UCLA researchers have developed an easy-to-use risk calculator that helps predict a heart failure patient’s chances of survival for up to five years; thus, doctors can use the calculator to determine whether more or less aggressive treatment is needed. The findings were published in the January edition of the journal Circulation: Heart Failure.
The study authors note that more than 5 million Americans suffer from heart failure and that numerous factors affect patient outcomes; thus, this type of risk-assessment tool can be extremely helpful to both physicians and patients for the assessment of prognosis over time and the guidance of medical decision-making.
Because heart failure exhibits different characteristics in men and women, the team initially attempted to create a sex-specific risk model for greater accuracy, which marked a departure from previous approaches. However, they discovered that separate risk models for men and women were not necessary. “We were extremely surprised that the same exact top predictors of risk were identical in both men and women,” explained senior author Dr. Tamara Horwich, an assistant professor of medicine in the cardiology division at the David Geffen School of Medicine at UCLA. She added, “We ultimately only needed to create one unified heart failure risk model for both sexes.”
Heart failure is due to the heart’s inability to pump enough blood throughout the body. Frequently, heart failure patients have reduced left-ventricle ejection fraction, which indicates a lowered volume of blood being pumped out of this heart chamber with each beat of the heart. To develop the risk calculator, the investigators accessed data from 2,255 heart failure patients (1,569 men and 686 women) who were referred to the Ahmanson–UCLA Cardiomyopathy Center between 2000 and 2011. They evaluated 39 patient variables, including information such as age, weight, medications, lab work, and the results of diagnostic tests including echocardiography, which is an ultrasound device that can image the heart pumping in real time.
Each variable was evaluated in terms of predicting the following serious risks: mortality, the need for an urgent transplant, and the need for a mechanical pump known as a ventricular assist device. With statistical analysis, they determined that four of the 39 factors were predictive of these serious risks in both men and women and could predict survival over a five-year period.
The four variables included:
- B-type natriuretic peptide level: This peptide (BNP) is a substance secreted from the ventricles, or lower chambers of the heart, in response to changes in pressure. The level of BNP in the blood increases when heart failure symptoms worsen and decreases when the condition is more stable.
- Peak oxygen consumption: Peak oxygen consumption (PkVO2), the maximum rate of oxygen used during exercise, is tested when a patient is on a treadmill or bike. Oxygen levels decrease as heart failure worsens.
- New York Heart Association classification: This classification places a patient in one of four categories depending upon how much their physical activity is limited. The limitations are related to breathing, shortness of breath, and angina (chest pain indicative of decreased blood flow to the heart muscle).
- Heart failure medications: Patients may be taking a common heart failure medication such as an angiotensin converting enzyme inhibitor (ACEI) or an angiotensin receptor blocker (ARB).
Although women had many characteristics that differed from men (e.g., younger age at heart failure diagnosis, with higher ejection fraction) and had less coronary artery disease, these four key variables still proved the best in assessing risk in both sexes.
To develop the risk model, the researchers accessed data from patients referred to UCLA from 2000 through 2007. They then tested and validated its use with information on patients seen from 2008 through 2011. “The model was just as effective in predicting risk in early as well as later years, when newer heart-failure treatments had emerged,” noted first author Jennifer Chyu, a UCLA student researcher at the time of the study who is now at the University of Washington.
Dr. Horwich notes that the risk calculator can currently be used via an Excel spreadsheet. The team also is actively working on developing a phone app of the calculator that will be even simpler to use; a physician could simply enter in the four facts about a patient and the model would instantly calculate the annual survival risk up to five years. “Physicians can begin to use the new UCLA tool right away for their advanced heart failure patients, to calculate survival risk,” explained study author Dr. Gregg C. Fonarow, UCLA’s Eliot Corday Professor of Cardiovascular Medicine and Science and director of the Ahmanson–UCLA Cardiomyopathy Center. He noted, for example, that patients at very high risk based on the calculator might consider very aggressive therapies such as a heart transplant or the surgical implantation of a heart assist device. Conversely, patients at lower risk may be able to avoid excess treatment.
The researchers found that their risk calculator outperformed several other risk-prediction models, including the Seattle Heart Failure Model and the Heart Failure Survival Score. Dr. Horwich noted that the next phase of their study will involve testing the accuracy and utility of the UCLA model in a larger sample of patients.