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1.
Einstein (Säo Paulo) ; 18: eAO5442, 2020. tab, graf
Article in English | LILACS | ID: biblio-1133738

ABSTRACT

ABSTRACT Objective: To verify if, by three distinct quantifiers, the measured electroencephalographic signal at rest is different from the signal measured during a word reading situation, especially considering the faster rhythms, gamma and high-gamma, as it occurs in clinical rhythms (delta to beta). Methods: A total of 96 electroencephalographic signals measured from neurologically healthy volunteers were evaluated at two moments: resting and word reading. Each signal segment was measured by three quantifiers that separately assess normalized power, percent power, and right and left hemisphere coherence. The Mann-Whitney test was used to compare the results of the quantifiers in each brain range. Results: The gamma and high-gamma rhythms presented a more distinct behavior when comparing the analyzed moments (resting and reading) than the clinical rhythms. Conclusion: This finding contributes to the scarce literature on faster rhythms, which can contain information that is normally disregarded in neurological clinical practice.


RESUMO Objetivo: Verificar se, por meio de três quantificadores distintos, o sinal eletroencefalográfico medido em repouso é diferente do sinal medido durante o processo de leitura, especialmente considerando os ritmos rápidos, gama e supergama, assim como ocorre nos ritmos clínicos delta a beta. Métodos: Foram avaliados 96 sinais eletroencefalográficos medidos em voluntários neurologicamente saudáveis, em dois momentos: repouso e leitura de palavras. Cada trecho do sinal foi mensurado por três quantificadores que medem, de maneira isolada, a potência normalizada e a potência percentual, bem como a coerência entre os hemisférios direito e esquerdo. O teste estatístico de Mann-Whitney foi usado para comparar os resultados dos quantificadores em cada faixa cerebral. Resultados: Os ritmos gama e supergama apresentaram comportamento mais distinto entre os momentos analisados (repouso e leitura) que os ritmos clinicamente analisados. Conclusão: Esse achado contribui com a escassa literatura segundo a qual os ritmos rápidos podem conter informações que normalmente são descartadas na neurologia clínica.


Subject(s)
Reading , Brain/diagnostic imaging , Electroencephalography/methods , Gamma Rhythm , Beta Rhythm , Delta Rhythm
2.
Biosci. j. (Online) ; 35(5): 1640-1650, sept./oct. 2019. ilus, graf, tab
Article in English | LILACS | ID: biblio-1049079

ABSTRACT

This study presents a mathematical model to carry out the demand forecasts in relation to patientes classified as green in the emergency department of a municipality in Minas Gerais, Brazil. In addition, another approach will investigate whether the green patients demand remains the same over the weekend, as compared to the weekdays, since there is no support from Primary Health Care units over the weekend. A retrospective study of the emergency service in the municipality of Monte Carmelo was carried out from January 2014 to December 2017.The time series of the patients classified as green during the host by the nurse, according to the Manchester Triage Scale, was analyzed in the temporal domain for the construction of a parametric model with the purpose of realizing the demand forecast. The Manchester Triage Scale has been adopted in most emergency department as a guiding instrument for risk classification, prioritizing the most serious cases. The data processing was fulfilled using Software R Version 3.4. The ARIMA model (1,1,1)presented a better fit for this forecast. The predictions of this model are values close to those observed for the number of patients seen that ranges from 1780.4 to 1796.6 patients per month. In relation to the demand of patients classified as green at the weekend, it has shown that it is slightly lower than the weekend, but it is still an expressive demand. The application of the models must be seen by the managers as a tool to aid decisions, thus it must support processes of planning, management and evaluation of public policies. In this context, mathematical models for demand forecasting are an instrument for management care and services.


Este estudo apresenta um modelo matemático para realizar as previsões de demanda em relação aos pacientes classificados como verdes no departamento de emergência de um município de Minas Gerais. Além disso, outra abordagem investigará se a demanda dos pacientes verdes permanece a mesma no final de semana, em relação aos dias da semana, uma vez que não há apoio das unidades de Atenção Primária de Saúde no final de semana. Um estudo retrospectivo do serviço de emergência no município de Monte Carmelo foi realizado no período de janeiro de 2014 a dezembro de 2017. A série temporal dos pacientes classificados como verdes durante o acolhimento pelo enfermeiro, segundo o Sistema de Triagem de Manchester, foi analisada no domínio temporal para a construção de um modelo paramétrico com a finalidade de realizar a previsão de demanda. O Sistema de Triagem de Manchester foi adotado na maioria dos serviços de emergência como instrumento orientador para a classificação de risco, priorizando os casos mais graves. O processamento de dados foi realizado usando o Software R Versão 3.4. O modelo ARIMA (1,1,1) apresentou melhor ajuste para essa previsão. As previsões deste modelo são valores próximos aos observados para o número de pacientes atendidos que variam de 1780.4 a 1796.6 pacientes por mês. Em relação à demanda de pacientes classificados como verdes no final de semana, constatou que é ligeiramente inferior a do fim de semana, mas ainda é uma demanda expressiva. A aplicação dos modelos deve ser vista pelos gestores como uma ferramenta para auxiliar as decisões, portanto, deve apoiar processos de planejamento, gestão e avaliação de políticas públicas. Nesse contexto, os modelos matemáticos para previsão de demanda são um instrumento de atendimento e serviços gerenciais.


Subject(s)
Patients , Public Health , Triage , Health Services Accessibility
3.
Rev. Soc. Bras. Med. Trop ; 46(1): 39-44, Jan.-Feb. 2013. graf, tab
Article in English | LILACS | ID: lil-666792

ABSTRACT

INTRODUCTION: Antimicrobial resistance is an increasing threat in hospitalized patients, and inappropriate empirical antimicrobial therapy is known to adversely affect outcomes in ventilator-associated pneumonia (VAP). The aim of this study was to evaluate antimicrobial usage, incidence, etiology, and antimicrobial resistance trends for prominent nosocomial pathogens causing ventilator-associated pneumonia in a clinical-surgical intensive care unit (ICU). METHODS: Gram-negative bacilli and Staphylococcus aureus causing VAP, as well as their antimicrobial resistance patterns and data on consumption (defined daily dose [DDD] per 1,000 patient days) of glycopeptides, extended-spectrum cephalosporins, and carbapenems in the unit were evaluated in two different periods (A and B). RESULTS: Antimicrobial use was high, mainly of broad-spectrum cephalosporins, with a significant increase in the consumption of glycopeptides (p < 0.0001) and carbapenems (p < 0.007) in period B. For Acinetobacter baumannii and members of the Enterobacteriaceae family, 5.27- and 3.06-fold increases in VAPs, respectively, were noted, and a significant increase in resistance rates was found for imipenem-resistant A. baumannii (p = 0.003) and third-generation cephalosporins-resistant Enterobacteriaceae (p = 0.01) isolates in this same period. CONCLUSIONS: Our results suggest that there is a link between antibiotics usage at institutional levels and resistant bacteria. The use of carbapenems was related to the high rate of resistance in A. baumannii and therefore a high consumption of imipenem/meropenem could play a major role in selective pressure exerted by antibiotics in A. baumannii strains.


Subject(s)
Humans , Anti-Bacterial Agents/administration & dosage , Gram-Negative Bacteria/isolation & purification , Gram-Positive Bacteria/isolation & purification , Intensive Care Units/statistics & numerical data , Pneumonia, Ventilator-Associated/microbiology , Critical Care , Cross-Sectional Studies , Drug Resistance, Multiple, Bacterial , Gram-Negative Bacteria/drug effects , Gram-Positive Bacteria/drug effects , Incidence , Inappropriate Prescribing/adverse effects
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