Defining and Refining Heart Failure Risk Stratification to Optimize Patient Selection for Cardiac Transplantation

Abstract

VO2, BNP, GFR, RAP, CI, LVEDP, EF, Na, BUN, MR, LVEDD, PCWP, PVCs, VT, QRS, LBBB, COPD, DM, TpnI, alb, CAD, OSA, Hct, RDW, CRT, ICD, HRV—the complex alphabet soup of heart failure risk assessment used to inform clinical decision making, select patient cohorts for trials, and ensure that expensive and supply-limited treatments are utilized in the most effective and equitable manner. Despite the seeming complexity of this task, heart failure clinicians have become facile at integrating multiple distinct variables into a cohesive understanding of risk using baseline patient characteristics, measures of cardiac structure and function, biomarkers, and assessment of functional capacity. The prognostic significance of many risk-associated parameters, such as ejection fraction, ventricular size, and the pathogenesis of heart failure are firmly established. However, recognition of the importance of common comorbidities and the rapidly evolving field of novel biomarkers that represent perturbation of normal biological pathways or markers of early organ damage have reshaped and refined contemporary risk assessment. More recently, larger datasets have facilitated the derivation and validation of multivariable risk-prediction models, such as the Heart Failure Survival Score, the Seattle Heart Failure Model, and the ESCAPE Risk Score.1–3 Article see p 6 In this issue of Circulation: Heart Failure , Kato et al4 re-examine the pivotal role of cardiopulmonary exercise testing in heart failure risk assessment and extend the sentinel work by Mancini that validated VO2 as a potent predictor of short- and intermediate-term mortality.5 Mancini’s original observation that a peak VO2 <14 mL/kg per min was associated with excessive morality led to its …