Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Los problemas son divertidos porque los vivimos

Este proyecto tiene como objetivo principal usar el cálculo, en sus diferentes formas, para resolver fácilmente situaciones que se plantean en circunstancias diversas dentro de las actividades propuestas. Se intenta acercar el mundo de los problemas a los intereses de los alumnos a través de situaciones de la vida real como ir al mercado, competiciones deportivas y juegos multimedia. Otros objetivos relacionados con las capacidades de los niños son desarrollar la inteligencia verbal-lingüística, la lógico-matemática, la inteligencia espacial, la corporal-cinestésica, la interpersonal y emocional; desarrollar la creatividad; implicar a las familias en los procesos de enseñar y pensar, y en definitiva, desplegar todo el potencial del niño en esta área del conocimiento. Estas son algunas de las actividades que se ponen en marcha: manipulación de objetos en el espacio, su orientación y representación; cuantificación de magnitudes utilizando naturales; ejercicios de distintos tipos de relación de objetos como agrupación, clasificación, orden; buscar información relacionarla y organizarla; invención de problemas; hacer problemas gráficos e interpretar acciones; actividades que relacionan los precios, iniciación a la estadística, ejercicios de series numéricas y estrategias para solucionar problemas. La metodología consiste primeramente en tener una toma de contacto con espacios y materiales, luego se crean las situaciones problemáticas, se reflexiona sobre la tarea y las distintas soluciones, luego se plasma gráficamente y por último se elaboran las fichas-problemas tanto manual como informaticamente. La evaluación es continua mediante una observación de cada una de las fases del proyecto. Mensualmente se llevan a cabo reuniones del profesorado implicado en el proyecto, a fin de valorar el trabajo realizado..Madrid (Comunidad Autónoma). Consejería de Educación. Dirección General de Mejora de la Calidad de la EnseñanzaMadridMadrid (Comunidad Autónoma). Subdirección General de Formación del Profesorado. CRIF Las Acacias; General Ricardos 179 - 28025 Madrid; Tel. + 34915250893ES

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts