'Acute Heart Failure': Should We Abandon the Term Altogether?

Acute Heart Failure: From The Emergency Department to the Intensive Care Unit

Acute heart failure (AHF) is a frequent cause of hospitalization around the world and is associated with high in-hospital and post-discharge morbidity and mortality. This review summarizes data on diagnosis and management of AHF from the emergency department to the intensive care unit. While more evidence is needed to guide risk stratification and care of patients with AHF, hospitalization is a key opportunity to optimize evidence-based medical therapy for heart failure. Close linkage to outpatient care is essential to improve post-hospitalization outcomes.

Clinical Predictive Modeling of Heart Failure: Domain Description, Models' Characteristics and Literature Review

This study attempts to identify and briefly describe the current directions in applied and theoretical clinical prediction research. Context-rich chronic heart failure syndrome (CHFS) telemedicine provides the medical foundation for this effort. In the chronic stage of heart failure, there are sudden exacerbations of syndromes with subsequent hospitalizations, which are called acute decompensation of heart failure (ADHF). These decompensations are the subject of diagnostic and prognostic predictions. The primary purpose of ADHF predictions is to clarify the current and future health status of patients and subsequently optimize therapeutic responses. We proposed a simplified discrete-state disease model as an attempt at a typical summarization of a medical subject before starting predictive modeling. The study tries also to structure the essential common characteristics of quantitative models in order to understand the issue in an application context. The last part provides an overview of prediction works in the field of CHFS. These three parts provide the reader with a comprehensive view of quantitative clinical predictive modeling in heart failure telemedicine with an emphasis on several key general aspects. The target community is medical researchers seeking to align their clinical studies with prognostic or diagnostic predictive modeling, as well as other predictive researchers. The study was written by a non-medical expert.