Europace Advance Access published online on September 13, 2009
Europace, doi:10.1093/europace/eup250
CLINICAL RESEARCH
Device diagnostics and long-term clinical outcome in patients receiving cardiac resynchronization therapy
1 Cardiac Arrhythmia Service, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, GRB 109, Boston, MA 02114-2696, USA; 2 University of Massachusetts Medical Center, Worcester, MA, USA; 3 Duke University Medical School, Durham, NC, USA; 4 Boston Scientific CRM, St Paul, MN, USA; 5 The Integra Group, Brooklyn Park, MN, USA; 6 Cardiovascular Associates of Mesa, Mesa, AZ, USA
Aims: This retrospective analysis sought to develop and validate a model using the measured diagnostic variables in cardiac resynchronization therapy (CRT) devices to predict mortality.
Methods and results: Data used in this analysis came from two CRT studies: Cardiac Resynchronization Therapy Registry Evaluating Patient Response with RENEWAL Family Devices (CRT RENEWAL) (n = 436) and Heart Failure-Heart Rate Variability (HF-HRV) (n = 838). Patients from CRT RENEWAL were used to create a model for risk of death using logistic regression and to create a scoring system that could be used to predict mortality. Results of both the logistic regression and the clinical risk score were validated in a cohort of patients from the HF-HRV study. Diagnostics significantly improved over time post-CRT implant (all P < 0.001) and were correlated with a trend of decreased risk of death. The regression model classified CRT RENEWAL patients into low (2.8%), moderate (6.9%), and high (13.8%) risk of death based on tertiles of their model predicted risk. The clinical risk score classified CRT RENEWAL patients into low (2.8%), moderate (10.1%), and high (13.4%) risk of death based on tertiles of their score. When both the regression model and the clinical risk score were applied to the HF-HRV study, each was able to classify patients into appropriate levels of risk.
Conclusion: Device diagnostics may be used to create models that predict the risk of death.
Key Words: Heart failure, Heart rate, Heart rate variability, Autonomic nervous system, Biventricular pacing, Mortality
* Corresponding author. Tel: +1 617 726 4662, Fax: +1 617 726 3852, Email: jsingh{at}partners.org
Manuscript submitted 7 May 2009. Accepted after revision 10 August 2009.