Predicting Adverse Outcomes in Heart Failure Patients

The European Society of Cardiology’s guidelines recommend ivabradine for heart failure (HF) patients with normal sinus rhythm who nonetheless remain symptomatic.

This recommendation was added after the large, international SHIFT trial determined the sinus node inhibitor lowers and stabilizes heart rate (HR) in patients with systolic HF without inducing significant bradycardia, ventricular arrhythmias, or supraventricular arrhythmias.

Using SHIFT’s findings, a team of researchers developed an objective prognostic model that could help clinicians prioritize risk factors in HF patients. The results, which were published in the April 2015 issue of the International Journal of Cardiology, identified the top 10 risk factors for morbidity and mortality in patients with chronic HF and elevated HR.

The researchers examined 4 adverse outcomes: cardiovascular death or HF hospitalization, all-cause mortality, cardiovascular mortality, and HF hospitalization.

On all of those outcomes, they found patients with the following 7 characteristics were at increased risk for morbidity or mortality:

• Increased resting HR, with every 10-bpm increase elevating risk significantly
• Low ejection fraction, with a 5% decrease associated with a 20% increase in risk
• Elevated creatinine
• New York Heart Association class III/IV, which increased risk by 43%
• Longer HF duration, with every 2 years of disease associated with a 7% to 9% increased risk
• History of left bundle branch block
• Low systolic blood pressure

Other predictors of adverse outcomes included low body mass index (the so-called “obesity paradox”), male gender, ischemic HF, and presence of atrial fibrillation/flutter, as well as 2 other paradoxical factors: low total cholesterol and no hyperlipidemia or dyslipidemia.

Unlike many other complex models used to predict HF outcomes, this model relies on readily available clinical characteristics to produce prognostic information in patients with chronic HF, systolic dysfunction, and elevated HR. The researchers suggest it could be a useful tool for clinicians who need to estimate an individual patient’s risk.