Abstract

Introduction

Heart failure is the end stage for all heart diseases. Because of longevity of life and modern diagnostic equipments and advanced management, disease burden due to heart failure keeps on increasing. In developing countries like India, infectious disease like Rheumatic valvular heart disease still contributing much of this disease burden. Because of the westernisation trend non-infectious causes like metabolic disease started increasing in the last decade¹.  

For a proper and methodical algorithmic approach in the management of heart failure, we need a simple but effective prognostic model. This model should contain all the variables which are easily available, cheaper and prognostically significant. They have to predict the outcome in an easily explained way, so that we can discuss with the patients and relatives about the prognosis and the need for further advanced interventions.

Over a period of decade, various attempts have been made for this simple but effective model, which includes variables like BNP, NT-pro BNP, C Reactive protein, high sensitivity CRP,  Interleukin-6, ESR, and echocardiographic parameters². But, nothing fits into the category of ‘ideal’. Variables like BNP has helped much in the diagnosis and prognosis determination of heart failure cases⁸. However, their added benefits in guiding therapy remain unknown .Other caveat in using these variables is, these markers are not unique for heart failure alone and these can also be elevated in other clinical conditions. Therefore, natriuretic peptides are not always sufficient.