55 research outputs found

    Atrial Fibrillation in the Setting of Acute Pneumonia: Not a Secondary Arrhythmia

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    Atrial fibrillation (AF) is the most common arrhythmia in the setting of critically ill patients. Pneumonia, and in particular communityacquired pneumonia, is one of the most common causes of illness and hospital admission worldwide. This article aims to review the association between AF and acute diseases, with specific attention to pneumonia, from the pathophysiology to its clinical significance. Even though the relationship between pneumonia and AF has been known for years, it was once considered a transient bystander. In recent years there has been growing knowledge on the clinical significance of this arrhythmia in acute clinical settings, in which it holds a prognostic role which is not so different as compared to that of the so-called "primary"AF. AF is a distinct entity even in the setting of pneumonia, and acute critical illnesses in general, and it should therefore be managed with a guidelines-oriented approach, including prescription of anticoagulants in patients at thromboembolic risk, always considering patients' individuality. More data on the significance of the arrhythmia in this setting will help clinicians to give patients the best possible care

    Impact of Glycemic and Blood Pressure Variability on Surrogate Measures of Cardiovascular Outcomes in Type 2 Diabetic Patients

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    OBJECTIVE—The effect of glycemic variability (GV) on cardiovascular risk has not been fully clarified in type 2 diabetes. We evaluated the effect of GV, blood pressure (BP), and oxidative stress on intima-media thickness (IMT), left ventricular mass index (LVMI), flow-mediated dilation (FMD), and sympathovagal balance (low frequency [LF]/high frequency [HF] ratio) in 26 type 2 diabetic patients (diabetes duration 4.41 6 4.81 years; HbA1c 6.70 6 1.25%) receiving diet and/or metformin treatment, with no hypotensive treatment or complications. RESEARCH DESIGN AND METHODS—Continuous glucose monitoring (CGM) data were used to calculate mean amplitude of glycemic excursion (MAGE), continuous overall net glycemic action (CONGA)-2, mean blood glucose (MBG), mean postprandial glucose excursion (MPPGE), and incremental area under the curve (IAUC). Blood pressure (BP), circadian rhythm, and urinary 15-F2t-isoprostane (8-iso-prostaglandin F2a [PGF2a]) were also evaluated. Subjects were divided into dipper (D) and nondipper (ND) groups according to DBP. RESULTS—IMT and LVMIwere increased inNDversusD(0.7760.08 vs. 0.6860.13 [P=0.04] and 67 6 14 vs. 55 6 11 [P = 0.03], respectively). MBG, MAGE, and IAUC were significantly associated with LF/HF ratio at night (r = 0.50, P = 0.01; r = 0.40, P = 0.04; r = 0.41, P = 0.04, respectively), MPPGE was negatively associated with FMD (r =20.45, P = 0.02), andCONGA-2was positively associatedwith LVMI (r=0.55, P=0.006).TheDsystolic BP was negatively associated with IMT (r =20.43, P = 0.03) andwith LVMI (r =20.52, P = 0.01). Urinary 8-iso-PGF2a was positively associated with LVMI (r = 0.68 P , 0.001). CONCLUSIONS—An impaired GV and BP variability is associated with endothelial and cardiovascular damage in short-term diabetic patients with optimal metabolic control. Oxidative stress is the only independent predictor of increased LV mass and correlates with glucose and BP variability

    Desarrollo de un componente de analítica para la clasificación de textos cortos dirigido a un proyecto institucional e integrable en una plataforma Web

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    Auxiliar de InvestigaciónLa clasificación de texto es una de las áreas de estudio de la disciplina del aprendizaje de máquina (en inglés Machine Learning) en donde se busca, posterior a una etapa de entrenamiento, predecir una categoría para datos de entrada que no hayan sido clasificados previamente. La longitud de los textos cortos, puede conllevar a una pérdida en la precisión de los resultados entregados por el proceso de clasificación de texto, ya que la cantidad de características aprovechables disminuye. Por lo tanto, se busca explorar una solución que permita realizar tareas de clasificación de textos cortos, con un nivel de precisión cercano al 80 %. Se desarrolló un componente de clasificación de textos cortos en el lenguaje de programación Python, haciendo uso del framework Flask el cual permite peticiones a través de un API y realiza la clasificación datasets que cumplan con el formato de entrada. Se probaron los resultados de este trabajo mediante el uso de publicaciones extraídas desde cuentas de Twitter, debido a la restricción sobre la longitud de sus publicaciones. La clasificación se realizó mediante el uso de algoritmos de aprendizaje supervisado, y en el mejor de los casos, la precisión obtenida fue cercana al 85 %.1. INTRODUCCIÓN 2. MARCO DE REFERENCIA 3. METODOLOGÍA 4. ESTADO DEL ARTE 5. DESARROLLO 6. RESULTADOS 7. CONCLUSIONES 8. TRABAJO FUTURO BIBLIOGRAFÍA ANEXOSPregradoIngeniero de Sistema

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    Sorption and condensation phenomena of volatile compounds on solid-state metalloporphyrin films

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    Metalloporphyrins have been in use since a decade as sensitive layers for thickness shear mode resonator gas sensors. In spite of several successful demonstrations of sensitivity properties a complete comprehension of the sensing mechanisms is still far to be reached also if it is rather clear that metalloporphyrins molecular structure determines peculiar physico-chemical interactions with guest molecules from gas phase. At the same time, the solubility properties are mostly regulated by the film architecture. In this paper a first attempt in this direction is presented through a detailed analysis of isotherm curves, typical for each volatile compounds, and related to a wide concentration range. Results show that a general mathematical model based on BET isotherms, fits adequately the experimental data. Fitted isotherm parameters show the different sensitivity features of metalloporphyrins aggregates, pointing out the role of both the surface structure and the diffusion processes through the film volume. © 2007 Elsevier B.V. All rights reserved
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