Research paper published in the latest issue of JAMA says that heart patients who are more at risk from death may get the fewer of medications.
Heart failure affects more than 5 million people in Canada and the United States and is associated with a high death rate, according to background information in the article. Medications shown to reduce the risk of illness and death from this condition include angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), and beta-adrenoreceptor antagonists. These drug classes have been studied extensively and recommended strongly by disease management guidelines, given their proven benefit of reducing the risk of death in patients at the highest risk. It might be expected that these individuals would be more likely to receive these medications.
Researchers from the University of Toronto examined the use of drug therapies for heart failure in relation to predicted 1-year death rates. The patients for this study included 9,942 hospitalized patients with heart failure. The researchers evaluated 1,418 patients, aged 79 years or younger, with documented left ventricular ejection fraction (a measure of the heart's pumping ability) of 40 percent or less and with low-, average-, and high-predicted risk of death within 1 year. All patients survived to hospital discharge.
Administration of ACE inhibitors, ACE inhibitors or ARBs, and beta-adrenoreceptor antagonists were evaluated according to predicted risk of death.
After accounting for varying survival time and potential contraindications to therapy, low-risk patients were 61 percent more likely to receive ACE inhibitors or ARBs; and 80 percent more likely to receive beta-adrenoreceptor antagonists compared with high-risk patients.
In conclusion the researchers had said that the predicted and observed risks of death in patients with heart failure were inversely associated with discharge and post discharge administration of potentially life-saving drug therapies. This finding is particularly important because patients at highest risk of death have great need for effective treatment. Clinical use of quantitative multifactorial risk profiles or algorithms that convey information regarding probability of poor outcomes could be applied to better identify such patients.