Analise Dos Motivos De Inaptidao De Candidatos a Doacao De Sangue No Banco De Sangue De Brasilia

Introducao: O Banco de Sangue de Brasilia do Grupo GSH foi inaugurado em outubro de 2021 com o objetivo de coletar sangue e hemocomponentes por aferese para suprir a demanda transfusional de seis agencias transfusionais localizadas em Hospitais do Distrito Federal. No processo de doacao de sangue, a triagem clinica consiste em etapa importante que visa garantir a seguranca de doadores e receptores de sangue atraves de questoes sobre antecedentes pessoas e patologicos. Objetivo: O presente trabalho tem o objetivo de analisar os principais motivos de inaptidao clinica dos candidatos a doacao de sangue e hemocomponentes por aferese no Banco de Sangue de Brasilia do Grupo GSH no periodo de outubro de 2021 a junho de 2022. Material e metodos: Estudo restrospectivo atraves da analise de dados de relatorios emitidos pelo sistema informatizado institucional. Resultados: No periodo de outubro de 2021 a junho de 2022 tivemos um total de 7796 candidatos a doacao de sangue, deste total 987 (12,66%) foram inaptos na triagem clinica. A avaliacao dos doadores quanto ao genero evidenciou que 585 (59,27%) era do sexo masculino e 402 (40,62%) do sexo feminino. Os principais motivos de inaptidao na triagem clinica foram: uso de medicamentos (31,9%), parceiros sexuais, incluindo numero e fatores de risco dos parceiros (12,66%), historico de cirurgias e procedimentos endoscopicos (10,73%), historico de doencas auto-imunes, epilepsias, diabetes em uso de insulina (8,40%), tatuagens, piercings, micropigmentacao (5,67%), infeccoes recentes(3,03%). Uso de vacinas, contato com pessoas e antecedente de covid, canceres e anemias representaram 2,02% cada um. Evidenciamos que quanto ao genero, as inaptidoes clinicas predominantes no sexo masculino foram uso de medicamentos e parceiros sexuais. Inaptidoes por antecedentes de tatuagens, piercings, micropigmentacao, cirurgias e procedimentos endoscopicos foram mais frequentes no sexo feminino. Quanto a periodicidade das recusas clinicas, percebemos um aumento significativo do numero de inaptidoes por infeccoes respiratorias no mes de Junho de 2022 quando comparado com o mes anterior 14,35% e 2,7%, respectivamente e que uso de medicamentos foi o motivo de maior recusa em todos os meses avaliados. Discussao: Apesar do pouco tempo de funcionamento do Banco de sangue de Brasilia, evidenciamos que existe maior numero de doadores inaptos do sexo masculino pelo uso de medicamento e que pode existir sazonalidade da inaptidao clinica por infeccoes respiratorias. Os motivos mais frequentes podem ser reforcados em material explicativo aos doadores, minimizando o tempo de atendimento e evitar a ida de doadores ao banco de sangue com inaptidoes clinicas. Conclusao: O conhecimento dos principais motivos de inaptidao clinica auxilia no gerenciamento do processo, tornando-o mais eficiente e agil e materiais informativos e uma ferramenta relevante para auxilio no atendimento aos doadores de sangue. Copyright © 2022

Sleep quality in patients in the rehabilitation phase after COVID-19 diagnosis

Introduction: The inflammatory process and multisystemic manifestation caused by Covid-19 infection can involve multiple sequelae with damage on physical, cognitive, psychological, and biological aspects. This condition results on poor quality of life, fatigue, dyspnea and sleep difficulties. The focus on sleep difficulties, the most common symptoms are related to night drowsiness and insomnia, but little is known about the clinical characteristics of these patients who develop this complication. Objective: Evaluate the main complaints and clinical signs in patients after COVID-19. - Rate the quality of sleep in post-COVID-19 Syndrome patients who have had mild, moderate and/or severe symptoms of the disease. Methods: Observational study and descriptive, with a quantitative approach to data. A general and a specific sleep quality questionnaire were applied to patients undergoing rehabilitation after the diagnosis of COVID-19, who did or did not need to be hospitalized, with symptoms that had started at least 5 weeks before the questionnaire response date. Participants who were unable to answer the questionnaires due to a deficit in understanding the questions asked, or who gave up on completing the questionnaires without finishing, were excluded. Results: 177 participants participated in the research, 124 men (70%) and 53 women (30%). 62.7% of participants reported at least one comorbidity and only 23 people (12.9%) were not vaccinated with any dose until participation in this study. With regard to hospital admission, 109 participants (61.6%) required admission to the ICU and of these, 57.8% (63) required orotracheal intubation, with prolonged hospital stay for more than 12 days. The most common symptoms after covid-19 were muscle fatigue (78.3%), excessive daytime sleepiness (51.4%), persistent cough (47.4%) and headache (47.1%). 81.4% of participants reported that they felt their sleep quality had worsened after the diagnosis of COVID-19. And after applying a specific questionnaire (PSQI), 93.7% of participants were classified as poor sleepers. There was a very strong correlation (r>0.9) with participants who assessed hospitalized and in invasive mechanical ventilation, with bad sleep quality. Conclusion: The post-COVID-19 Syndrome, associated with age, comorbidities, length of stay and use of invasive mechanical ventilation, were factors that are associated with a higher prevalence of sleep disorders.

Agile Computational Intelligence for Supporting Hospital Logistics During the COVID-19 Crisis

This chapter describes a case study regarding the use of ‘agile’ computational intelligence for supporting logistics in Barcelona’s hospitals during the COVID-19 crisis in 2020. Due to the lack of sanitary protection equipment, hundreds of volunteers, the so-called “Coronavirus Makers” community, used their home 3D printers to produce sanitary components, such as face covers and masks, which protect doctors, nurses, patients, and other civil servants from the virus. However, an important challenge arose: how to organize the daily collection of these items from individual homes, so they could be transported to the assembling centers and, later, distributed to the different hospitals in the area. For over one month, we have designed daily routing plans to pick up the maximum number of items in a limited time—thus reducing the drivers’ exposure to the virus. Since the problem characteristics were different each day, a series of computational intelligence algorithms was employed. Most of them included flexible heuristic-based approaches and biased-randomized algorithms, which were capable of generating, in a few minutes, feasible and high-quality solutions to quite complex and realistic optimization problems. This chapter describes the process of adapting several of our ‘heavy’ route-optimization algorithms from the scientific literature into ‘agile’ ones, which were able to cope with the dynamic daily conditions of real-life routing problems. Moreover, it also discusses some of the computational aspects of the employed algorithms along with several computational experiments and presents a series of best practices that we were able to learn during this intensive experience. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

GOVERNMENT FINANCIAL RESILIENCE AND COPING WITH COVID-19

Governmental financial resilience is characterized by the way in which government entities face and recover from financial crises or shocks, being manifested from interactive dimensions. In view of the shock generated by COVID-19, the present research seeks to assess whether vulnerability and the ability to anticipate (resilience proxies) are correlated with the ability to cope with the virus (measured by the number of tests per inhabitant). To determine possible correlations, Spearman's correlation test was used, since the sample did not respect normality in its distribution, to measure the relationship between variables. The evidence points to a negative correlation between the dependence on intergovernmental transfer (vulnerability) and the ability to generate savings (anticipation capacity) and the capacity to cope with COVID-19. Despite methodological limitations, the research provides a potential contribution to advancing the observation of the interaction between the financial and social aspects of resilience, especially in view of the role that accounting plays in shaping different forms and paths for government financial resilience, providing answers short- or long-term shocks, anticipating them through planning and control mechanisms, which can contribute to the development of governance practices based on this literature.