Usefulness of heart rate variability as a diagnostic for identifying dysfunction established

According to Dr. Daniel Weiss, a recent study of heart rate autonomic markers, and cardiac mortality published in the November issue of Heart Rhythm provides additional support for the usefulness of heart rate variability as a diagnostic for identifying dysfunction (neuropathy in diabetics and others) and cardiovascular mortality, including fatal arrhythmia or sudden cardiac death. Dr. Weiss is a cardiologist and Chief Medical Officer of Vicor Technologies. Vicor Technologies, Inc. (OTCBB: VCRT) is a biotechnology company focused on the commercialization of innovative, non-invasive medical devices and diagnostics using its patented, proprietary PD2i® nonlinear algorithm and software to stratify patients at risk of sudden cardiac death and trauma victims in need of lifesaving intervention.

"As the national debate on how to cut healthcare spending continues, diagnostics that enable inexpensive, accurate, and early identification of disease states in at-risk populations (more than a) 12 million at-risk cardiac patients, b) 23.7 million diabetics, and c) 38 million trauma incidents) -- prior to costly treatments for advanced disease or inaccurate identification -- are garnering increased attention. While awareness of HRV's potential to serve as a cost-effective diagnostic for numerous disease states has existed for quite some time, only recently has HRV, which is collected in a simple ECG, become the diagnostic of choice; the challenge is accurately unlocking the information contained in HRV to obtain a useful diagnosis," stated Dr. Weiss.

"In multiple trials comparing the efficacy of various tools in measuring HRV for diagnostic purposes, Vicor's PD2i® nonlinear algorithm has consistently proven itself to be the most consistently accurate diagnostic for identifying those at risk of sudden cardiac death and autonomic dysfunction, as well as trauma victims in need of lifesaving intervention. As such, Vicor's PD2i® nonlinear algorithm effectively lowers healthcare spending by providing an inexpensive to use diagnostic that enables accurate early diagnosis of conditions before they advance to costly disease states, and also prevents the exorbitant costs associated with inaccurate diagnosis and resulting unnecessary, ineffective treatment," Dr. Weiss concluded.