Risk stratification and prognostic markers in patients with acute decompensated heart failure

Ravinder Bhukar; Shekhar Kunal; Pradeep Kumar Meena; Sourav Bansal; Himanshu Mahla; Chandrabhan Meena

Volume : IX, Issue : VIII, August - 2020

Risk stratification and prognostic markers in patients with acute decompensated heart failure

Ravinder Bhukar, Shekhar Kunal, Pradeep Kumar Meena, Sourav Bansal, Himanshu Mahla, Chandrabhan Meena

Abstract :

Introduction: Heart failure is one of the leading cause of hospitalization and death worldwide having a major impact on the health care systems. Risk stratification of these patients helps to achieve a better clinical outcome with a reduction in morbidity and mortality. Methods: This was a single centre prospective observational study wherein patients with acute decompensated heart failure were enrolled. All enrolled patients underwent detailed clinical history including symptomatology, risk factors for cardiovascular diseases and family history were recorded. All these patients underwent routine haematological and biochemical testing along with documentation of cardiac biomarkers viz. Troponin T and N–terminal pro ain natriuretic peptide (NT pro–BNP). All these patients were then followed for one year. Outcomes in form of in–hospital mortality as well as adverse cardiac events (mortality, rehospitalisation) were documented. Results: A total of 264 patients were included with mean age of 67.6 � 9.8 years. In–hospital mortality was reported in 28 patients (10.6%) while 27 (10.2%) patients died over a year of follow–up. Patients with an in–hospital mortality were older and higher NYHA class and heart rate, lower ejection fraction, systolic and diastolic blood pressure and higher cardiac troponins and NT–pro BNP levels. Multivariate logistic regression analysis revealed that heart rate, NYHA class, systolic blood pressures, NT pro–BNP and creatinine were independent predictors of mortality. Conclusions: Our study showed that acute heart failure has a substantial in–hospital as well as one year mortality rates. Use of biomarkers leads to a better risk stratification and hence an impact on outcomes.