To underscore the magnitude of the problem and its impact on the U.S. healthcare system, Dr. Zareba referenced the following statistics

· According to the American Heart Association, heart failure affects nearly 5.7 million Americans of all ages and is responsible for more hospitalizations than all forms of cancer combined. It is the leading cause for hospitalization among Medicare patients.


· Heart failure is the fastest-growing clinical cardiac disease entity in the U.S., affecting 2% of the population.

· Each year, 550,000 new cases of heart failure are diagnosed and 300,000 deaths are caused by heart failure.

· Nearly 2% of all hospital admissions in the U.S. are for decompensated heart failure; heart failure is the most frequent cause of hospitalization in patients older than 65 years, with an annual incidence of 10 per 1,000.

· The average duration of hospitalization for heart failure is 6 days.

Dr. Zareba explained that heart failure patients typically experience an insidious downward spiral. Their heart and overall physiology -- cardiac shape and function, and neurohormonal balance -- undergo "negative remodeling" resulting in more severe heart failure and eventually death. Initially, despite these negative changes having already begun, heart failure patients may appear relatively stable.

"Being able to identify those heart failure patients entering the downward spiral, especially in the early stages when interventions may be far more likely to succeed - be they lifestyle/nutrition, pharmacological, or device/procedural - has the potential to result in improved quality of life and vast cost savings for our overburdened healthcare system. The results of 'Prognostic Significance of Point Correlation Dimension Algorithm (PD2i) in Chronic Heart Failure' study are of major importance for those involved in the search to identify a means of enhancing risk stratification of heart failure patients eligible for ICD or CRT-D, " Dr. Zareba continued.

The goal of "Prognostic Significance of Point Correlation Dimension Algorithm (PD2i) in Chronic Heart Failure" was to evaluate the ability of Vicor's PD2i® nonlinear algorithm, to predict cardiac events in the 537 chronic heart failure patients enrolled in the MUSIC Trial; MUSIC Trial participants were followed for an average period of 44 months. The conclusion of the University of Rochester researchers who conducted the study is that the PD2i® nonlinear algorithm and software is predictive of total mortality, cardiac death, and heart failure death in patients with left ventricular ejection fraction of less than or equal to 35%. With a hazard ratio of 2.34 and a P value of 0.023 for congestive heart failure mortality, a hazard ratio of 1.89 and a p value of .013 for cardiac mortality and a hazard ration of 1.95 and a p value of .004 for total mortality, the study results are highly statistically significant and demonstrated the ability of the PD2i Analyzer™ to identify those patients at an elevated risk of total mortality, cardiac mortality and congestive heart failure death.

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