Is it time to start with device-based prognosticators?

Abstract

Do we really need to look into device-based prognostic indicators of mortality of heart failure patients? After all, numerous studies demonstrated the predictive importance of a large number of parameters including natriuretic peptides, inflammatory markers, and electrocardiographic parameters, not to mention innumerable demographic and readily available blood tests. Thus, one could view the excellent study by Singh et al. 1 in this issue of the journal as an academic exercise in prognostication of the outcome of heart failure patients. Indeed, we already have models and scores aiming at a better prognostic performance across the heart failure spectrum, i.e. the Heart Failure Survival Score, the Seattle Heart Failure Model, the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure predictive schemes, the Acute Decompensated Heart Failure National Registry regression tree discrimination, just to mention some of them. However, the study by Singh et al. 1 provides more reasons to care about prognostic indicators in general and, in this case, based on device diagnostics. Indeed, currently available models and scores are imperfect for predicting major events, such as implantation of left ventricular assist device, heart transplantation, and mortality. The authors used a rather simple dynamic predictive model based on device diagnostic data in risk stratification of out-patient heart failure patients treated with cardiac resynchronization therapy (CRT). They showed, e.g., that higher heart rate variability measured by Standard Deviation of the averages of intrinsic R-R intervals (SDANN) at two points in time (2 weeks and 3 months after CRT implantation), and relative large increase from 2 weeks value to 3 months value were associated with a decreased risk of death. Although the … *Corresponding author. Tel: +41 91 805 3340, Fax: +41 91 805 3167, Email: angelo.auricchio{at}cardiocentro.org