Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe

Riociguat treatment in patients with chronic thromboembolic pulmonary hypertension: Final safety data from the EXPERT registry

Objective: The soluble guanylate cyclase stimulator riociguat is approved for the treatment of adult patients with pulmonary arterial hypertension (PAH) and inoperable or persistent/recurrent chronic thromboembolic pulmonary hypertension (CTEPH) following Phase

Depression influence on memory and executive functions in patients with post-traumatic stress disorders victims of the army conflic in Colombia

El trastorno de estrés postraumático (TEPT) es una patología neuropsiquiátrica. Se caracteriza por el hecho de que el sujeto ha estado expuesto a situaciones estresantes que le han provocado inestabilidad física, emocional y mental en diferentes aspectos de su vida diaria. Los sujetos diagnosticados de TEPT presentan un cuadro clínico de depresión severa que se relaciona con un déficit en su funcionamiento neurocognitivo, específicamente en tareas de memoria (memoria operativa y memoria verbal inmediata) y en funciones ejecutivas (fluidez verbal semántica, inhibición, planificación y control de su conducta inmediata). Objetivo: Identificar la influencia de la depresión en la memoria y el funcionamiento ejecutivo en pacientes con TEPT víctimas del conflicto militar en Colombia. Metodología: Participantes: 50 personas diagnosticadas con SDPT, depresión y sin demencia (35 hombres y 15 mujeres) participaron en este estudio. Los individuos fueron reclutados de la unidad de víctimas adscrita al municipio de Palmira, Valle del Cauca, Colombia en un período de tiempo de 2015 a 2017, y un grupo control de 50 sujetos sanos con el objetivo de comparar los resultados y poder Establecer diferencias y resultados robustos intragrupo. Resultados: Los individuos con TEPT muestran una sintomatología depresiva mayor que los del grupo control. Se encontró que la depresión se relaciona con el déficit en la memoria verbal inmediata, memoria operativa y funciones ejecutivas en sujetos con TEPT víctimas del conflicto armado en Colombia. Conclusión: Es necesario hacer planes de neurorrehabilitación funcional para los individuos diagnosticados con PTSD con el fin de mejorar su calidad de vida y ralentizar su cuadro clínico a un postraumático diagnosticar la demencia. El gobierno necesita crear políticas de salud mental diseñadas para contrarrestar esta patología neuropsiquiátrica; nuestro principal objetivo, y el funcionamiento neurocognitivo, neurorrehabilitación neuroconductual / emocional, individual y familiar de personas con TEPT víctimas de el conflicto militar en Colombia, evitando así cuadros clínicos de alexitimia postraumática.Introduction: Post traumatic Stress Disorder (PTSD) is a neuropsychiatric pathology. It is characterized by the fact that the subject has been exposed to stressful situations which have caused them physical, emotional and mental instability in different aspects of their daily life. The subjects diagnosed with PTSD show a clinical picture of severe depression which is related to a deficit in their neurocognitive functioning, especifically in memory tasks (operative memory and inmediate verbal memory) and in executive functions (semantic verbal fluency, inhibition, planning and control of their immediate conduct). Objective: To indentify the influence of depression on memory and the executive functioning in patients with PTSD who are victims of the army conflict in Colombia. Methodology: Participants: 50 people diagnosed with PTDS, depression, and without dementia (35 men and 15 women) participated in this study. The individuals were enlisted from the unit of victims affiliated with the municipality of Palmira, Valle del Cauca, Colombia in a period of time from 2015 through 2017, and a control group of 50 healthy subjects with the objective to compare the results and be able to establish differences and intra-group robust results. Results: Individuals with PTSD show a higher depressive symptomatology than the ones in the control group. It was found that depression is related to the deficit in the immediate verbal memory, operative memory, and the executive functions in subjects with PTSD victims of the army conflict in Colombia.Conclusion: It is necessary to make plans for functional neurorehabilitation for individuals diagnosed with PTSD in order to improve their quality of life and to slow down their clinical picture to a posttraumatic dementia diagnose. The government needs to create mental health policies designed to counteract this neuropsychiatric pathology ;our main goal ,and the neurocognitive functioning, neurobehavioral/emotional, individual, and family neurorehabilitation of people with PTSD victims of the army conflict in Colombia, thus preventing clinical pictures of post-traumatic [email protected]

SOPHIA: System for Ophthalmic Image Acquisition, Transmission, and Intelligent Analysis

Ocular diseases are one of the main causes of irreversible disability in people in productive age. In 2020, approximately 18% of the worldwide population was estimated to suffer of diabetic retinopathy and diabetic macular edema, but, unfortunately, only half of these people were correctly diagnosed. On the other hand, in Colombia, the diabetic population (8% of the country’s total population) presents or has presented some ocular complication that has led to other associated costs and, in some cases, has caused vision limitation or blindness. Eye fundus images are the fastest and most economical source of ocular information that can provide a full clinical assessment of the retinal condition of patients. However, the number of ophthalmologists is insufficient and the clinical settings, as well as the attention of these experts, are limited to urban areas. Also, the analysis of said images by professionals requires extensive training, and even for experienced ones, it is a cumbersome and error-prone process. Deep learning methods have marked important breakthroughs in medical imaging due to outstanding performance in segmentation, detection, and disease classification tasks. This article presents SOPHIA, a deep learning-based system for ophthalmic image acquisition, transmission, intelligent analysis, and clinical decision support for the diagnosis of ocular diseases. The system is under active development in a project that brings together healthcare provider institutions, ophthalmology specialists, and computer scientists. Finally, the preliminary results in the automatic analysis of ocular images using deep learning are presented, as well as future work necessary for the implementation and validation of the system in Colombia.Las enfermedades oculares son una de las principales causas de incapacidad irreversible en personas en edad productiva. En 2020, la población mundial con retinopatía diabética y edema macular diabético está estimada como el 18% de la población mundial, aproximadamente, desafortunadamente, solo la mitad de estas personas fueron diagnosticadas correctamente. Por otro lado, en Colombia, la población diabética (8% de la población total del país) presenta o ha presentado alguna complicación ocular que ha llevado a otros costos asociados y, en algunos casos, ha provocado limitación de la visión o ceguera. Las imágenes de fondo de ojo son la fuente de información ocular más rápida y económica que puede proveer una valoración clínica del estado de la retina de los pacientes. Sin embargo, el número de oftalmólogos es insuficiente, la atención de estos expertos está limitada a zonas urbanas, y el análisis de dichas imágenes por parte de profesionales requiere una amplia formación; incluso para los más experimentados, es un proceso engorroso y propenso a errores. Los métodos de aprendizaje profundo han marcado avances importantes en imágenes médicas debido al desempeño sobresaliente en tareas de segmentación, detección y clasificación de enfermedades. Este artículo presenta SOPHIA, un sistema basado en el aprendizaje profundo para la adquisición, transmisión, análisis inteligente y soporte de decisiones clínicas para el diagnóstico de enfermedades oculares. El sistema se encuentra en desarrollo activo en un proyecto que reúne a instituciones proveedoras de salud, especialistas en oftalmología e informáticos. Finalmente, los resultados preliminares en el análisis automático de imágenes oculares utilizando el aprendizaje profundo son presentados, y se discute el trabajo futuro necesario para la implementación y validación del sistema en Colombia