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Introduction: Stevens-Johnson syndrome (SJS) is caused by a delayed immune response triggered by the association of genetic and environmental factors. This reaction can be mediated mainly by some drugs. Objective: The purpose of this article is to report the case of a patient with SJS associated with carbamazepine. Case report: A man was hospitalized complaining of odynophagia, whitish plaques in the mouth and swelling of the lips. Clinical examination revealed ulcerated and erosive lesions involving the buccal mucosa, lips, tongue and hard palate. The lips were swollen and with hemorrhagic crusts. Papular and purplish-colored lesions were observed on the skin. The patient reported that the lesions started 10 days ago, coinciding with the start of carbamazepine use. The diagnosis of SJS was established based on clinical information and the patient treated with support therapy. Conclusion: SJS is a clinical condition that affects the oral mucosa and can be triggered by the use of carbamazepine. (AU)

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The SARS-CoV-2 virus was first registered in Brazil by the end of February 2020. Since then, the country counts over 150000 deaths due to COVID-19 and faces a profound social and economic crisis; there is also an ongoing health catastrophe, with the majority of hospital beds in many Brazilian cities currently occupied with COVID-19 patients. Thus, a Nonlinear Model Predictive Control (NMPC) scheme used to plan appropriate social distancing measures (and relaxations) in order to mitigate the effects of this pandemic is formulated in this paper. The strategy is designed upon an adapted data-driven Susceptible-Infected-Recovered-Deceased (SIRD) model, which includes time-varying auto-regressive immunological parameters. A novel identification procedure is proposed, composed of analytical regressions, Least-Squares optimization and auto-regressive model fits. The adapted SIRD model is validated with real data and able to adequately represent the contagion curves over large forecast horizons. The NMPC strategy is designed to generate piecewise constant quarantine guidelines, which can be reassessed (relaxed/strengthened) each week. Simulation results show that the proposed NMPC technique is able to mitigate the number of infections and progressively loosen social distancing measures. With respect to a "no-control" condition, the number of deaths could be reduced in up to 30% if the proposed NMPC coordinated health policy measures are enacted.

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The SARS-CoV-2 pandemic triggered substantial economic and social disruptions. Mitigation policies varied across countries based on resources, political conditions, and human behavior. In the absence of widespread vaccination able to induce herd immunity, strategies to coexist with the virus while minimizing risks of surges are paramount, which should work in parallel with reopening societies. To support these strategies, we present a predictive control system coupled with a nonlinear model able to optimize the level of policies to stop epidemic growth. We applied this system to study the unfolding of COVID-19 in Bahia, Brazil, also assessing the effects of varying population compliance. We show the importance of finely tuning the levels of enforced measures to achieve SARS-CoV-2 containment, with periodic interventions emerging as an optimal control strategy in the long-term.

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The COVID-19 pandemic is the defying crisis of our time. Since mass vaccination has not yet been established, countries still have been facing many issues due to the viral spread. Even in cities with high seroprevalence, intense resurgent waves of COVID-19 have been registered, possibly due to viral variants with greater transmission rates. Accordingly, we develop a new Model Predictive Control (MPC) framework that is able to determine social distancing guidelines and altogether provide estimates for the future epidemiological characteristic of the contagion. For such, the viral dynamics are represented through a Linear Parameter Varying (LPV) version of the Susceptible-Infected-Recovered-Deceased (SIRD) model. The solution of the LPV MPC problem is based on a Sequential Quadratic Program (SQP). This SQP provides convergent estimates of the future LPV scheduling parameters. We use real data to illustrate the efficiency of the proposed method to mitigate this contagion while vaccination is ongoing.

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This paper formulates a Model Predictive Control (MPC) policy to mitigate the COVID-19 contagion in Brazil, designed as optimal On-Off social isolation strategy. The proposed optimization algorithm is able to determine the time and duration of social distancing policies in the country. The achieved results are based on data from the period between March and May of 2020, regarding the cumulative number of infections and deaths due to the SARS-CoV-2 virus. This dataset is assumably largely sub-notified due to the absence of mass testing in Brazil. Thus, the MPC is based on a SIR model which is identified using an uncertainty-weighted Least-Squares criterion. Furthermore, this model includes an additional dynamic variable that mimics the response of the population to the social distancing policies determined by the government, which affect the COVID-19 transmission rate. The proposed control method is set within a mixed-logical formalism, since the decision variable is forcefully binary (existence or the absence of social distance policy). A dwell-time constraint is included to avoid too frequent shifts between these two inputs. The achieved simulation results illustrate how such optimal control method would operate in practice, pointing out that no social distancing should be relaxed before mid August 2020. If relaxations are necessary, they should not be performed before this date and should be in small periods, no longer than 25 days. This paradigm would proceed roughly until January/2021. The results also indicate a possible second peak of infections, which has a forecast to the beginning of October. This peak can be reduced if the periods of days with relaxed social isolation measures are shortened.

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Propósito: El objetivo de nuestro trabajo consiste en describir colecciones grasas relacionadas con la vena cava inferior, describir sus causas y realizar una revisión de la literatura. Material y métodos: Se realizaron entre los meses de mayo de 2000 y marzo de 2001, dos mil tomografías toracoabdominales por diferentes patologías. Los estudios fueron llevados a cabo en un equipo PQ 5000 helicoidal, con y sin contraste endovenoso. Resultados: Se encontraron tres casos de colecciones grasas relacionadas con la vena cava inferior a nivel intrahepático. Los cortes axiales mostraron colecciones proyectadas sobre la pared posteromedial y anteromedial de la vena cava inferior. Conclusiones: El hallazgo de pequeñas colecciones de grasa relacionadas con la vena cava inferior, son hallazgos incidentales benignos. Deberían tenerse en cuenta como diagnóstico diferencial, ante la sospecha de trombosis de la vena cava, tumores primarios con contenido graso o extensiones tumorales secundarias (AU)

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Propósito: El objetivo de nuestro trabajo consiste en describir colecciones grasas relacionadas con la vena cava inferior, describir sus causas y realizar una revisión de la literatura. Material y métodos: Se realizaron entre los meses de mayo de 2000 y marzo de 2001, dos mil tomografías toracoabdominales por diferentes patologías. Los estudios fueron llevados a cabo en un equipo PQ 5000 helicoidal, con y sin contraste endovenoso. Resultados: Se encontraron tres casos de colecciones grasas relacionadas con la vena cava inferior a nivel intrahepático. Los cortes axiales mostraron colecciones proyectadas sobre la pared posteromedial y anteromedial de la vena cava inferior. Conclusiones: El hallazgo de pequeñas colecciones de grasa relacionadas con la vena cava inferior, son hallazgos incidentales benignos. Deberían tenerse en cuenta como diagnóstico diferencial, ante la sospecha de trombosis de la vena cava, tumores primarios con contenido graso o extensiones tumorales secundarias

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