Utilization of machine learning for dengue case screening.

Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern. To address this, artificial intelligence tools like machine learning can play a crucial role in developing more effective strategies for control, diagnosis, and treatment. This study identifies relevant variables for the screening of dengue cases through machine learning models and evaluates the accuracy of the models. Data from reported dengue cases in the states of Rio de Janeiro and Minas Gerais for the years 2016 and 2019 were obtained through the National Notifiable Diseases Surveillance System (SINAN). The mutual information technique was used to assess which variables were most related to laboratory-confirmed dengue cases. Next, a random selection of 10,000 confirmed cases and 10,000 discarded cases was performed, and the dataset was divided into training (70%) and testing (30%). Machine learning models were then tested to classify the cases. It was found that the logistic regression model with 10 variables (gender, age, fever, myalgia, headache, vomiting, nausea, back pain, rash, retro-orbital pain) and the Decision Tree and Multilayer Perceptron (MLP) models achieved the best results in decision metrics, with an accuracy of 98%. Therefore, a tree-based model would be suitable for building an application and implementing it on smartphones. This resource would be available to healthcare professionals such as doctors and nurses.

Recommendations by the Scientific Department of Neuroimmunology of the Brazilian Academy of Neurology (DCNI/ABN) and the Brazilian Committee for Treatment and Research in Multiple Sclerosis and Neuroimmunological Diseases (BCTRIMS) on vaccination in general and specifically against SARS-CoV-2 for patients with demyelinating diseases of the central nervous system.

The Scientific Department of Neuroimmunology of the Brazilian Academy of Neurology (DCNI/ABN) and Brazilian Committee for Treatment and Research in Multiple Sclerosis and Neuroimmunological Diseases (BCTRIMS) provide recommendations in this document for vaccination of the population with demyelinating diseases of the central nervous system (CNS) against infections in general and against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. We emphasize the seriousness of the current situation in view of the spread of COVID-19 in our country. Therefore, reference guides on vaccination for clinicians, patients, and public health authorities are particularly important to prevent some infectious diseases. The DCNI/ABN and BCTRIMS recommend that patients with CNS demyelinating diseases (e.g., MS and NMOSD) be continually monitored for updates to their vaccination schedule, especially at the beginning or before a change in treatment with a disease modifying drug (DMD). It is also important to note that vaccines are safe, and physicians should encourage their use in all patients. Clearly, special care should be taken when live attenuated viruses are involved. Finally, it is important for physicians to verify which DMD the patient is receiving and when the last dose was taken, as each drug may affect the induction of immune response differently.

Recommendations by the Scientific Department of Neuroimmunology of the Brazilian Academy of Neurology (DCNI/ABN) and the Brazilian Committee for Treatment and Research in Multiple Sclerosis and Neuroimmunological Diseases (BCTRIMS) on vaccination in general and specifically against SARS-CoV-2 for patients with demyelinating diseases of the central nervous system / Recomendações do Departamento Científico de Neuroimunologia da Academia Brasileira de Neurologia (DCNI/ABN) e do Comitê Brasileiro de Tratamento e Pesquisa em Esclerose Múltipla e Doenças Neuroimunológicas (BCTRIMS) sobre vacinação em geral e contra a SARS-CoV-2 para pacientes com doenças desmielinizantes do sistema nervoso central

ABSTRACT The Scientific Department of Neuroimmunology of the Brazilian Academy of Neurology (DCNI/ABN) and Brazilian Committee for Treatment and Research in Multiple Sclerosis and Neuroimmunological Diseases (BCTRIMS) provide recommendations in this document for vaccination of the population with demyelinating diseases of the central nervous system (CNS) against infections in general and against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. We emphasize the seriousness of the current situation in view of the spread of COVID-19 in our country. Therefore, reference guides on vaccination for clinicians, patients, and public health authorities are particularly important to prevent some infectious diseases. The DCNI/ABN and BCTRIMS recommend that patients with CNS demyelinating diseases (e.g., MS and NMOSD) be continually monitored for updates to their vaccination schedule, especially at the beginning or before a change in treatment with a disease modifying drug (DMD). It is also important to note that vaccines are safe, and physicians should encourage their use in all patients. Clearly, special care should be taken when live attenuated viruses are involved. Finally, it is important for physicians to verify which DMD the patient is receiving and when the last dose was taken, as each drug may affect the induction of immune response differently.

RESUMO O DC de Neuroimunologia da ABN e o BCTRIMS trazem, nesse documento, as recomendações sobre vacinação da população com doenças desmielinizantes do sistema nervoso central (SNC) contra infecções em geral e contra o coronavírus da síndrome respiratória aguda grave 2 (SARS-CoV-2), causador da COVID-19. Destaca-se a gravidade do atual momento frente ao avanço da COVID-19 em nosso País, o que torna mais evidente e importante a criação de guia de referência para orientação aos médicos, pacientes e autoridades de saúde pública quanto à vacinação, meio efetivo e seguro no controle de determinadas doenças infecciosa. O DCNI/ABN e o BCTRIMS recomendam que os pacientes com doenças desmielinizantes do SNC (ex., EM e NMOSD) sejam constantemente monitorados, quanto a atualização do seu calendário vacinal, especialmente, no início ou antes da mudança do tratamento com uma droga modificadora de doença (DMD). É importante também salientar que as vacinas são seguras e os médicos devem estimular o seu uso em todos os pacientes. Evidentemente, deve ser dada especial atenção às vacinas com vírus vivos atenuados. Por fim, é importante que os médicos verifiquem qual DMD o paciente está em uso e quando foi feita a sua última dose, pois cada fármaco pode interagir de forma diferente com a indução da resposta imune.

Prevalence of multiple sclerosis in Goiânia, Goiás, Brazil.

OBJECTIVE: Multiple sclerosis (MS) prevalence, in some cities in Brazil, was estimated and was found to range from 0.75 to 30.7/100,000. The reasons for such a large variation in rates of prevalence are not clear, but environment and genetics help to explain this phenomenon. METHODS: A cross-sectional study using three sources of case ascertainment to estimate the prevalence of MS in the city of Goiânia in December, 2015. RESULTS: A total of 318 MS patients was found after removing overlapping sources. The prevalence of MS was 22.4/100,000 population. CONCLUSION: Our study was the first in Goiás and the third in the midwest region, and we found a great increase in the prevalence of MS in the region. It is necessary to perform other studies using the same methodology for a more accurate evaluation of the true prevalence of MS in Brazil.

Prevalence of multiple sclerosis in Goiânia, Goiás, Brazil / Prevalência de esclerose múltipla em Goiânia, Goiás, Brasil

ABSTRACT Multiple sclerosis (MS) prevalence, in some cities in Brazil, was estimated and was found to range from 0.75 to 30.7/100,000. The reasons for such a large variation in rates of prevalence are not clear, but environment and genetics help to explain this phenomenon. Methods: A cross-sectional study using three sources of case ascertainment to estimate the prevalence of MS in the city of Goiânia in December, 2015. Results: A total of 318 MS patients was found after removing overlapping sources. The prevalence of MS was 22.4/100,000 population. Conclusion: Our study was the first in Goiás and the third in the midwest region, and we found a great increase in the prevalence of MS in the region. It is necessary to perform other studies using the same methodology for a more accurate evaluation of the true prevalence of MS in Brazil.

RESUMO A prevalência de esclerose múltipla (EM) no Brasil foi estimada em algumas cidades e foi encontrada entre 0,75 e 30,7 / 100.000. As razões para tal grande variação nas taxas de prevalência não são claras, mas existem aspectos ambientais e genéticos para explicar esse fenômeno. Métodos: Foram utilizadas três fontes de averiguação de casos para estimar a prevalência de esclerose múltipla (EM) no município de Goiânia em dezembro de 2015. Resultados: Foram encontrados 318 casos de EM, retirando as sobreposições de fontes. A prevalência foi de 22,4 / 100.000. Conclusão: Nosso estudo foi o primeiro em Goiás e o terceiro na Região Centro-Oeste, e encontrou um grande aumento na prevalência de EM na região. É necessário realizar outros estudos utilizando a mesma metodologia para uma melhor avaliação da real prevalência da EM no Brasil.