Expert Opin Biol Ther. Koncz T, Pentek M, Brodszky V, Ersek K, Orlewska E, Gulacsi L. sept 2010;10(9):1367‑78.[4]Adherence of rheumatoid arthritis patients to biologic disease-modifying antirheumatic drugs: a cross-sectional study. Mena-Vazquez N, Manrique-Arija S, Yunquera-Romero L, Ureña-Garnica I, Rojas-Gimenez et al.. Rheumatol Int [Internet]. oct 2017 [cité 30 oct 2022];37(10):1709‑18.[5]Adherence to Anti-Tumor Necrosis Factor Therapy Administered Subcutaneously and Associated Factors in Patients with Rheumatoid Arthritis. Salaffi F, Carotti M, Di Carlo M, Farah S, Gutierrez M. J Clin Rheumatol. déc 2015;21(8):419‑25.Acknowledgements:N L.Disclosure of InterestsNone Declared.
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Since December 2019, a new virus of the coronaviridae, called Coronavirus 2019 (COVID-19), has appeared in the Wuhan province of China. It has been declared a pandemic by the World Health Organization (WHO). The clinical manifestations of COVID-19 reported in the literature are diverse and very heterogeneous. Among these manifestations, reactive arthritis (ReA) remains ambiguous, because of the difficulty of linking these arthritides to COVID-19. ReA is a condition caused by bacteria. The clinical pattern of ReA commonly consists of an inflammation of fewer than five joints, which often includes the lower extremities, joints, eyes, skin, and urethra. It is triggered by an infection in another part of the body;generally the intestines, genitals, or urinary tract. Arthritis may be "additive" or "migratory" (new joints become inflamed after the initially inflamed site has already improved). The time required to develop ReA after infection must not exceed 6 weeks. It occurs most often in men between the ages of 18 and 40. Some patients carry the HLA-B27 gene. Some authors reported cases of ReA caused by COVID-19. They argued that the timing of disease onset was consistent with COVID-19 infection and that no other clear sources of infection were identified. The presence of arthritis, digestive or genital associated manifestations, and the absence of other evident etiologies (after clinical and laboratory exams) were also advanced as arguments for the diagnosis of ReA. The treatment of ReA depends on its stage. Acute inflammation can be treated with nonsteroidal anti-inflammatory drugs. The late stage of reactive arthritis is considered chronic and generally treated with a diseasemodifying antirheumatic drug such as sulfasalazine or methotrexate. In more severe cases, biologic disease-modifying antirheumatic drugs may be used. © 2023 Nova Science Publishers, Inc.
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Successful data representation is a fundamental factor in machine learning based medical imaging analysis. Deep Learning (DL) has taken an essential role in robust representation learning. However, the inability of deep models to generalize to unseen data can quickly overfit intricate patterns. Thereby, the importance of implementing strategies to aid deep models in discovering useful priors from data to learn their intrinsic properties. Our model, which we call a dual role network (DRN), uses a dependency maximization approach based on Least Squared Mutual Information (LSMI). LSMI leverages dependency measures to ensure representation invariance and local smoothness. While prior works have used information theory dependency measures like mutual information, these are known to be computationally expensive due to the density estimation step. In contrast, our proposed DRN with LSMI formulation does not require the density estimation step and can be used as an alternative to approximate mutual information. Experiments on the CT based COVID-19 Detection and COVID-19 Severity Detection Challenges of the 2nd COV19D competition [24] demonstrate the effectiveness of our method compared to the baseline method of such competition. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Background: The incidence of infections in patients with chronic inflammatory rheumatic disease is increased. It is often due to the disease itself and to the immunosuppressive treatments used. Objectives: To assess the incidence of infections during JIA. Methods: We conducted a repeated cross-sectional study including 29 patients followed for JIA according to the International League of Associations for Rheumatology (ILAR) criteria over a period from 1994 to 2022. Sociodemographic and anthropometric parameters, clinical data, biological assessments, and prescribed therapies were collected. We identified patients who had at least one infectious episode during their follow-up. Results: There were 17 women and 12 men. The mean age was 35.69 ± 11.72 [18–61] years. The polyarticular form was seen in 55.2% of cases. The mean age of disease onset was 11.10 ± 4.25 [2–16] years. The average disease duration was 24.48 ± 12.76 [1–47] years.Diabetes and arterial hypertension were the main comorbidities associated with JIA, observed in 13.8% of cases each. At least one extra-articular manifestation was noted in 16 cases: pulmonary (3 cases), cardiac (4 cases), renal (2 cases), cutaneous (4 cases) and ocular (7 cases).The most prescribed DMARDs was Methotrexate in 79.3% (n = 23), biotherapy was used in 3 (10.3%), NSAIDs and corticosteroids were used in 62.1% (n = 18) and 69% (n = 20) respectively.All the infections observed in our population were of community origin. Urinary tract infection was the most common infection (n = 5). Bronchopulmonary infections were observed in 2 cases including a case of tuberculosis. Sub periosteal abscess of the femur was also seen in one of the patients.Regarding the SARS-CoV-2 infection, 6 patients were infected, 2 of whom required hospitalization, including one in the intensive care. Conclusion: The risk of infections is increased during JIA. This is due to the immunosuppression induced by the disease, the treatment, and comorbidities.
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Background: Vaccine hesitancy is defned by the OMS as 'a delay in acceptance or refusal of vaccines despite availability of vaccination services' [1], and it is considered as one of threats to global health. This hesitancy emerges around Covid-19 vaccination. Patients on biologic Disease-Modifying Anti-Rheumatic Drug (bDMARD) are vulnerable to Covid-19 infection and their perception to vaccination is unknown. Objectives: The aim of our study was to identify Covid-19 vaccine hesitancy among rheumatoid arthritis (RA) patient on bDMARD. Methods: We conducted a monocentric, cross-sectional study, including patients with RA who met the ACR/EULAR 2010 criteria. All patients were on bDMARD with or without conventional synthetic (Cs) DMARD for at least 3 months. Disease activity was assessed using the Disease Activity Score (DAS) 28 (CRP) and the functional impairment using the Health Assessment Questionnaire (HAQ). A structured interview was done using a prepared questionnaire evaluating their vaccine hesitancy behavior. Results: We enrolled 60 patients: 10 male (16.7%) and 50 females (83.3%). Their average age was 58.16±9.04 years [34-80]. For the education level;38.5% of patients were illiterate, 34.6% had primary education, 23.1% had secondary education, and 3.8% have a university degree. Forty-four patients (73.3%) had no occupation, 13 patients (21.7%) were employed, and 5% were retired. The majority of patients lived in urban areas (85%) and 98.2% with their families. The average duration of RA was 15.23±8.92 years [2-39]. The average DAS28 (CRP) and the average HAQ were 4.05±1.22 [1.5-7.2] and 0.7±0.4 [0-2.4], respectively. Fifteen patients (25%) had a high disease activity and seven (11.7%) were in remission. When asking patients about their Covid19 infection and vaccination status;15% had caught the virus and 61.7% have already received the vaccine. One third (35.6%) believed that they had enough information about vaccination. Their main sources were their family, friends, and the media. More than half of the asked patients (68.3%) reported vaccine hesitancy. Reasons of vaccine hesitancy were divided into three categories: lack of confdence (66.7%, p<0.005) (63.3% fear related to side effects, 10% conspiracy theory, 6.7% lack of confdence in the provider), complacency problem (16.7%, p=0.01) and lack of convenience (8.6%). There was no association between vaccine hesitancy and sociodemographic data. The existence of comorbidities had no influence on vaccine hesitancy (p=0.4). This hesitancy was not associated with DAS28 (CRP) (p=0.6) and with HAQ (p=0.7). Patients with moderate to high disease activity were more likely to deny the usefulness of Covid-19 vaccination (p=0.09). Regarding to the therapeutic data, there was no association between corticotherapy and vaccine hesitancy (p=0.1). There was no influence on the type of the current bDMARD (p=0.3) or of the rate of administration (p=0.4). The route of administration was associated with hesitation (53.65% intravenous vs 46.34% subcutaneous, p=0.04). Conclusion: Our study showed that Covid-19 vaccination coverage among RA patients on bDMARDs was not optimal with a high percentage of hesitancy. The reasons are complex and they may be related to a lack of awareness. Rheuma-tologists should play a key role in the vaccine company.
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Les patients suivis pour un rhumatisme inflammatoire chronique tel que la polyarthrite rhumatoïde (PR) sont vulnérables aux infections. Durant la période de la Covid-19, le problème de l'adhésion au traitement biologique chez cette population a été soulevé. L'objectif de notre étude était d'identifier le degré d'adhésion au biologique chez une population de patients suivis pour une PR durant la période de la pandémie Covid-19 et de déterminer l'influence des comorbidités sur cette adhésion. Il s'agit d'une étude transversale incluant des patients atteints d'une PR recevant un traitement biologique depuis au moins trois mois. L'adhésion au traitement biologique a été évaluée à l'aide d'une question directe posée aux patients portant sur la prise régulière du traitement biologique en cours comme prescrite par le médecin (adhésion auto-déclarée). Les données de l'étude ont été saisies et analysées au moyen du logiciel Statistical Package for Social Sciences (SPSS) version 23.0. Le seuil de signification (p) a été fixé à 0,05. Ils s'agissaient de 75 patients atteints de PR sous traitement biologique répartis en 60 femmes (80 %) et 15 hommes (20 %). Le sex-ratio était de 0,25. L'âge moyen des patients était 56,92 ± 9,06 ans. La tranche d'âge la plus représentée était celle des 50–59 ans. Trente-trois pour cent des patients étaient non instruits. Vingt patients avaient une activité professionnelle. La durée moyenne d'évolution de la PR était 14,85 ± 8,5 ans. Des comorbidités ont été relevées chez 36 patients (48 %). Ils étaient répartis comme suit : diabète (n = 22), HTA (n = 13, dyslipidémie (n = 13), maladie gastro-intestinale (n = 4), hypothyroïdie (n = 2), accident-vasculaire cérébral (n = 2) et fibrillation auriculaire (n = 1). Au moment de l'étude, l'activité moyenne de la maladie mesurée par le DAS28 CRP était 4,08 ± 1,3 chez les patients ayant des comorbidités et 3,81 ± 1,3 chez les patients sans comorbidités. La présence de comorbidités n'avait pas d'influence sur l'activité de la maladie (p = 0,690). Concernant le traitement de fond biologique actuel, les molécules les plus prescrites étaient l'Infliximab (22,7 %), le Certolizumab (22,7 %) et le Tocilizumab (22,7 %). La durée moyenne de prise du traitement biologique actuel était similaire dans les 2 groupes (comorbidités (+) : 38,91 ± 48,59 mois vs comorbidités (−) : 35,56 ± 29,14 mois, p = 0,206). L'infection par le Covid-19 était observée seulement dans le groupe comorbidités (−). La couverture vaccinale anti-Covid-19 était comme suit : 46 % dans le groupe comorbidités (+) vs 54 % dans le groupe comorbidités (−) sans différence significative (p = 0,752). L'adhésion au traitement biologique était auto-déclarée par 94 % des patients comorbidités (+) vs 95 % des patients comorbidités (−). Cette adhésion n'était pas statistiquement différente entre les 2 groupes (p = 0,934). Notre étude a montré que la présence de comorbidités n'a pas empêché les patients PR de continuer de prendre leur biologique durant la période de la pandémie Covid-19. (French) [ FROM AUTHOR] Copyright of Revue de Médecine Interne is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Covid-19 pandemic detection is the key to health safety and coronavirus prevention. Due to the complex changes in CT scan treatment, it is difficult to identify the Covid-19 in the lung image. According to the latest clinical research, an automated fast framework is still required to resolve error prone problem from the pandemic assessment and Covid19 patients screening during this critical control period. Computer aided methods can be very useful in this regard. They are suitable to estimate the infected lung boundary based on elliptical Hough transform with reduced time processing. In this paper, we propose to use a computerized approach to show that the deep neural network (DNN) is a distinctive method to classify Covid-19 pandemic. Experimental results on various lung CT scan images of different Covid-19 patients, demonstrate the effectiveness of the proposed methodology when compared to the manual scoring of pathological experts. According to the performance evaluation, we recorded more than 92% for accuracy of infection detected in ROI scoring over the truths provided by experienced radiologists. Comparative automatic studies are performed to demonstrate the suitability of the proposed technique over other advanced techniques from the literature.