Clinical Effectiveness of Hydralazine-Isosorbide Dinitrate in African-American Patients With Heart Failure

This study sought to evaluate the effectiveness of hydralazine-isosorbide dinitrate (H-ISDN) in African Americans with heart failure (HF) with reduced ejection fraction (HFrEF).

Among African-American patients with HFrEF, H-ISDN was found to improve quality of life and lower HF-related hospitalization and mortality rates in the A-HEFT (African-American Heart Failure Trial). Few studies have evaluated the effectiveness of this therapy in clinical practice.

Veterans Affairs patients with a hospital admission for HF between 2007 and 2013 were screened. Inclusion criteria included African-American race, left ventricular ejection fraction <40%, and receipt of Veterans Affairs medications. Exclusions were documented contraindications to H-ISDN, creatinine >2.0 mg/dl, or intolerance to angiotensin-converting enzyme inhibitors or angiotensin receptor blockers. Adjusted hazard ratios were calculated for patients who received H-ISDN 6-months before admission compared with patients who did not receive H-ISDN, by using inverse probability weighting of propensity scores and a time to death analysis for 18 months of follow-up. Propensity scores were generated using patients' characteristics, left ventricular ejection fraction, laboratory values, and hospital characteristics.

The final cohort included 5,168 African-American patients with HF (mean age 65.2 years), with 15.2% treated with H-ISDN before index admission. After 18 months, there were 1,275 reported deaths (24.7%). The adjusted mortality rate at 18 months was 22.1% for patients receiving H-ISDN treatment and 25.2% for untreated patients (p = 0.009); adjusted hazard ratio: 0.85 (95% confidence interval: 0.73 to 1.00; p = 0.057).

H-ISDN remains underused in African-American patients with HFrEF. In this cohort, the study found that H-ISDN use was associated with lower mortality rates in African-American patients with HFrEF when controlling for patient selection by using an inverse probability weighting of propensity scores.