High levels of immunosuppression are related to unfavourable outcomes in hospitalised patients with rheumatic diseases and COVID-19 : first results of ReumaCoV Brasil registry

Objectives To evaluate risk factors associated with unfavourable outcomes: emergency care, hospitalisation, admission to intensive care unit (ICU), mechanical ventilation and death in patients with immune-mediated rheumatic disease (IMRD) and COVID-19. Methods Analysis of the first 8 weeks of observational multicentre prospective cohort study (ReumaCoV Brasil register). Patients with IMRD and COVID-19 according to the Ministry of Health criteria were classified as eligible for the study. Results 334 participants were enrolled, a majority of them women, with a median age of 45 years; systemic lupus erythematosus (32.9%) was the most frequent IMRD. Emergency care was required in 160 patients, 33.0% were hospitalised, 15.0% were admitted to the ICU and 10.5% underwent mechanical ventilation; 28 patients (8.4%) died. In the multivariate adjustment model for emergency care, diabetes (prevalence ratio, PR 1.38; 95% CI 1.11 to 1.73; p=0.004), kidney disease (PR 1.36; 95% CI 1.05 to 1.77; p=0.020), oral glucocorticoids (GC) (PR 1.49; 95% CI 1.21 to 1.85; p50 years (PR 1.89; 95% CI 1.26 to 2.85; p=0.002), no use of tumour necrosis factor inhibitor (TNFi) (PR 2.51;95% CI 1.16 to 5.45; p=0.004) and methylprednisolone pulse therapy (PR 2.50; 95% CI 1.59 to 3.92; p<0.001); for ICU admission, oral GC (PR 2.24; 95% CI 1.36 to 3.71; p<0.001) and pulse therapy with methylprednisolone (PR 1.65; 95% CI 1.00 to 2.68; p<0.043); the two variables associated with death were pulse therapy with methylprednisolone or cyclophosphamide (PR 2.86; 95% CI 1.59 to 5.14; p<0.018). Conclusions Age >50 years and immunosuppression with GC and cyclophosphamide were associated with unfavourable outcomes of COVID-19. Treatment with TNFi may have been protective, perhaps leading to the COVID-19 inflammatory process

Results From the Global Rheumatology Alliance Registry

Funding Information: We acknowledge financial support from the ACR and EULAR. The ACR and EULAR were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Publisher Copyright: © 2022 The Authors. ACR Open Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.Objective: Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. Methods: Data were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. Results: The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. Conclusion: We were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression.publishersversionepub_ahead_of_prin

Pharmacologic management of pain in patients with Chikungunya: a guideline

Abstract From the arrival of Chikungunya virus in the Americas in 2013 until March 2016, approximately two million cases of the disease have been reported. In Brazil, the virus was identified in 2014 and thousands of people have been affected. The disease has high attack rates, infecting 50% of a population within a few months. Approximately 50% of infected people develop chronic symptoms lasting for months or years. Joint involvement is the main clinical manifestation of Chikungunya. It is characterized by swelling and intense pain that is poorly responsive to analgesics, both in the acute and chronic phase of the disease. This significantly compromises quality of life and may have immeasurable psychosocial and economic repercussions, constituting therefore, a serious public health problem requiring a targeted approach. Physicians are often not familiar with how to approach the management of pain, frequently prescribing limited analgesics, such as dipyrone, in sub-therapeutic doses. In addition, there are few published studies or guidelines on the approach to the treatment of pain in patients with Chikungunya. Some groups of specialists from different fields have thus developed a protocol for the pharmacologic treatment of Chikungunya-associated acute and chronic joint pain; this will be presented in this review

Pharmacologic management of pain in patients with Chikungunya: a guideline

Abstract From the arrival of Chikungunya virus in the Americas in 2013 until March 2016, approximately two million cases of the disease have been reported. In Brazil, the virus was identified in 2014 and thousands of people have been affected. The disease has high attack rates, infecting 50% of a population within a few months. Approximately 50% of infected people develop chronic symptoms lasting for months or years. Joint involvement is the main clinical manifestation of Chikungunya. It is characterized by swelling and intense pain that is poorly responsive to analgesics, both in the acute and chronic phase of the disease. This significantly compromises quality of life and may have immeasurable psychosocial and economic repercussions, constituting therefore, a serious public health problem requiring a targeted approach. Physicians are often not familiar with how to approach the management of pain, frequently prescribing limited analgesics, such as dipyrone, in sub-therapeutic doses. In addition, there are few published studies or guidelines on the approach to the treatment of pain in patients with Chikungunya. Some groups of specialists from different fields have thus developed a protocol for the pharmacologic treatment of Chikungunya-associated acute and chronic joint pain; this will be presented in this review

Recommendations of the Brazilian Society of Rheumatology for the diagnosis and treatment of chikungunya fever. Part 2 – Treatment

Universidade Federal de Pernambuco. Recife, PE, Brasil; Universidade Federal de Pernambuco. Hospital das Clínicas. Recife, PE, Brasil; Universidade Federal de Pernambuco. Hospital das Clínicas. Serviço de Reumatologia. Recife, PE, Brasil; Instituto de Medicina Integral Professor Fernando Figueira. Recife, PE, Brasil; Hospital Getúlio Vargas. Ambulatório de Chikungunya. Recife, PE, Brasil; Universidade Federal da Paraíba. João Pessoa, PB, Brasil; Universidade Federal da Paraíba. Hospital Universitário Lauro Wanderley. Serviço de Reumatologia. João Pessoa, PB, Brasil; Universidade Estadual de Ciências da Saúde de Alagoas. Maceió, AL, Brasil; Universidade Federal do Rio Grande do Norte. Natal, RN, Brasil; Universidade Federal do Ceará. Faculdade de Medicina. Departamento de Medicina Clínica. Fortaleza, CE, Brasil; Universidade Federal da Bahia. Instituto de Ciências da Saúde. Salvador, BA, Brasil; Universidade Estadual do Piauí. Faculdade de Medicina. Teresina, PI, Brasil; Universidade Federal de Sergipe. Aracaju, SE, Brasil; Universidade do Estado do Rio de Janeiro. Disciplina de Reumatologia. Rio de Janeiro, RJ, Brasil; Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Sérgio Arouca. Rio de Janeiro, RJ, Brasil; Universidade Federal do Rio de Janeiro. Hospital Universitário Clementino Fraga Filho. Rio de Janeiro, RJ, Brasil; Hospital dos Servidores do Estado do Rio de Janeiro. Rio de Janeiro, RJ, Brasil; Hospital Estadual Eduardo Rabello. Serviço de Reumatologia. Rio de Janeiro, RJ, Brasil; Universidade Federal do Amazonas. Faculdade de Medicina. Manaus, AM, Brasil; Universidade Federal de Mato Grosso do Sul. Campo Grande, MS, Brasil; Universidade Federal de Mato Grosso do Sul. Hospital Universitário Maria Aparecida Pedrossian. Serviço de Reumatologia. Campo Grande, MS, Brasil; Universidade de São Paulo. Faculdade de Medicina de Ribeirão Preto. Serviço de Reumatologia e Imunologia Pediátrica. Ribeirão Preto, SP, Brasil; Universidade Federal de São Paulo. São Paulo, SP, Brasil; Universidade de Santo Amaro. São Paulo, SP, Brasil; Universidade de São Paulo. Hospital das Clínicas. Ambulatório da Divisão de Moléstias Infecciosas de Parasitárias. São Paulo, SP, Brasil; Instituto de Medicina Integral Professor Fernando Figueira. Hospital Miguel Arraes. Paulista, PE, Brasil; Universidade Federal de Pernambuco. Hospital das Clínicas. Divisão de Gestão do Cuidado. Recife, PE, Brasil; CRP Fisioterapia. Rio de Janeiro, RJ, Brasil; Universidade Estadual do Piauí. Teresina, PI, Brasil; Sociedade Brasileira de Reumatologia. São Paulo, SP, Brasil; Santa Casa de Misericórdia de Maceió. Maceió, AL, BrasilSubmitted by Fátima Lopes ([email protected]) on 2017-10-24T13:42:18Z No. of bitstreams: 1 RecomendaçõesSociedadeBrasileiraP2.pdf: 984331 bytes, checksum: 9e4f277be0f65c545e7ac6b277aac848 (MD5)Approved for entry into archive by Fátima Lopes ([email protected]) on 2017-10-24T13:58:50Z (GMT) No. of bitstreams: 1 RecomendaçõesSociedadeBrasileiraP2.pdf: 984331 bytes, checksum: 9e4f277be0f65c545e7ac6b277aac848 (MD5)Made available in DSpace on 2017-10-24T13:58:50Z (GMT). No. of bitstreams: 1 RecomendaçõesSociedadeBrasileiraP2.pdf: 984331 bytes, checksum: 9e4f277be0f65c545e7ac6b277aac848 (MD5) Previous issue date: 2017Multipla - ver em NotasA febre chikungunya tem se tornado um importante problema de saúde pública nos países onde ocorrem as epidemias, visto que metade dos casos evolui com artrite crônica, persistente e incapacitante. Os dados na literatura sobre terapêuticas específicas nas diversas fases da artropatia ocasionada pela infecção pelo vírus chikungunya (CHIKV) são limitados, não existem estudos randomizados de qualidade que avaliem a eficácia das diferentes terapias. Há algumas poucas publicações sobre o tratamento das manifestações musculoesqueléticas da febre chikungunya, porém com importantes limitações metodológicas. Os dados atualmente disponíveis não permitem conclusões favoráveis ou contrárias a terapêuticas específicas, bem como uma adequada avaliação quanto à superioridade entre as diferentes medicações empregadas. O objetivo deste trabalho foi elaborar recomendações para o tratamento da febre chikungunya no Brasil. Foi feita uma revisão da literatura com seleção de artigos baseados em evidência, nas bases de dados Medline, SciELO, PubMed e Embase e de resumos de anais de congressos, além da opinião dos especialistas para dar apoio às decisões tomadas para definir as recomendações. Para a definição do grau de concordância foi feita uma metodologia Delphi, em duas reuniões presenciais e várias rodadas de votação on line. Este artigo refere-se à parte 2 das Recomendações da Sociedade Brasileira de Reumatologia para Diagnóstico e Tratamento da Febre Chikungunya, que trata especificamente do tratamento

Recommendations of the Brazilian Society of Rheumatology for diagnosis and treatment of Chikungunya fever. Part 1 - Diagnosis and special situations

Abstract Chikungunya fever has become a relevant public health problem in countries where epidemics occur. Until 2013, only imported cases occurred in the Americas, but in October of that year, the first cases were reported in Saint Marin island in the Caribbean. The first autochthonous cases were confirmed in Brazil in September 2014; until epidemiological week 37 of 2016, 236,287 probable cases of infection with Chikungunya virus had been registered, 116,523 of which had serological confirmation. Environmental changes caused by humans, disorderly urban growth and an ever-increasing number of international travelers were described as the factors responsible for the emergence of large-scale epidemics. Clinically characterized by fever and joint pain in the acute stage, approximately half of patients progress to the chronic stage (beyond 3 months), which is accompanied by persistent and disabling pain. The aim of the present study was to formulate recommendations for the diagnosis and treatment of Chikungunya fever in Brazil. A literature review was performed in the MEDLINE, SciELO and PubMed databases to ground the decisions for recommendations. The degree of concordance among experts was established through the Delphi method, involving 2 in-person meetings and several online voting rounds. In total, 25 recommendations were formulated and divided into 3 thematic groups: (1) clinical, laboratory and imaging diagnosis; (2) special situations; and (3) treatment. The first 2 themes are presented in part 1, and treatment is presented in part 2

Recommendations of the Brazilian Society of Rheumatology for the diagnosis and treatment of chikungunya fever. Part 2 - Treatment

Abstract Chikungunya fever has become an important public health problem in countries where epidemics occur because half of the cases progress to chronic, persistent and debilitating arthritis. Literature data on specific therapies at the various phases of arthropathy caused by chikungunya virus (CHIKV) infection are limited, lacking quality randomized trials assessing the efficacies of different therapies. There are a few studies on the treatment of musculoskeletal manifestations of chikungunya fever, but these studies have important methodological limitations. The data currently available preclude conclusions favorable or contrary to specific therapies, or an adequate comparison between the different drugs used. The objective of this study was to develop recommendations for the treatment of chikungunya fever in Brazil. A literature review was performed via evidence-based selection of articles in the databases Medline, SciELO, PubMed and Embase and conference proceedings abstracts, in addition to expert opinions to support decision-making in defining recommendations. The Delphi method was used to define the degrees of agreement in 2 face-to-face meetings and several online voting rounds. This study is part 2 of the Recommendations of the Brazilian Society of Rheumatology (Sociedade Brasileira de Reumatologia - SBR) for the Diagnosis and Treatment of chikungunya fever and specifically addresses treatment

Development of a Prediction Model for COVID-19 Acute Respiratory Distress Syndrome in Patients With Rheumatic Diseases: Results From the Global Rheumatology Alliance Registry.

ObjectiveSome patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings.MethodsData were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier.ResultsThe study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator.ConclusionWe were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression