Patterns and Predictors of Evidence-Based Medication Continuation Among Hospitalized Heart Failure Patients (from Get With the Guidelines-Heart Failure).

摘要

Hospitalized patients with heart failure and decreased ejection fraction are at substantial risk for mortality and rehospitalization, yet no acute therapies are proven to decrease this risk. Therefore, in-hospital use of medications proved to decrease long-term mortality is a critical strategy to improve outcomes. Although endorsed in guidelines, predictors of initiation and continuation of angiotensin-converting enzyme (ACE) inhibitors/angiotensin receptor blockers (ARBs), beta blockers, and aldosterone antagonists have not been well studied. We assessed noncontraindicated use patterns for the 3 medications using the Get With the Guidelines-Heart Failure (GWTG-HF) registry from February 2009 through March 2010. Medication continuation was defined as treatment on admission and discharge. Multivariable logistic regression using generalized estimating equations was used to determine factors associated with discharge use. In total 9,474 patients were enrolled during the study period. Of those treated before hospitalization, overall continuation rates were 88.5% for ACE inhibitors/ARBs, 91.6% for beta blockers, and 71.9% for aldosterone-antagonists. Of patients untreated before admission, 87.4% had ACE inhibitors/ARBs and 90.1% had beta blocker initiated during hospitalization or at discharge, whereas only 25.2% were started on an aldosterone antagonist. In multivariate analysis, admission therapy was most strongly associated with discharge use (adjusted odds ratios 7.4, 6.0, and 20.9 for ACE inhibitors/ARBs, beta blockers, and aldosterone antagonists, respectively). Western region, younger age, and academic affiliation were also associated with higher discharge use. Although ACE inhibitor/ARB and beta-blocker continuation rates were high, aldosterone antagonist use was lower despite potential eligibility. In conclusion, being admitted on evidence-based medications is the most powerful, independent predictor of discharge use.