Multi-Level Diagnostic Biomarker Panels for the Precise Stratification of Patients with Heart Failure: Potential Application for an Improved Disease Management

Chronic diseases are increasing today, it is a challenge to fight against this kind of diseases which affect especially older populations, and most of them are related to lack of self-care, sedentary and Western lifestyle. As an example of these diseases emerges Heart Failure (HF). Related costs of HF are far from lowering in the next few years unless changes take place, and the management of HF and other chronic diseases take a new direction. This evolution must be done taking new technologies and computerization of Healthcare into account. The objective of this project is to propose a new method to manage the immediate future of HF patients thanks to the situation and qualities of the patient. New technologies and their use in Healthcare and research include applications based on text mining. This kind of tools let researchers make faster and more precise investigations. An example of those tools is SCAIView, an application developed by the Fraunhofer Institute for Algorithms and Scientific Computing based on PubMed library. Research was performed using SCAIView and PubMed; the information obtained was used to build a HF patient stratification into 5 categories, depending on the patient’s results on molecular biomarkers, invasive and non-invasive parameters. Stratification is based on age, body mass index, sleep disordered breathing, NYHA classification, blood glucose levels, diagnosis of arrhythmia, diagnosis of structural defects, blood pressure, diagnosis of anaemia, glomerular filtration rate, and levels of the biomarkers N-terminal pro-Beta Natriuretic Peptide (NT-proBNP), Galectin 3, soluble ST2 and troponin I. The 5 classes distinguish 5 different levels of severity and risk depending on the results from the parameters mentioned. The classification gives out information about the momentary situation of the patient and where doctors and specialists should focus to prevent a worse situation. By constant evaluation and monitoring of the patients, HF costs can be reduced, sudden hospitalizations can be prevented depending on each patient, and deterioration can be predicted. Molecular tests and physical control are able to give in the immediate future precise diagnostics and solutions, for changing today’s reactive Healthcare to a modern and precise model