Feature: New HF risk marker may gauge autonomic nervous system
Why do some heart failure (HF) patients spiral downhill quickly while others do not? The answer may lie in how hard the autonomic nervous system is compensating to mask symptoms and measuring that stress could better triage patients to receive implantable devices.

"We know that adverse events happen to people who have heart failure. But some patients with heart failure are at a greater risk of these events and we want to be able to risk stratify them," Daniel N. Weiss, MD, director of the Jim Moran Heart and Vascular Center at Holy Cross Hospital in Fort Lauderdale, Fla., told Cardiovascular Business News.

The current paradigm for determining risk is to use standard clinical parameters such as vital signs, as well as history and medication use, but it is subjective for the most part, Weiss said. He and colleagues are developing a method that would add another metric to the clinical diagnosis that it is not subjective.

The test is a proprietary analysis of an ECG that links heart rate variability with abnormal stress to the autonomic nervous system. The technology, PD2i CA (cardiac analyzer) (Vicor Technologies) is currently in clinical trials and a report about its progress will be presented at ACC11 by Wojciech Zareba, MD, PhD, director of the Heart Research Follow-up Program at the University of Rochester Medical Center in Rochester, N.Y.

The aim of the retrospective study by Zareba and colleagues was to evaluate the ability of PD2i algorithm to predict cardiac events in the 537 chronic HF patients enrolled in the MUSIC (Merte Subita en Insufficiencia Cardiaca) trial, which is being conducted in partnership with the Catalan Institute of Cardiovascular Sciences in Barcelona, Spain.

MUSIC trial participants were followed for an average period of 44 months and researchers concluded that the novel risk marker was significantly predictive of total mortality, cardiac death and heart failure death in patients with left ventricular ejection fraction of less than or equal to 35 percent.

The results signify a better way to risk stratify HF patients who are eligible for implantable cardioverter-defibrillators (ICDs) or cardiac resynchronization therapy with defibrillator (CRT-D) devices, said Weiss, who also serves as the CMO of Vicor Technologies.

In an earlier study of 918 patients admitted to six emergency departments for chest pain and a determination of acute MI risk, the PD2i algorithm was able to risk stratify those at imminent risk of arrhythmic death with a 96 percent sensitivity (with a 99 percent negative predictive value) and 85 percent specificity (Ther Clin Risk Manag 2008;4:689–697).

The algorithm examines the interaction between the brain and the heart that is being done subconsciously—the autonomic nervous system. "If everything is functioning well, we get one pattern; if not, we get another pattern," Weiss said.

In many acute and chronic disease and trauma conditions, the body will try to compensate for the dysfunction by parceling resources to the areas of the body that are suffering. While this works very well acutely, in chronic diseases this compensation can take its toll on the body, using up valuable reserves.

"The body internally knows how sick you are and is reacting to it. We look for a pattern of heartbeats that tells us how the autonomic system is functioning," Weiss said. "While on the outside, patients may appear to be doing fine, considering they have heart failure, on the inside, their reserves are being used up quickly and they are at a greater risk of having adverse events."

The test takes about 15 minutes to administer and if positive, physicians can use this information to more aggressively treat patients or to decide it may not be time to release a patient from the hospital.

The algorithm received FDA 510(k) approval in 2009 as a means to identify the presence of diabetic autonomic neuropathy in asymptomatic patients with diabetes. Researchers also are testing the algorithm in military and civilian trauma, concussions and in elite athletes to determine optimal training regimens.

Researchers also have found that the marker can identify those admitted to the intensive care unit who are at a greater risk of dying within 30 days.