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O Atlas Brasileiro Online de Doenças Raras é um serviço da Rede Nacional de Doenças Raras. Ele foi criado para disseminar informações sobre epidemiologia, quadro clínico, recursos diagnósticos e terapêuticos usados, e custos relacionados a doenças raras de origem genética e não genética no Brasil.
As doenças raras podem ser definidas como aquelas que afetam até 65 pessoas em cada 100 mil, ou seja, 1,3 pessoas para cada 2.000 indivíduos. No Brasil, estima-se que cerca de treze milhões de pessoas possuem alguma doença rara.
Após coletar, armazenar, processar e analisar os dados provenientes do projeto Rede Nacional de Doenças Raras, produzimos e publicamos estudos científicos para revistas e conferências científicas nacionais e internacionais.
Portanto, bem-vindo(a) a nossa lista de publicações. Essas publicações científicas representam um esforço contínuo para o entendimento e a explicação de fenômenos na área das doenças raras.
Esses esforços visam fornecer subsídios úteis e relevantes para a tomada de decisão baseadas em evidências no campo das doenças raras. Corroborando assim para o cumprimento dos objetivos gerais e específicos deste projeto.
Perfil Das Doenças Raras Em Um Centro De Referência Em Genética Clínica
Ana Mondadori Dos Santos, et al.
Oliveira BM, Baiochi JF, Milke JC, Lorea CF, Viegas I, Bernardi FA, Alves D, Schwartz IVD, Félix TM, RARAS Network Group
BACKGROUND: Inborn errors of metabolism (IEM) present significant challenges in diagnosis and management. The Brazilian Rare Diseases Network (BRDN) is a consortium of 40 healthcare centers from all five regions of Brazil established in 2020, designed to perform an epidemiological survey on rare diseases (RD). This study aims to present comprehensive data on patients with IEM assisted in the centers of BRDN, including their clinical profiles, diagnosis, and treatments applied. METHODS: We conducted a comprehensive review of all cases with confirmed or suspected IEM in BRDN. Selection criteria were established using the Rare IEM classification from Orphadata (v. Dec 4, 2023, https: //www.orphadata.com/classifications/), incorporating ICD-10, OMIM, and Orpha diagnostic codes. A retrospective (2018-2019) and prospective (2022-2024) data collection was conducted using a RedCap standard form. RESULTS: Of 19,307 total records at BRDN, 2,667 (13.8%) IEM cases were registered (retrospective phase: 1,798/12,285; prospective phase: 870/7022). Most participants (32.4%) lived in the Southeast region of Brazil. The mean age at inclusion was 18.0 years (±15.5), and 1,402 (52.6%) were female. Diagnosis of IEM was confirmed in 88.3% and suspected in 11.7%. For RD coding, Orpha was mostly (71.4%) used. The most frequent diagnoses were Phenylketonuria (PKU, n=762), Mucopolysaccharidosis (MPS) type 2 (n=102), Fabry disease (n=95), MPS type 6 (n=89) and Gaucher disease (n=86). Biochemical diagnosis was performed in 66.6% of cases, molecular diagnosis was conducted in 25.7%, and the remaining cases were categorized as Others. Only 26.2% were diagnosed through newborn screening. The most recorded Human Phenotype Ontology were: Reduced phenylalanine hydroxylase level, Seizure, and Hyperphenylalaninemia. Positive family history was registered in 27.1% and 16.5% reported consanguinity. In the retrospective phase, specific treatment for IEM was reported in 71.6% of cases. Within the overall cohort, 41.2% received diet therapy. Previous hospitalizations were documented in 88.3%. The mortality rate was 1.8% during the retrospective phase. CONCLUSIONS: This study shows the first Brazilian nationwide data on IEM, demonstrating the importance of networking between specialized RD centers. PKU is included in the Brazilian Newborn Screening Program, leading to higher diagnostic prevalence. This data may contribute to improving the assistance of IEM in Brazil.
Domingos Alves, Diego Bettiol Yamada, Filipe Andrade Bernardi, Isabelle Carvalho, Márcio Eloi Colombo Filho, Mariane Barros Neiva, Vinícius Costa Lima, Têmis Maria Félix
Abstract Background: A rare disease is a medical condition with low prevalence in the general population, but these can collectively affect up to 10% of the population. Thus, rare diseases have a significant impact on the health care system, and health professionals must be familiar with their diagnosis, management, and treatment. Objective: This paper aims to provide health indicators regarding the rare diseases in Brazil and to create a network of reference centers with health professionals from different regions of the country. RARASnet proposes to map, analyze, and communicate all the data regarding the infrastructure of the centers and the patients' progress or needs. The focus of the proposed study is to provide all the technical infrastructure and analysis, following the World Health Organization and the Brazilian Ministry of Health guidelines. Methods: To build this digitized system, we will provide a security framework to assure the privacy and protection of each patient when collecting data. Systems development life cycle methodologies will also be applied to align software development, infrastructure operation, and quality assurance. After data collection of all information designed by the specialists, the computational analysis, modeling, and results will be communicated in scientific research papers and a digital health observatory. Results: The project has several activities, and it is in an initial stage. Initially, a survey was given to all health care centers to understand the technical aspects of each network member, such as the existence of computers, technical support staff, and digitized systems. In this survey, we detected that 59% (23/39) of participating health units have electronic medical records, while 41% (16/39) have paper records. Therefore, we will have different strategies to access the data from each center in the data collection phase. Later, we will standardize and analyze the clinical and epidemiological data and use these data to develop a national network for monitoring rare diseases and a digital health observatory to make the information available. The project had its financing approved in December 2019. Retrospective data collection started in October 2020, and we expect to finish in January 2021. During the third quarter of 2020, we enrolled 40 health institutions from all regions of Brazil. Conclusions: The nature of rare disease diagnosis is complex and diverse, and many problems will be faced in the evolution of the project. However, decisions based on data analysis are the best option for the improvement of the rare disease network in Brazil. The creation of RARASnet, along with all the digitized infrastructure, can improve the accessibility of information and standardization of rare diseases in the country.
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Ministério da Saúde do Brasil
Conselho Nacional de Desenvolvimento Científico e Tecnológico
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