Publication: Generación y validación de un modelo predictivo en pacientes con insuficiencia cardiaca aplicable en servicios de urgencias y centros de atención primaria
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2018-04-09
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Universidad Complutense de Madrid
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Abstract
La mortalidad de los pacientes con insuficiencia cardiaca sigue siendo muy elevada a pesar de los esfuerzos realizados en los últimos años encaminados a mejorar su manejo y su pronóstico. Esto puede explicarse en parte por el cambio poblacional (con pacientes de mayor edad y mayor número de comorbilidades) y por las dificultades para identificar pacientes de alto riesgo. Debido a todo lo expuesto previamente nos encontramos ante un nuevo escenario, con pacientes de mayor edad y pluripatológicos, condicionando el pronóstico de estos pacientes y requiriendo un manejo multidisciplinar de los mismos. Por ello son necesarias nuevas herramientas de ayuda en el manejo de estos pacientes, que nos permitan identificar pacientes de alto riesgo, así como pacientes subsidiarios de manejo ambulatorio. Uno de los principales problemas de las herramientas pronósticas elaboradas hasta ahora es que requieren variables complejas y de difícil acceso en centros de atención primaria y servicios de urgencias. Esto es importante, ya que dichos servicios son el principal filtro de este tipo de pacientes y donde se realiza la toma inicial de decisiones. El objetivo de este estudio es describir el patrón de mortalidad de los pacientes con IC, describir las variables asociadas con la mortalidad al año y establecer un modelo pronóstico de fácil acceso y aplicación universal en función de dichas variables...
Heart failure (HF) mortality remains very high despite the efforts in recent years to improve their management and prognosis. This can be explained in part by the population change (with older patients and greater number of comorbidities) and the difficulties in identifying high risk patients. For that reason, we are faced with a new scenario, with older patients and with greater comorbidities), conditioning the prognosis of these patients and requiring a multidisciplinary management of them. Therefore, new tools are needed to manage these patients, which allow us to identify high risk patients, as well as subsidiary outpatient management patients. One of the main problems with the prognostic tools developed so far is that they require complex and its access is dificult in primary care centers and emergency departments. This is important, since these services are the main filter of this type of patients and where the initial decisions are taken. The objective of this study is to describe the mortality pattern of patients with HF, to describe the associated variables with mortality per year and to establish a predictive model of easy access and universal application based on these variables...
Heart failure (HF) mortality remains very high despite the efforts in recent years to improve their management and prognosis. This can be explained in part by the population change (with older patients and greater number of comorbidities) and the difficulties in identifying high risk patients. For that reason, we are faced with a new scenario, with older patients and with greater comorbidities), conditioning the prognosis of these patients and requiring a multidisciplinary management of them. Therefore, new tools are needed to manage these patients, which allow us to identify high risk patients, as well as subsidiary outpatient management patients. One of the main problems with the prognostic tools developed so far is that they require complex and its access is dificult in primary care centers and emergency departments. This is important, since these services are the main filter of this type of patients and where the initial decisions are taken. The objective of this study is to describe the mortality pattern of patients with HF, to describe the associated variables with mortality per year and to establish a predictive model of easy access and universal application based on these variables...
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Tesis inédita de la Universidad Complutense de Madrid, Facultad de Medicina, Departamento de Medicina, leída el 29/05/2017